Best Artificial Intelligence Courses

Find the best online Artificial Intelligence Courses for you. The courses are sorted based on popularity and user ratings. We do not allow paid placements in any of our rankings. We also have a separate page listing only the Free Artificial Intelligence Courses.

Artificial Intelligence A-Z™: Learn How To Build An AI

Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications!

Created by Hadelin de Ponteves - AI Entrepreneur

"]

Students: 160976, Price: $129.99

Students: 160976, Price:  Paid

*** AS SEEN ON KICKSTARTER ***

Learn key AI concepts and intuition training to get you quickly up to speed with all things AI. Covering:

  • How to start building AI with no previous coding experience using Python
  • How to merge AI with OpenAI Gym to learn as effectively as possible
  • How to optimize your AI to reach its maximum potential in the real world

Here is what you will get with this course:

1. Complete beginner to expert AI skills – Learn to code self-improving AI for a range of purposes. In fact, we code together with you. Every tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means.

2. Code templates – Plus, you’ll get downloadable Python code templates for every AI you build in the course. This makes building truly unique AI as simple as changing a few lines of code. If you unleash your imagination, the potential is unlimited.

3. Intuition Tutorials – Where most courses simply bombard you with dense theory and set you on your way, we believe in developing a deep understanding for not only what you’re doing, but why you’re doing it. That’s why we don’t throw complex mathematics at you, but focus on building up your intuition in coding AI making for infinitely better results down the line.

4. Real-world solutions – You’ll achieve your goal in not only 1 game but in 3. Each module is comprised of varying structures and difficulties, meaning you’ll be skilled enough to build AI adaptable to any environment in real life, rather than just passing a glorified memory “test and forget” like most other courses. Practice truly does make perfect.

5. In-course support – We’re fully committed to making this the most accessible and results-driven AI course on the planet. This requires us to be there when you need our help. That’s why we’ve put together a team of professional Data Scientists to support you in your journey, meaning you’ll get a response from us within 48 hours maximum.

Artificial Intelligence in Web Design Certification (2021)

MBA in Creative Arts, Design and Animation: Level 2 - Part 1 course that teaches Artificial Intelligence (AI) Web Design

Created by Srinidhi Ranganathan - Digital Marketing Legend - India's Top Udemy Instructor

"]

Students: 149870, Price: $24.99

Students: 149870, Price:  Paid

Welcome to Level 2 of the series "MBA in Creative Arts, Design and Animation".

What is this 2021 Website Design course all about?

Website design is the art and science of building the look, feel, and how a website functions in a nutshell. This course is having clear, concise, and easy to use website design technologies and will ultimately lead to a better user experience for your custom audience or clients. There are many aspects of successful website design like HTML, colors, layouts, text size, graphics, and so much more. But, this course is a huge differentiator in the design field as it uses artificial intelligence-based website design state-of-the-art technologies that are covered nowhere in the world. If you've been wondering how to learn website design, you've come to the right place - after all.

Why website design is needed for a successful online presence?

Having a good website is the backbone of every business and to achieve this successful feat, typically we need website design developers, content marketers, SEO specialists, etc. in an organization. But, some website design developers charge a lot of money outside in the market and other freelancing marketplaces to design websites using content management platforms like WordPress CMS. In fact, tools like Bookmark in website design will help advance your web-design career, altogether. This course is both a beginner's website design course and an advanced course for web developers.

Jobs in Website Design in 2021:

According to Glassdoor, you can expect an average salary of $64,468 in the United States for doing website design. As your experience grows in website design all the time, you can expect to see higher salary ranges in the upcoming future. For example, you can expect an average Junior Website Designer to make around $62k in the United States alone and Rs. 2-3 Lakhs in India. As a Front End Website Design Developer, you can expect to make over $90k abroad.

Introduction to the website design course powered by Artificial Intelligence technology:

In the beginning website, design developers and designers designed websites using HTML. Soon, the internet was formless and empty, darkness was over the surface of the deep web, and the Spirit of Code was hovering over the pinnacle of utmost ignorance.

We’ve come a long way from that time. The internet is still a dark, dreadful place, but it’s much more stylish, sophisticated, and amazing now. Website Design has grown exponentially in scale and sophistication over the last few years, thanks to new Artificial Intelligence-based website creation tools that are dominating the digital marketing industry.

The technology is still in its infancy stage, however - but machine learning is enabling artificial design intelligence (ADI) to understand creative rules and apply them independently and in an intuitive and more attractive way - for that matter. Artificial design technology will soon be advanced enough to automate a lot of web design work in the near future too. New thought leaders would emerge and new courses like this would serve to be game-changers in the artificial intelligence-powered digital marketing space.

This game-changing course focuses on "Artificial Intelligence in Web Design Certification" taught by Digital Marketing Legend "Srinidhi Ranganathan" will cover artificial intelligence tools in website, chatbot design, and analytics in website design which will help you to create a website in merely minutes in 2021.

I will teach you to easily create websites in the fastest time possible using advanced website design tools or design techniques and customize your site look and feel according to your requirement in a simple drag-and-drop timeline by talking to chatbots.

Why learn this artificial intelligence game-changing course on website design and how is this a differentiator?

This website design course can change your life as a web developer or marketer. With no coding experience, you can create amazing looking websites and pave the path for unlimited designs and interchange content and play god using artificial intelligence tech. 

This course will save you a ton of time when it comes to creating websites without using any expensive website design tool and without using complex tools like WordPress etc. You do not even need to outsource websites to other agencies ever again as you can do it yourself now in minutes.

About Bookmark - The 2021 Artificial Intelligence Based Website Design Builder

Bookmark is an AI-powered website builder to help you design amazing websites at lightning speed. Bookmarks AI software AiDA (Artificial Intelligence Design Assistant) - The algorithm behind the website design empowers the non-technical entrepreneur and small business owner with the ability to instantly create an exceptional website that one can be proud of. AiDA eliminates up to 90% of the pain points associated with website design and creation by building a brand new, striking website in less than 30 seconds and then simply walks the user through the process of editing content and design. AiDA's features taught in the course comprises automatically moving the mouse cursor to aid in the website design process and instant change of website design style and fonts in a matter of minutes.

The question is "Are you ready to get into action and embrace the power to leverage artificial intelligence in website design using AiDA?”. 

If yes, plunge into action right away by signing up NOW. All the best to become an Artificial Intelligence Web-Design Creator.

Artificial Intelligence Expert Certification (2021 Edition)

MBA in Artificial Intelligence Digital Marketing: Term 2.1 course that teaches new Artificial Intelligence (AI) Tools

Created by Srinidhi Ranganathan - Digital Marketing Legend - India's Top Udemy Instructor

"]

Students: 117303, Price: $24.99

Students: 117303, Price:  Paid

Welcome to the first course in Term 2 as part of the series "MBA in Artificial Intelligence Digital Marketing".

Artificial Intelligence (AI) seems to be a unique technology of making a machine, a robot fully autonomous. AI is an analysis of how the machine is thinking, studying, determining, and functioning when it is trying to solve problems.

These kinds of problems are present in all fields, the most emerging ones, and even beyond. The aim of Artificial Intelligence is to enhance machine functions relating to human knowledge, such as reasoning, learning, and problems along with the ability to manipulate things. For example, virtual assistants or chatbots offer expert advice. Smart robots or robot advisors will provide instant research or findings in the fields of finance, insurance, law, the media, and journalism, and medical diagnosis and support will be provided by AI software on the health front. Other advantages include increasing productivity dramatically in research and development programs by reducing time to the market, enhancing the transport and supply chain networks and improving governance by improved decision-making processes etc.

Artificial Intelligence technology is aiding the following prominent fields for 2021 and many others:

Website Creation - Artificial Intelligence tools can help to create websites and landing pages in merely minutes.

App Creation - Artificial Intelligence tools can help to automate the whole concept of creating apps.

Natural Language Processing (NLP) − This process is simulating the actual interaction with the computer that understands natural language spoken by humans.

Expert Systems − Learners and users will be provided with guided information and advice on the computer or software.

Vision Systems − Artificial Intelligence (AI) systems in 2021 can understand, explain and describe the computer's visual input to the ultimate core.

Spoken Word or Speech Recognition − Many Artificial Intelligence (AI) based speech recognition systems are capable of listening, voicing and recognizing the user input - i.e. when a person speaks with them. Alexa, Siri and Google's assistant, are examples of this function.

Machine Learning - Artificial Intelligence (AI) can help users to create and experiment with machine learning models and build data science applications in a flash.

Video Creation - Artificial Intelligence (AI) can help to automate video production and cut high costs of hiring resources and team as everything is taken care of in the cloud.

Python and Coding tools - Artificial Intelligence (AI) can help to automate writing lakhs of lines of code in python and even Java or PHP in minutes without the need for a human coder or even someone who will debug the code. Everything is automated in the concept of AI-powered programming.

This mind-blowing exhaustive course focusing on  "Artificial Intelligence Expert Certification" taught by Digital Marketing Legend Srinidhi Ranganathan and Civil MasterMind Saranya Srinidhi will change your perspective on the concept of Artificial Intelligence forever to rely on AI tools of the future for your needs. We will cover 100's of Artificial Intelligence (AI) tools that are highly popular in the following fields that include: Machine Learning, Deep Learning, Digital Marketing, Research, Analytics, Voice-cloning, Mind-Cloning, Video Creation, Virtual Reality (VR) based Artificial Intelligence tools etc. As you learn these AI tools you will understand that Artificial Intelligence has so much evolved in the last 2 to 5 years. You will also see the growth of the emergence of Artificial Intelligence (AI) tools across industries that have exploded and its impact on business and society that is emerging at a quick pace. In this incredible journey, you will also encounter businesses that are pushing the limits of automation, search and social media. As you slowly realize that with the brain of a computer, AI would potentially automate control in such sectors as self-employed vehicles and non-manned drones, you will be left spellbound.

"Artificial Intelligence (AI) will not only reduce costs by automating processes but also skyrocket revenues by helping startups and corporates introduce new product and service categories at the fastest speed ever imagined with limited resources."

But, will jobs die as automation takes over? Will AI will surpass human intelligence in 2021, itself? The answer to these questions is a "No".

The development and eventual growth in AI apps helping in productivity will provide workers with a range of opportunities to improve their skills and concentrate on creative aspects. Stating additional forecasts, disruptive market trends are highly likely to occur in the AI Expansion period (i.e. 2025-2030), the opportunity for employment would require a high degree of personalization, innovation or ability tasks which will still require a person to perform them (even though the AI robotic tools have actually speeded up the process). These occupations or technologies are difficult to imagine at this stage, yet these occupations will rapidly increase as new specializations are required when the demand would kick in. The time is coming soon for a global Artificial Intelligence (AI) revolution to strongly emerge.

Okay. Let's start learning and go on an adventure in Artificial Intelligence. Enrol Now and I will see you inside. Let's rock this world with learning secretive tools. Don't waste any more time.

Special Note: Several Artificial Intelligence (AI) coding tools will be taught in the course. Most of the tools will be free and also paid alternatives will be covered. You can choose the best tools according to your requirements with the correct features during usage.

Artificial Intelligence in Video Creation: 2021 Edition

MBA in Creative Arts, Design and Animation: Level 1 - Part 4

Created by Srinidhi Ranganathan - Digital Marketing Legend - India's Top Udemy Instructor

"]

Students: 77842, Price: $24.99

Students: 77842, Price:  Paid

Welcome to the fourth course as part of the series "MBA in Creative Arts, Design and Animation".

This incredible artificial intelligence video creation course 2021 will cover the tools called Biteable and Lumen5 which are the world's simplest video makers offering hundreds of free animated, live-action, or photo scenes in lots of different styles made by top designers.

I will teach you to easily add your own text, photos, colours, and sound to customize your video and edit it all on a simple drag-and-drop timeline.

Once, you've done that we will go through the process of choosing a soundtrack from Biteable's huge, high-quality music library to match the look and feel of your video. 

Artificial Intelligence and Its Advancement in Video Creation in 2021.

Let's delve down further into the use of AI technology. Artificial Intelligence (AI) is now involved in the creation of smart video and has also been able to influence businesses. Users can now film and edit videos through Artificial Intelligence. It also brings many job opportunities in the field. Due to its ability to sense, reason, act and adapt, AI has suddenly become one of the most important technologies and the most in-demand tool for the video creation market; and also due to the popularity of automation in different business practices. Several companies have invested in keeping video production as their main target in Artificial Intelligence. Examples include AI implementation and deployment through multiple video distribution channels such as Netflix and YouTube. These companies have invested in AI just to make it more exciting and innovative to watch videos. Many aspects of the production and editing process of videos have been handled by artificial intelligence. Its innovation is also a blessing for production teams and video editors. It helps practitioners to concentrate more on creative aspects instead of editing which is perceived by many to be a very dull and repetitive job.

Did you also know this fact?

Most aspects of the production and distribution system are managed by artificial intelligence. It can now record, edit, pick and distribute online videos. Artificial intelligence has allowed automated video editing in 2021. A camera can now operate on its own without human instructions. Ok, so what does this Artificial Intelligence in Video Creation course cover? Let's look into this further. Here is the ultimate question.

Why learn this mind-blowing course and how this can be a differentiator when it comes to AI video creation?

With Biteable, you can convert any plain infographic into fun slides that will not only explain and pass the information but also make the content more understandable. This course can change your life as a video creator.

Biteable is the god of video creation to aid you to create videos in minutes. Lumen5 whereas is an Artificial Intelligence Video Creation Tool that allows you to turn your blog posts, articles into engaging videos to post on social media platforms. 

This course will save you tons of time when it comes to creating videos without using any expensive video creation software. The output videos generated will be so powerful that it would create a huge impact on your business. This is highly beneficial to any business and you will realize this inside the course. If you learn how to work on a PowerPoint presentation, you can work on Biteable and Lumen5. An 8th grader can do it.

The question is "Are you ready to get into the video-making action, right now?"

2021 seems to be a great and amazing year to take your video creation efforts to great heights of success.

Artificial Intelligence In Digital Marketing

Learn Highly Futuristic Digital Marketing Technologies with Artificial Intelligence

Created by Liaqat Eagle - I Am Web designer , Android Developer and SMO, SEO Expert

"]

Students: 55796, Price: $89.99

Students: 55796, Price:  Paid

Being smart in business means knowing what’s just around the corner. It means thinking ahead and preparing for inevitable changes that will impact the way business is conducted.

This is what allows a business to be resilient and to thrive in a changing environment.

This video course will help you to prepare, and explain a number of concepts:

  • AI vs Machine Learning

  • How to conduct SEO now that Google is an “AI first” company

  • Chat bots

  • Programmatic advertising

  • Big data

  • Rank Brain

  • Digital assistants

  • Data science

  • SQL

  • Latent Semantic Indexing

  • The future of internet marketing

In this course, you will gain a crystal ball with which to gaze into the future of internet marketing, and to ensure that you are ready for all those changes when they come.

Topics covered:

  • What Is AI And Machine Learning?

  • Google As An AI-First Company

  • Preparing For Semantic Search

  • Big Data

  • Computer Version

  • Advertising

  • Email Marketing

  • Chat bots

  • Developing Your AI Skills – Using SQL

  • How To Future Proof Your Marketing

Advanced Artificial Intelligence in Digital Marketing Course

MBA in Artificial Intelligence Digital Marketing: Term 1.2 course on Advanced Artificial Intelligence Digital Marketing

Created by Srinidhi Ranganathan - Digital Marketing Legend - India's Top Udemy Instructor

"]

Students: 50560, Price: $24.99

Students: 50560, Price:  Paid

Welcome to the second course in Term 1 as part of the series "MBA in Artificial Intelligence Digital Marketing".

Digital Marketing is vital in today's scenario of any company that is transparent in its corporate scale and scope. Having said that, Artificial Intelligence (AI) in Digital Marketing is the big revolutionary thing that is being talked about by each one of us today - thanks to the drastic emerging AI tools that are changing the brandscape, altogether. Companies are leveraging innovative ways to market around the clock using Artificial Intelligence (AI) tools and technologies. Recently, companies are also making use of social media and video-making tools powered by Artificial Intelligence (AI) to speed up social media content creation and video production to dominate the industry which they are particularly catering to. This reasoning shift from traditional digital marketing to Artificial Intelligence (AI) in Digital Marketing has filled the gap - giving rise to high chances of crossover between company and consumers.

There are numerous cloud-based and offline Digital Marketing tools, you can leverage based on the needs. Your daily Digital Marketing works can be managed by these AI tools and this is an incredibly true fact.

This game-changing course in 2021 focusing on "Advanced Artificial Intelligence in Digital Marketing Course" created by Marketing Legend "Srinidhi Ranganathan" and MasterMind "Saranya Srinidhi" takes a step further to cover Artificial Intelligence (AI) tools in website creation, app making, affiliate marketing, video creation, LinkedIn networking automation and also invites you to explore the future of technology. We will also look at creating a resume using a powerful Artificial Intelligence (AI) tool.

Ok, having given all this interesting information that focuses on "Artificial Intelligence in Digital Marketing", the question is "Are you ready to start learning new-age technologies in digital marketing, this year?"

If yes, plunge into action right away by signing up NOW for this course. Your successful Artificial Intelligence (AI) in your digital marketing career is waiting.

There is no time to waste. The course will be educative, informative, and practical at the same time.

Enrol now, and let's start booming. There are interesting, engaging, and new things to experience here in this course.

This course has the potential to change the digital marketing world, altogether.

Lights. Camera. Action. Let us do the magic.

Get ready for a new mind-blowing course by Digital Marketing Legend "Srinidhi Ranganathan", and Mastermind "Saranya Srinidhi".

Artificial Intelligence: Reinforcement Learning in Python

Complete guide to Reinforcement Learning, with Stock Trading and Online Advertising Applications

Created by Lazy Programmer Team - Artificial Intelligence and Machine Learning Engineer

"]

Students: 41189, Price: $199.99

Students: 41189, Price:  Paid

When people talk about artificial intelligence, they usually don’t mean supervised and unsupervised machine learning.

These tasks are pretty trivial compared to what we think of AIs doing - playing chess and Go, driving cars, and beating video games at a superhuman level.

Reinforcement learning has recently become popular for doing all of that and more.

Much like deep learning, a lot of the theory was discovered in the 70s and 80s but it hasn’t been until recently that we’ve been able to observe first hand the amazing results that are possible.

In 2016 we saw Google’s AlphaGo beat the world Champion in Go.

We saw AIs playing video games like Doom and Super Mario.

Self-driving cars have started driving on real roads with other drivers and even carrying passengers (Uber), all without human assistance.

If that sounds amazing, brace yourself for the future because the law of accelerating returns dictates that this progress is only going to continue to increase exponentially.

Learning about supervised and unsupervised machine learning is no small feat. To date I have over TWENTY FIVE (25!) courses just on those topics alone.

And yet reinforcement learning opens up a whole new world. As you’ll learn in this course, the reinforcement learning paradigm is very from both supervised and unsupervised learning.

It’s led to new and amazing insights both in behavioral psychology and neuroscience. As you’ll learn in this course, there are many analogous processes when it comes to teaching an agent and teaching an animal or even a human. It’s the closest thing we have so far to a true artificial general intelligence.  What’s covered in this course?

  • The multi-armed bandit problem and the explore-exploit dilemma

  • Ways to calculate means and moving averages and their relationship to stochastic gradient descent

  • Markov Decision Processes (MDPs)

  • Dynamic Programming

  • Monte Carlo

  • Temporal Difference (TD) Learning (Q-Learning and SARSA)

  • Approximation Methods (i.e. how to plug in a deep neural network or other differentiable model into your RL algorithm)

  • How to use OpenAI Gym, with zero code changes

  • Project: Apply Q-Learning to build a stock trading bot

If you’re ready to take on a brand new challenge, and learn about AI techniques that you’ve never seen before in traditional supervised machine learning, unsupervised machine learning, or even deep learning, then this course is for you.

See you in class!

"If you can't implement it, you don't understand it"

  • Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".

  • My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratch

  • Other courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?

  • After doing the same thing with 10 datasets, you realize you didn't learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times...

Suggested Prerequisites:

  • Calculus

  • Probability

  • Object-oriented programming

  • Python coding: if/else, loops, lists, dicts, sets

  • Numpy coding: matrix and vector operations

  • Linear regression

  • Gradient descent

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

  • Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)

Artificial Intelligence In Python: Build 6 AI Projects

Learn Artificial Intelligence with Python. Create Advanced Artificial Intelligence (AI) Applications with Python

Created by Data Is Good Academy - An Google, Facebook, Kaggle Grandmasters team

"]

Students: 36311, Price: $19.99

Students: 36311, Price:  Paid

Are you ready to master Artificial Intelligence skills?

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions.

It is the simulation of natural intelligence in machines that are programmed to learn and mimic the actions of humans. These machines are able to learn with experience and perform human-like tasks. As technologies such as AI continue to grow,

they will have a great impact on our quality of life.

Artificial intelligence (AI) is one of the top tech fields to be in right now!

Financial institutions, legal institutions, media companies, and insurance companies are all figuring out ways to use artificial intelligence (ai) to their advantage. From fraud detection to writing news stories with natural language processing(NLP) and reviewing law briefs, AI’s reach is extensive.

If you want to build super-powerful applications in artificial intelligence(ai).

Then, you are at the right place.

This course will provide you with in-depth knowledge on a very hot topic i.e., Artificial Intelligence(AI).

The purpose of this course is to provide you with knowledge of key aspects of modern AI without any intimidating mathematics and in a practical, easy, and fun way. The course provides students with practical hands-on experience using real-world datasets.

This course will cover the following topics:-

1. Natural Language Processing (NLP).

2. Artificial Neural Network (ANN).

3. Convolutional Neural Network (CNN).

4. Recurrent Neural Network. (RCN)

5. Machine Learning (ML).

6. Deep Learning (DL).

This course will take you through the basics to an advanced level in all the mentioned four topics.

After taking this course, you will be confident enough to work independently on any projects on these topics.

There are lots and lots of exercises for you to practice In this Python Data Science Course and also a  5 Bonus Data Science Project "Sentiment Analysis", "Drug Prescription", "Detecting Pneumonia from X-rays", "Stock Market Prediction", "Fruits Recognition" and "Face emotion Recognition".

In this Sentiment Analysis project, you will learn how to Extract and Scrap Data from Social Media Websites and Extract out Beneficial Information from these Data for Driving Huge Business Insights.

In this Drug Prescription project, you will learn how to Deal with Data having Textual Features, you will also learn NLP Techniques to transform and Process the Data to find out Important Insights.

In this Detecting Pneumonia from X-rays project, you will learn how to solve Image Classification Tasks using Deep Neural Networks such as ResNet which is a High Level CNN Architectures.

In this Stock Market Prediction project, you will learn to analyze and the Stock Market Prices using Time Series Forecasting, Advanced Deep Learning Models and different Statistical features.

In this Fruits Recognition project, you will learn how to solve a complicated Image Classification Task with Multiple Classes using various Deep Learning Architectures and Compare the Result.

In this Face Expression Recognizer project, you will learn to use Computer Vision Techniques to detect Human Emotions such as Angry, Sad, Happy, Disgust, Fear etc. to build a Facial Emotion Detector.

You will have access to all the resources used in this course.

The Beginner’s Guide to Artificial Intelligence in Unity.

A practical guide to programming non-player characters for games.

Created by Penny de Byl - International Award Winning Professor & Best Selling Author

"]

Students: 34675, Price: $19.99

Students: 34675, Price:  Paid

Do your non-player characters lack drive and ambition?  Are they slow, stupid and constantly banging their heads against the wall? Then this course is for you.  Join Penny as she explains, demonstrates and assists you in creating your very own NPCs in Unity with C#. All you need is a sound knowledge of Unity, C# and the ability to add two numbers together.

In this course, Penny reveals the most popular AI techniques used for creating believable character behaviour in games using her internationally acclaimed teaching style and knowledge from over 25 years working with games, graphics and having written two award winning books on games AI. Throughout, you will follow along with hands-on workshops designed to teach you about the fundamental AI techniques used in today's games.  You'll join in as NPCs are programmed to chase, patrol, shoot, race, crowd and much more.

Learn how to program and work with:

  • vectors

  • waypoints

  • navmeshes

  • the A* algorithm

  • crowds

  • flocks

  • animated characters

  • vehicles

Contents and Overview

The course begins with a detailed examination of vector mathematics that sits at the very heart of programming the movement of NPCs. Following this, systems of waypoints will be used to move characters around in an environment before examining the Unity waypoint system for car racing with AI controlled cars.  This leads into an investigation of graph theory and the A* algorithm before we apply these principles to developing navmeshes and developing NPCs who can find their way around a game environment.  Before an aquarium is programmed complete with autonomous schooling fish, crowds of people will be examined from the recreation of sidewalk traffic, to groups of people fleeing from danger. Having examined the differing ways to move NPCs around in a game environment, their thinking abilities will be discussed with full explanations and more hands-on workshops using finite state machines and behaviour trees.

The follow-along workshops included in the course come with starter Unity asset files and projects complete with solutions.  Throughout, there are also quizzes and challenge exercises to reinforce your learning and guide you to express your newfound knowledge.

At the completion of this course you will have gained a broad understanding of what AI is in games, how it works and how you can use it in your own projects.  It will equip you with a toolset to examine any of the techniques presented in more depth to take your game environments to the next level.

What students are saying about this course:

  • This has been my favourite Udemy-Unity course so far. It took me from literally 0% knowledge of how game AI is achieved, and took me to a whole new level. Waypoints, pathfinding, state machines, etc etc etc are all covered in-depth and will reveal the magic (spoiler alert: it isn't magic) behind making your computer characters seem like they really have a mind of their own.

  • Oh My God. I love her way of teaching things. I haven’t finished this course yet. But all i can say is that it is another brilliant course from her. Artificial intelligence by itself is a tricky thing to do. And before starting this course i never thought that i will understand anything in it. But i was wrong. With her style of teaching, you will learn how to move your characters in an ”intelligent“ way. This course is perfectly sliced and the pace is wonderful.

Advanced AI: Deep Reinforcement Learning in Python

The Complete Guide to Mastering Artificial Intelligence using Deep Learning and Neural Networks

Created by Lazy Programmer Team - Artificial Intelligence and Machine Learning Engineer

"]

Students: 33375, Price: $29.99

Students: 33375, Price:  Paid

This course is all about the application of deep learning and neural networks to reinforcement learning.

If you’ve taken my first reinforcement learning class, then you know that reinforcement learning is on the bleeding edge of what we can do with AI.

Specifically, the combination of deep learning with reinforcement learning has led to AlphaGo beating a world champion in the strategy game Go, it has led to self-driving cars, and it has led to machines that can play video games at a superhuman level.

Reinforcement learning has been around since the 70s but none of this has been possible until now.

The world is changing at a very fast pace. The state of California is changing their regulations so that self-driving car companies can test their cars without a human in the car to supervise.

We’ve seen that reinforcement learning is an entirely different kind of machine learning than supervised and unsupervised learning.

Supervised and unsupervised machine learning algorithms are for analyzing and making predictions about data, whereas reinforcement learning is about training an agent to interact with an environment and maximize its reward.

Unlike supervised and unsupervised learning algorithms, reinforcement learning agents have an impetus - they want to reach a goal.

This is such a fascinating perspective, it can even make supervised / unsupervised machine learning and "data science" seem boring in hindsight. Why train a neural network to learn about the data in a database, when you can train a neural network to interact with the real-world?

While deep reinforcement learning and AI has a lot of potential, it also carries with it huge risk.

Bill Gates and Elon Musk have made public statements about some of the risks that AI poses to economic stability and even our existence.

As we learned in my first reinforcement learning course, one of the main principles of training reinforcement learning agents is that there are unintended consequences when training an AI.

AIs don’t think like humans, and so they come up with novel and non-intuitive solutions to reach their goals, often in ways that surprise domain experts - humans who are the best at what they do.

OpenAI is a non-profit founded by Elon Musk, Sam Altman (Y Combinator), and others, in order to ensure that AI progresses in a way that is beneficial, rather than harmful.

Part of the motivation behind OpenAI is the existential risk that AI poses to humans. They believe that open collaboration is one of the keys to mitigating that risk.

One of the great things about OpenAI is that they have a platform called the OpenAI Gym, which we’ll be making heavy use of in this course.

It allows anyone, anywhere in the world, to train their reinforcement learning agents in standard environments.

In this course, we’ll build upon what we did in the last course by working with more complex environments, specifically, those provided by the OpenAI Gym:

  • CartPole

  • Mountain Car

  • Atari games

To train effective learning agents, we’ll need new techniques.

We’ll extend our knowledge of temporal difference learning by looking at the TD Lambda algorithm, we’ll look at a special type of neural network called the RBF network, we’ll look at the policy gradient method, and we’ll end the course by looking at Deep Q-Learning (DQN) and A3C (Asynchronous Advantage Actor-Critic).

Thanks for reading, and I’ll see you in class!

"If you can't implement it, you don't understand it"

  • Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".

  • My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratch

  • Other courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?

  • After doing the same thing with 10 datasets, you realize you didn't learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times...

Suggested Prerequisites:

  • College-level math is helpful (calculus, probability)

  • Object-oriented programming

  • Python coding: if/else, loops, lists, dicts, sets

  • Numpy coding: matrix and vector operations

  • Linear regression

  • Gradient descent

  • Know how to build ANNs and CNNs in Theano or TensorFlow

  • Markov Decision Proccesses (MDPs)

  • Know how to implement Dynamic Programming, Monte Carlo, and Temporal Difference Learning to solve MDPs

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

  • Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)

Tensorflow 2.0: Deep Learning and Artificial Intelligence

Neural Networks for Computer Vision, Time Series Forecasting, NLP, GANs, Reinforcement Learning, and More!

Created by Lazy Programmer Inc. - Artificial intelligence and machine learning engineer

"]

Students: 31072, Price: $129.99

Students: 31072, Price:  Paid

Welcome to Tensorflow 2.0!

What an exciting time. It's been nearly 4 years since Tensorflow was released, and the library has evolved to its official second version.

Tensorflow is Google's library for deep learning and artificial intelligence.

Deep Learning has been responsible for some amazing achievements recently, such as:

  • Generating beautiful, photo-realistic images of people and things that never existed (GANs)

  • Beating world champions in the strategy game Go, and complex video games like CS:GO and Dota 2 (Deep Reinforcement Learning)

  • Self-driving cars (Computer Vision)

  • Speech recognition (e.g. Siri) and machine translation (Natural Language Processing)

  • Even creating videos of people doing and saying things they never did (DeepFakes - a potentially nefarious application of deep learning)

Tensorflow is the world's most popular library for deep learning, and it's built by Google, whose parent Alphabet recently became the most cash-rich company in the world (just a few days before I wrote this). It is the library of choice for many companies doing AI and machine learning.

In other words, if you want to do deep learning, you gotta know Tensorflow.

This course is for beginner-level students all the way up to expert-level students. How can this be?

If you've just taken my free Numpy prerequisite, then you know everything you need to jump right in. We will start with some very basic machine learning models and advance to state of the art concepts.

Along the way, you will learn about all of the major deep learning architectures, such as Deep Neural Networks, Convolutional Neural Networks (image processing), and Recurrent Neural Networks (sequence data).

Current projects include:

  • Natural Language Processing (NLP)

  • Recommender Systems

  • Transfer Learning for Computer Vision

  • Generative Adversarial Networks (GANs)

  • Deep Reinforcement Learning Stock Trading Bot

Even if you've taken all of my previous courses already, you will still learn about how to convert your previous code so that it uses Tensorflow 2.0, and there are all-new and never-before-seen projects in this course such as time series forecasting and how to do stock predictions.

This course is designed for students who want to learn fast, but there are also "in-depth" sections in case you want to dig a little deeper into the theory (like what is a loss function, and what are the different types of gradient descent approaches).

Advanced Tensorflow topics include:

  • Deploying a model with Tensorflow Serving (Tensorflow in the cloud)

  • Deploying a model with Tensorflow Lite (mobile and embedded applications)

  • Distributed Tensorflow training with Distribution Strategies

  • Writing your own custom Tensorflow model

  • Converting Tensorflow 1.x code to Tensorflow 2.0

  • Constants, Variables, and Tensors

  • Eager execution

  • Gradient tape

Instructor's Note: This course focuses on breadth rather than depth, with less theory in favor of building more cool stuff. If you are looking for a more theory-dense course, this is not it. Generally, for each of these topics (recommender systems, natural language processing, reinforcement learning, computer vision, GANs, etc.) I already have courses singularly focused on those topics.

Thanks for reading, and I’ll see you in class!

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

  • Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)

Modern Artificial Intelligence Masterclass: Build 6 Projects

Harness the power of AI to solve practical, real-world problems in Finance, Tech, Art and Healthcare

Created by Dr. Ryan Ahmed, Ph.D., MBA - Professor & Best-selling Udemy Instructor, 200K+ students

"]

Students: 27373, Price: $99.99

Students: 27373, Price:  Paid

# Course Update June 2021: Added a study on Explainable AI with Zero Coding

Artificial Intelligence (AI) revolution is here!

Artificial Intelligence market worldwide is projected to grow by US$284.6 Billion driven by a compounded growth of 43. 9%. Deep Learning, one of the segments analyzed and sized in this study, displays the potential to grow at over 42. 5%.” (Source: globenewswire).

AI is the science that empowers computers to mimic human intelligence such as decision making, reasoning, text processing, and visual perception. AI is a broader general field that entails several sub-fields such as machine learning, robotics, and computer vision.

For companies to become competitive and skyrocket their growth, they need to leverage AI power to improve processes, reduce cost and increase revenue. AI is broadly implemented in many sectors nowadays and has been transforming every industry from banking to healthcare, transportation and technology.

The demand for AI talent has exponentially increased in recent years and it’s no longer limited to Silicon Valley! According to Forbes, AI Skills are among the most in-demand for 2020.

The purpose of this course is to provide you with knowledge of key aspects of modern Artificial Intelligence applications in a practical, easy and fun way. The course provides students with practical hands-on experience using real-world datasets. The course covers many new topics and applications such as Emotion AI, Explainable AI, Creative AI, and applications of AI in Healthcare, Business, and Finance.

One key unique feature of this course is that we will be training and deploying models using Tensorflow 2.0 and AWS SageMaker. In addition, we will cover various elements of the AI/ML workflow covering model building, training, hyper-parameters tuning, and deployment. Furthermore, the course has been carefully designed to cover key aspects of AI such as Machine learning, deep learning, and computer vision.

Here’s a summary of the projects that we will be covering:

· Project #1 (Emotion AI): Emotion Classification and Key Facial Points Detection Using AI

· Project #2 (AI in HealthCare): Brain Tumor Detection and Localization Using AI

· Project #3 (AI in Business/Marketing): Mall Customer Segmentation Using Autoencoders and Unsupervised Machine Learning Algorithms

· Project #4: (AI in Business/Finance): Credit Card Default Prediction Using AWS SageMaker's XG-Boost Algorithm (AutoPilot)

· Project #5 (Creative AI): Artwork Generation by AI

· Project #6 (Explainable AI): Uncover the Blackbox nature of AI

Who this course is for:

The course is targeted towards AI practitioners, aspiring data scientists, Tech enthusiasts, and consultants wanting to gain a fundamental understanding of data science and solve real world problems. Here’s a list of who is this course for:

· Seasoned consultants wanting to transform industries by leveraging AI.

· AI Practitioners wanting to advance their careers and build their portfolio.

· Visionary business owners who want to harness the power of AI to maximize revenue, reduce costs and optimize their business.

· Tech enthusiasts who are passionate about AI and want to gain real-world practical experience.

Course Prerequisites:

Basic knowledge of programming is recommended. However, these topics will be extensively covered during early course lectures; therefore, the course has no prerequisites, and is open to anyone with basic programming knowledge. Students who enroll in this course will master data science fundamentals and directly apply these skills to solve real world challenging business problems.

Cutting-Edge AI: Deep Reinforcement Learning in Python

Apply deep learning to artificial intelligence and reinforcement learning using evolution strategies, A2C, and DDPG

Created by Lazy Programmer Inc. - Artificial intelligence and machine learning engineer

"]

Students: 22621, Price: $109.99

Students: 22621, Price:  Paid

Welcome to Cutting-Edge AI!

This is technically Deep Learning in Python part 11 of my deep learning series, and my 3rd reinforcement learning course.

Deep Reinforcement Learning is actually the combination of 2 topics: Reinforcement Learning and Deep Learning (Neural Networks).

While both of these have been around for quite some time, it’s only been recently that Deep Learning has really taken off, and along with it, Reinforcement Learning.

The maturation of deep learning has propelled advances in reinforcement learning, which has been around since the 1980s, although some aspects of it, such as the Bellman equation, have been for much longer.

Recently, these advances have allowed us to showcase just how powerful reinforcement learning can be.

We’ve seen how AlphaZero can master the game of Go using only self-play.

This is just a few years after the original AlphaGo already beat a world champion in Go.

We’ve seen real-world robots learn how to walk, and even recover after being kicked over, despite only being trained using simulation.

Simulation is nice because it doesn’t require actual hardware, which is expensive. If your agent falls down, no real damage is done.

We’ve seen real-world robots learn hand dexterity, which is no small feat.

Walking is one thing, but that involves coarse movements. Hand dexterity is complex - you have many degrees of freedom and many of the forces involved are extremely subtle.

Imagine using your foot to do something you usually do with your hand, and you immediately understand why this would be difficult.

Last but not least - video games.

Even just considering the past few months, we’ve seen some amazing developments. AIs are now beating professional players in CS:GO and Dota 2.

So what makes this course different from the first two?

Now that we know deep learning works with reinforcement learning, the question becomes: how do we improve these algorithms?

This course is going to show you a few different ways: including the powerful A2C (Advantage Actor-Critic) algorithm, the DDPG (Deep Deterministic Policy Gradient) algorithm, and evolution strategies.

Evolution strategies is a new and fresh take on reinforcement learning, that kind of throws away all the old theory in favor of a more "black box" approach, inspired by biological evolution.

What’s also great about this new course is the variety of environments we get to look at.

First, we’re going to look at the classic Atari environments. These are important because they show that reinforcement learning agents can learn based on images alone.

Second, we’re going to look at MuJoCo, which is a physics simulator. This is the first step to building a robot that can navigate the real-world and understand physics - we first have to show it can work with simulated physics.

Finally, we’re going to look at Flappy Bird, everyone’s favorite mobile game just a few years ago.

Thanks for reading, and I’ll see you in class!

"If you can't implement it, you don't understand it"

  • Or as the great physicist Richard Feynman said: "What I cannot create, I do not understand".

  • My courses are the ONLY courses where you will learn how to implement machine learning algorithms from scratch

  • Other courses will teach you how to plug in your data into a library, but do you really need help with 3 lines of code?

  • After doing the same thing with 10 datasets, you realize you didn't learn 10 things. You learned 1 thing, and just repeated the same 3 lines of code 10 times...

Suggested prerequisites:

  • Calculus

  • Probability

  • Object-oriented programming

  • Python coding: if/else, loops, lists, dicts, sets

  • Numpy coding: matrix and vector operations

  • Linear regression

  • Gradient descent

  • Know how to build a convolutional neural network (CNN) in TensorFlow

  • Markov Decision Proccesses (MDPs)

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

  • Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)

Artificial Intelligence for Business

Solve Real World Business Problems with AI Solutions

Created by Hadelin de Ponteves - AI Entrepreneur

"]

Students: 19049, Price: $109.99

Students: 19049, Price:  Paid

Structure of the course:

Part 1 - Optimizing Business Processes
Case Study: Optimizing the Flows in an E-Commerce Warehouse
AI Solution: Q-Learning

Part 2 - Minimizing Costs
Case Study: Minimizing the Costs in Energy Consumption of a Data Center
AI Solution: Deep Q-Learning

Part 3 - Maximizing Revenues
Case Study: Maximizing Revenue of an Online Retail Business
AI Solution: Thompson Sampling

Real World Business Applications:

With Artificial Intelligence, you can do three main things for any business:

  1. Optimize Business Processes

  2. Minimize Costs

  3. Maximize Revenues

We will show you exactly how to succeed these applications, through Real World Business case studies. And for each of these applications we will build a separate AI to solve the challenge.

In Part 1 - Optimizing Processes, we will build an AI that will optimize the flows in an E-Commerce warehouse.

In Part 2 - Minimizing Costs, we will build a more advanced AI that will minimize the costs in energy consumption of a data center by more than 50%! Just as Google did last year thanks to DeepMind.

In Part 3 - Maximizing Revenues, we will build a different AI that will maximize revenue of an Online Retail Business, making it earn more than 1 Billion dollars in revenue!

But that's not all, this time, and for the first time, we’ve prepared a huge innovation for you. With this course, you will get an incredible extra product, highly valuable for your career:

"a 100-pages book covering everything about Artificial Intelligence for Business!".

The Book:

This book includes:

  • 100 pages of crystal clear explanations, written in beautiful and clean latex

  • All the AI intuition and theory, including the math explained in detail

  • The three Case Studies of the course, and their solutions

  • Three different AI models, including Q-Learning, Deep Q-Learning, and Thompson Sampling

  • Code Templates

  • Homework and their solutions for you to practice

  • Plus, lots of extra techniques and tips like saving and loading models, early stopping, and much much more.

Conclusion:

If you want to land a top-paying job or create your very own successful business in AI, then this is the course you need.

Take your AI career to new heights today with Artificial Intelligence for Business -- the ultimate AI course to propel your career further.

Artificial Intelligence Masterclass

Enter the new era of Hybrid AI Models optimized by Deep NeuroEvolution, with a complete toolkit of ML, DL & AI models

Created by Hadelin de Ponteves - AI Entrepreneur

"]

Students: 10792, Price: $109.99

Students: 10792, Price:  Paid

Today, we are bringing you the king of our AI courses...:

The Artificial Intelligence MASTERCLASS

Are you keen on Artificial Intelligence? Do want to learn to build the most powerful AI model developed so far and even play against it? Sounds tempting right...

Then Artificial Intelligence Masterclass course is the right choice for you. This ultimate AI toolbox is all you need to nail it down with ease. You will get 10 hours step by step guide and the full roadmap which will help you build your own Hybrid AI Model from scratch.  

In this course, we will teach you how to develop the most powerful Artificial intelligence model based on the most robust Hybrid Intelligent System. So far this model proves to be the best state of the art AI ever created beating its predecessors at all the AI competitions with incredibly high scores.

This Hybrid Model is aptly named the Full World Model, and it combines all the state of the art models of the different AI branches, including Deep Learning, Deep Reinforcement Learning, Policy Gradient, and even, Deep NeuroEvolution.

By enrolling in this course you will have the opportunity to learn how to combine the below models in order to achieve best performing artificial intelligence system:

  • Fully-Connected Neural Networks

  • Convolutional Neural Networks

  • Recurrent Neural Networks

  • Variational AutoEncoders

  • Mixed Density Networks

  • Genetic Algorithms

  • Evolution Strategies

  • Covariance Matrix Adaptation Evolution Strategy (CMA-ES)

  • Parameter-Exploring Policy Gradients

  • Plus many others

Therefore, you are not getting just another simple artificial intelligence course but all in one package combining a course and a master toolkit, of the most powerful AI models. You will be able to download this toolkit and use it to build hybrid intelligent systems. Hybrid Models are becoming the winners in the AI race, so you must learn how to handle them already.

In addition to all this, we will also give you the full implementations in the two AI frameworks: TensorFlow and Keras. So anytime you want to build an AI for a specific application, you can just grab those model you need in the toolkit, and reuse them for different projects!

Don’t wait to join us on this EPIC journey in mastering the future of the AI - the hybrid AI Models.

Artificial Intelligence 2018: Build the Most Powerful AI

Learn, build and implement the most powerful AI model at home. Compete with multi-billion dollars companies using ARS.

Created by Hadelin de Ponteves - AI Entrepreneur

"]

Students: 8743, Price: $109.99

Students: 8743, Price:  Paid

Two months ago we discovered that a very new kind of AI was invented.

The kind of AI which is based on a genius idea and that you can build from scratch and without the need for any framework.

We checked that out, we built it, and... the results are absolutely insane!

This game-changing AI called Augmented Random Search, ARS for short.

And in a very simple implementation, it is able to do an exact same thing that Google Deep Mind did in their accomplishment last year  - which is to train an AI to walk and run across a field.

However, ARS is 100x times faster and 100x times more powerful.

  • Be prepared for the most significant tech challenges of the 21st century
  • No need for sophisticated algorithms and frameworks
  • What Facebook or Google spent on millions or even more - you can literally do at home!
  • You will be able to compete with multi-billion dollars companies
  • Change the world on your own within months or even weeks
  • Build the most powerful AI that anyone has ever built

Artificial Intelligence I: Meta-Heuristics and Games in Java

Graph Algorithms, Genetic Algorithms, Simulated Annealing, Swarm Intelligence, Minimax, Heuristics and Meta-Heuristics

Created by Holczer Balazs - Software Engineer

"]

Students: 6663, Price: $109.99

Students: 6663, Price:  Paid

This course is about the fundamental concepts of artificial intelligence. This topic is getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns which can help detecting cancer for example. We may construct algorithms that can have a very  good guess about stock price movement in the market.

- PATHFINDING ALGORITHMS -

Section 1 - Breadth-First Search (BFS)

  • what is breadth-first search algorithm

  • why to use graph algorithms in AI

Section 2 - Depth-First Search (DFS)

  • what is depth-first search algorithm

  • implementation with iteration and with recursion

  • depth-first search stack memory visualization

  • maze escape application

Section 3 - Iterative Deepening Depth-First Search (IDDFS)

  • what is iterative deepening depth-first search algorithm

Section 4 - A* Search Algorithm

  • what is A* search algorithm

  • what is the difference between Dijkstra's algorithm and A* search

  • what is a heuristic

  • Manhattan distance and Euclidean distance

- OPTIMIZATION -

Section 5 - Optimization Approaches

  • basic optimization algorithms

  • brute-force search

  • hill climbing algorithm

- META-HEURISTICS -

Section 6 - Tabu Search

  • what is the tabu search algorithm

  • tabu tenure and aspiration criteria

Section 7 - Simulated Annealing

  • what is simulated annealing

  • how to find the extremum of functions

  • how to solve combinatorial optimization problems

  • travelling salesman problem (TSP)

Section 8 - Genetic Algorithms

  • what are genetic algorithms

  • artificial evolution and natural selection

  • crossover and mutation

  • solving the knapsack problem

Section 9 - Particle Swarm Optimization (PSO)

  • what is swarm intelligence

  • what is the Particle Swarm Optimization algorithm

- GAMES AND GAME TREES -

Section 10 - Game Trees

  • what are game trees

  • how to construct game trees

Section 11 - Minimax Algorithm and Game Engines

  • what is the minimax algorithm

  • what is the problem with game trees?

  • using the alpha-beta pruning approach

  • chess problem

Section 12 - Tic Tac Toe with Minimax

  • Tic Tac Toe game and its implementation

  • using minimax algorithm

In the first chapter we are going to talk about the basic graph algorithms. Several advanced algorithms can be solved with the help of graphs, so as far as I am concerned these algorithms are the first steps.

Second chapter is about local search: finding minimum and maximum or global optimum in the main. These searches are used frequently when we use regression for example and want to find the parameters for the fit. We will consider basic concepts as well as the more advanced algorithms: heuristics and meta-heuristics.

The last topic will be about minimax algorithm and how to use this technique in games such as chess or tic-tac-toe, how to build and construct a game tree, how to analyze these kinds of tree like structures and so on. We will implement the tic-tac-toe game together in the end.

Thanks for joining the course, let's get started!

Artificial Intelligence & Machine Learning for Business

The Ultimate Artificial Intelligence & Machine Learning course for CxOs, Managers, Team Leaders and Entrepreneurs

Created by Analytics Vidhya - Data Science Community

"]

Students: 5688, Price: $94.99

Students: 5688, Price:  Paid

Are you prepared for the inevitable AI revolution? How can you leverage it in your current role as a business leader (whether that's a manager, team leader or a CxO)? Analytics Vidhya’s ‘Artificial Intelligence (AI) & Machine Learning (ML) for Business’ course, curated and delivered by experienced instructors, will help you understand the answers to these pressing questions.

Artificial Intelligence has become the centrepiece of strategic decision making for organizations. It is disrupting the way industries function - from sales and marketing to finance and HR, companies are betting on AI to give them a competitive edge.

AI for Business Leaders is a thoughtfully created course designed specifically for business people and does not require any programming.

Through this course you will learn about the current state of AI, how it's disrupting businesses globally and in diverse fields, how it might impact your current role and what you can do about it. This course also dives into the various building blocks of AI and why it's necessary for you to have a high-level overview of these topics in today's data-driven world.

We will also provide you with multiple practical case studies towards the end of the course that will test your understanding and add context to all that you've studied.

By the time you finish the course, you will be ready to apply your newly-acquired knowledge in your current organization. You will be able to make informed strategic decisions for yourself and your business.

Artificial Intelligence II – Hands-On Neural Networks (Java)

Hopfield networks, neural networks, gradient descent and backpropagation algorithms explained step by step

Created by Holczer Balazs - Software Engineer

"]

Students: 4768, Price: $89.99

Students: 4768, Price:  Paid

This course is about artificial neural networks. Artificial intelligence and machine learning are getting more and more popular nowadays. In the beginning, other techniques such as Support Vector Machines outperformed neural networks, but in the 21th century neural networks again gain popularity. In spite of the slow training procedure, neural networks can be very powerful. Applications ranges from regression problems to optical character recognition and face detection.

Section 1:

  • what are neural networks

  • modeling the human brain

  • the big picture

Section 2:

  • Hopfield neural networks

  • how to construct an autoassociative memory with neural networks

Section 3:

  • what is back-propagation

  • feedforward neural networks

  • optimizing the cost function

  • error calculation

  • backpropagation and gradient descent

Section 4:

  • the single perceptron model

  • solving linear classification problems

  • logical operators (AND and XOR operation)

Section 5:

  • applications of neural networks

  • clustering

  • classification (Iris-dataset)

  • optical character recognition (OCR)

  • smile-detector application from scratch

In the first part of the course you will learn about the theoretical background of neural networks, later you will learn how to implement them.

If you are keen on learning methods, let's get started!

PyTorch: Deep Learning and Artificial Intelligence

Neural Networks for Computer Vision, Time Series Forecasting, NLP, GANs, Reinforcement Learning, and More!

Created by Lazy Programmer Team - Artificial Intelligence and Machine Learning Engineer

"]

Students: 4312, Price: $199.99

Students: 4312, Price:  Paid

Welcome to PyTorch: Deep Learning and Artificial Intelligence!

Although Google's Deep Learning library Tensorflow has gained massive popularity over the past few years, PyTorch has been the library of choice for professionals and researchers around the globe for deep learning and artificial intelligence.

Is it possible that Tensorflow is popular only because Google is popular and used effective marketing?

Why did Tensorflow change so significantly between version 1 and version 2? Was there something deeply flawed with it, and are there still potential problems?

It is less well-known that PyTorch is backed by another Internet giant, Facebook (specifically, the Facebook AI Research Lab - FAIR). So if you want a popular deep learning library backed by billion dollar companies and lots of community support, you can't go wrong with PyTorch. And maybe it's a bonus that the library won't completely ruin all your old code when it advances to the next version. ;)

On the flip side, it is very well-known that all the top AI shops (ex. OpenAI, Apple, and JPMorgan Chase) use PyTorch. OpenAI just recently switched to PyTorch in 2020, a strong sign that PyTorch is picking up steam.

If you are a professional, you will quickly recognize that building and testing new ideas is extremely easy with PyTorch, while it can be pretty hard in other libraries that try to do everything for you. Oh, and it's faster.

Deep Learning has been responsible for some amazing achievements recently, such as:

  • Generating beautiful, photo-realistic images of people and things that never existed (GANs)

  • Beating world champions in the strategy game Go, and complex video games like CS:GO and Dota 2 (Deep Reinforcement Learning)

  • Self-driving cars (Computer Vision)

  • Speech recognition (e.g. Siri) and machine translation (Natural Language Processing)

  • Even creating videos of people doing and saying things they never did (DeepFakes - a potentially nefarious application of deep learning)

This course is for beginner-level students all the way up to expert-level students. How can this be?

If you've just taken my free Numpy prerequisite, then you know everything you need to jump right in. We will start with some very basic machine learning models and advance to state of the art concepts.

Along the way, you will learn about all of the major deep learning architectures, such as Deep Neural Networks, Convolutional Neural Networks (image processing), and Recurrent Neural Networks (sequence data).

Current projects include:

  • Natural Language Processing (NLP)

  • Recommender Systems

  • Transfer Learning for Computer Vision

  • Generative Adversarial Networks (GANs)

  • Deep Reinforcement Learning Stock Trading Bot

Even if you've taken all of my previous courses already, you will still learn about how to convert your previous code so that it uses PyTorch, and there are all-new and never-before-seen projects in this course such as time series forecasting and how to do stock predictions.

This course is designed for students who want to learn fast, but there are also "in-depth" sections in case you want to dig a little deeper into the theory (like what is a loss function, and what are the different types of gradient descent approaches).

I'm taking the approach that even if you are not 100% comfortable with the mathematical concepts, you can still do this! In this course, we focus more on the PyTorch library, rather than deriving any mathematical equations. I have tons of courses for that already, so there is no need to repeat that here.

Instructor's Note: This course focuses on breadth rather than depth, with less theory in favor of building more cool stuff. If you are looking for a more theory-dense course, this is not it. Generally, for each of these topics (recommender systems, natural language processing, reinforcement learning, computer vision, GANs, etc.) I already have courses singularly focused on those topics.

Thanks for reading, and I’ll see you in class!

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

  • Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)

Modern Artificial Intelligence with Zero Coding

Build 5 Practical Projects & Harness the Power of AI to solve practical, real-world business problems with Zero Coding!

Created by Dr. Ryan Ahmed, Ph.D., MBA - Professor & Best-selling Udemy Instructor, 200K+ students

"]

Students: 3769, Price: $199.99

Students: 3769, Price:  Paid

Do you want to build super powerful applications in Artificial intelligence (AI) but you don’t know how to code?

Are you intimidated by AI and don’t know where to start?

Or maybe you don’t have a computer science degree and want to break into AI?

Are you an aspiring entrepreneur who wants to maximize business revenue and reduce costs with AI but don’t know how to get there quickly and efficiently?

If the answer is yes to any of these questions, then this course is for you!

Artificial intelligence is one of the top tech fields to be in right now!

AI will change our lives in the same way electricity did 100 years ago.

AI is widely adopted in Finance, banking, healthcare, transportation, and technology. The field is exploding with opportunities and career prospects.

This course solves a key problem which is making AI available to anyone with no coding background or computer science degree.

The purpose of this course is to provide you with knowledge of key aspects of modern AI without any intimidating mathematics and in a practical, easy, and fun way. The course provides students with practical hands-on experience using real-world datasets.

In this course, we will assume that you have been recently hired as a consultant at a start-up in San Francisco. The CEO has tasked you to apply cutting edge AI techniques to 5 projects. There is only one caveat, your key data scientist quit on you and do not know how to code, and you need to generate results fast. In fact, you only have one week to solve these key company problems. Your will be provided with datasets from all these departments and you will be asked to achieve the following tasks:

  • Project #1: Develop an AI model to detect people emotions using Google Teachable Machines (Technology).

  • Project #2: Develop an AI model to detect and classify chest disease using X-Ray chest data using Google Teachable Machines (HealthCare).

  • Project #3: Predict Insurance Premium using Customer Features such as age, smoking habit and geo-location using AWS AI AutoPilot (Business).

  • Project #4: Detect Cardiovascular Disease using DataRobot AI (HealthCare).

  • Project #5: Recognize food types and explore AI explainability using DataRobot AI (Technology).

Financial Engineering and Artificial Intelligence in Python

Financial Analysis, Time Series Analysis, Portfolio Optimization, CAPM, Algorithmic Trading, Q-Learning, and MORE!

Created by Lazy Programmer Team - Artificial Intelligence and Machine Learning Engineer

"]

Students: 3670, Price: $199.99

Students: 3670, Price:  Paid

Have you ever thought about what would happen if you combined the power of machine learning and artificial intelligence with financial engineering?

Today, you can stop imagining, and start doing.

This course will teach you the core fundamentals of financial engineering, with a machine learning twist.

We will cover must-know topics in financial engineering, such as:

  • Exploratory data analysis, significance testing, correlations, alpha and beta

  • Time series analysis, simple moving average, exponentially-weighted moving average

  • Holt-Winters exponential smoothing model

  • ARIMA and SARIMA

  • Efficient Market Hypothesis

  • Random Walk Hypothesis

  • Time series forecasting ("stock price prediction")

  • Modern portfolio theory

  • Efficient frontier / Markowitz bullet

  • Mean-variance optimization

  • Maximizing the Sharpe ratio

  • Convex optimization with Linear Programming and Quadratic Programming

  • Capital Asset Pricing Model (CAPM)

  • Algorithmic trading (VIP only)

  • Statistical Factor Models (VIP only)

  • Regime Detection with Hidden Markov Models (VIP only)

In addition, we will look at various non-traditional techniques which stem purely from the field of machine learning and artificial intelligence, such as:

  • Regression models

  • Classification models

  • Unsupervised learning

  • Reinforcement learning and Q-learning

***VIP-only sections (get it while it lasts!) ***

  • Algorithmic trading (trend-following, machine learning, and Q-learning-based strategies)

  • Statistical factor models

  • Regime detection and modeling volatility clustering with HMMs

We will learn about the greatest flub made in the past decade by marketers posing as "machine learning experts" who promise to teach unsuspecting students how to "predict stock prices with LSTMs". You will learn exactly why their methodology is fundamentally flawed and why their results are complete nonsense. It is a lesson in how not to apply AI in finance.

As the author of ~30 courses in machine learning, deep learning, data science, and artificial intelligence, I couldn't help but wander into the vast and complex world of financial engineering.

This course is for anyone who loves finance or artificial intelligence, and especially if you love both!

Whether you are a student, a professional, or someone who wants to advance their career - this course is for you.

Thanks for reading, I will see you in class!

Suggested Prerequisites:

  • Matrix arithmetic

  • Probability

  • Decent Python coding skills

  • Numpy, Matplotlib, Scipy, and Pandas (I teach this for free, no excuses!)

WHAT ORDER SHOULD I TAKE YOUR COURSES IN?:

  • Check out the lecture "Machine Learning and AI Prerequisite Roadmap" (available in the FAQ of any of my courses, including the free Numpy course)

Practical AI with Python and Reinforcement Learning

Learn how to use Reinforcement Learning techniques to create practical Artificial Intelligence programs!

Created by Jose Portilla - Head of Data Science, Pierian Data Inc.

"]

Students: 3177, Price: $89.99

Students: 3177, Price:  Paid

Please note! This course is in an "early bird" release, and we're still updating and adding content to it, please keep in mind before enrolling that the course is not yet complete.

“The future is already here – it’s just not very evenly distributed.“

Have you ever wondered how Artificial Intelligence actually works? Do you want to be able to harness the power of neural networks and reinforcement learning to create intelligent agents that can solve tasks with human level complexity?

This is the ultimate course online for learning how to use Python to harness the power of Neural Networks to create Artificially Intelligent agents!

This course focuses on a practical approach that puts you in the driver's seat to actually build and create intelligent agents, instead of just showing you small toy examples like many other online courses. Here we focus on giving you the power to apply artificial intelligence to your own problems, environments, and situations, not just those included in a niche library!

This course covers the following topics:

  • Artificial Neural Networks

  • Convolution Neural Networks

  • Classical Q-Learning

  • Deep Q-Learning

  • SARSA

  • Cross Entropy Methods

  • Double DQN

  • and much more!

We've designed this course to get you to be able to create your own deep reinforcement learning agents on your own environments. It focuses on a practical approach with the right balance of theory and intuition with useable code. The course uses clear examples in slides to connect mathematical equations to practical code implementation, before showing how to manually implement the equations that conduct reinforcement learning.

We'll first show you how Deep Learning with Keras and TensorFlow works, before diving into Reinforcement Learning concepts, such as Q-Learning. Then we can combine these ideas to walk you through Deep Reinforcement Learning agents, such as Deep Q-Networks!

There is still a lot more to come, I hope you'll join us inside the course!

Jose

Artificial Intelligence Ethics Certification

Understand the foundation of your moral code and how it can guide you through the most influential industry of our time.

Created by Ross Asdourian - Founder and Editor

"]

Students: 2131, Price: $19.99

Students: 2131, Price:  Paid

The AI Ethics Certification course teaches right and wrong, if such a thing exists, in the context of the artificial intelligence industry. This three-section training starts by asking "What is ethics?" We’ll discuss its history, different philosophies, ethics in business, and learn the five most common principles. Second, ethics as it pertains specifically to AI with interviews from founders across the globe. We will examine commonly cited principles from governments and leaders and equate them to the five traditional pillars. Then finally, we establish a framework for your ethics roadmap. The goal is to provide stronger trust between you, your product or service, the people in the industry, and the public. Despite being a nebulous topic, we'll have fun on the path to understanding morality and committing to a better future.

Introduction to Artificial Intelligence ( AI ) for Managers

Data Science, Machine Learning, Deep Learning & Neural Networks for Beginners with Scikit-Learn & Python

Created by Kumaresan Ramanathan - Principal Architect at Coroman Systems

"]

Students: 1764, Price: $29.99

Students: 1764, Price:  Paid

Do you want to learn Artificial Intelligence technology quickly?

Are you a manager, director, or VP who needs to understand how AI works at a technical level?

This fast-paced course explains the core concepts of Artificial Intelligence through engaging animations. In less than 2 hours you will be able to:

- Identify opportunities for using AI in your business

- Evaluate technical solutions

- Manage AI development projects

- Estimate resource requirements for your AI project

- Reuse pre-trained libraries to save cost

... and lead your AI project to success.

Prerequisites

You must be adept with 10th grade level high-school Math. 

This course describes AI algorithms at a technical level. You need to be able to understand step-by-step descriptions of algorithms.

Though this is a non-coding introduction, some knowledge of programming will make it easier to understand the algorithms presented.

Technology Explained in Simple Terms

You will be able to apply these algorithms in your own projects: kNN, Stochastic Gradient Descent, Regularization, Support Vector Machines, Random Forests, Classification with Sigmoids, Multi-Layer Neural Nets, Deep Learning with Convolutional Neural Networks and Recurrent Nets, and Natural Language Processing with Word-Embeddings. 

Real-world project:

You will build an AI system that detects cancer. The code is explained clearly line-by-line. No prior programming knowledge is required. This project is developed on Python with the Scikit-Learn library.

Experience:

The material in this course is built upon 15 years of my experience developing machine learning systems for industry projects.

Enroll today & accelerate your career with AI.

Artificial Intelligence for Simple Games

Learn how to use powerful Deep Reinforcement Learning and Artificial Intelligence tools on examples of AI simple games!

Created by Jan Warchocki - Artificial Intelligence Engineer

"]

Students: 1578, Price: $99.99

Students: 1578, Price:  Paid

Ever wish you could harness the power of Deep Learning and Machine Learning to craft intelligent bots built for gaming?

If you’re looking for a creative way to dive into Artificial Intelligence, then ‘Artificial Intelligence for Simple Games’ is your key to building lasting knowledge.

Learn and test your AI knowledge of fundamental DL and ML algorithms using the fun and flexible environment of simple games such as Snake, the Travelling Salesman problem, mazes and more.

1. Whether you’re an absolute beginner or seasoned Machine Learning expert, this course provides a solid foundation of the basic and advanced concepts you need to build AI within a gaming environment and beyond.

2. Key algorithms and concepts covered in this course include: Genetic Algorithms, Q-Learning, Deep Q-Learning with both Artificial Neural Networks and Convolutional Neural Networks.

3. Dive into SuperDataScience’s much-loved, interactive learning environment designed to build knowledge and intuition gradually with practical, yet challenging case studies.

4. Code flexibility means that students will be able to experiment with different game scenarios and easily apply their learning to business problems outside of the gaming industry.

‘AI for Simple Games’ Curriculum

Section #1 — Dive into Genetic Algorithms by applying the famous Travelling Salesman Problem to an intergalactic game. The challenge will be to build a spaceship that travels across all planets in the shortest time possible!

Section #2 — Learn the foundations of the model-free reinforcement learning algorithm, Q-Learning. Develop intuition and visualization skills, and try your hand at building a custom maze and design an AI able to find its way out.

Section #3 — Go deep with Deep Q-Learning. Explore the fantastic world of Neural Networks using the OpenAI Gym development environment and learn how to build AIs for many other simple games!

Section #4 — Finish off the course by building your very own version of the classic game, Snake! Here you’ll utilize Convolutional Neural Networks by building an AI that mimics the same behavior we see when playing Snake.

Intro to Big Data, Data Science and Artificial Intelligence

Big Data Technology & Tools for Non-Technical Leaders. Industry expert insights on IoT, AI and Machine Learning for all.

Created by Julia Mariasova - Management Consultant / Media Producer

"]

Students: 1292, Price: $44.99

Students: 1292, Price:  Paid

If you are like me - finding it difficult to read thick manuals with formulae, but still very much interested in modern technologies and their applications, then this course is for you.

You will learn about big data, Internet of Things (IoT), data science, big data technologies, artificial intelligence (AI), machine learning (ML) algorithms, neural networks, and why this could be relevant to you even if you don't have technology or data science background. Please note that this is NOT TECHNICAL TRAINING and it does NOT teach Coding/Development or Statistics.

The course includes the interviews with industry experts that cover  big data developments in Real Estate, Logistics & Transportation and Healthcare industries.  You will learn how machine learning is used to predict engine failures, how artificial intelligence is used in anti-ageing, cancer treatment and clinical diagnosis, you will find out what technology is used in managing smart buildings and smart cities including Hudson Yards in New York.  We have got fantastic guest speakers who are the experts in their areas:

- WAEL ELRIFAI - Global VP of Solution Engineering - Big Data, IoT & AI at Hitachi Vantara with over 15 years of experience in the field of machine learning and IoT. Wael is also a Co-Authour of the book "The Future of IoT".

- ED GODBER - Healthcare Strategist with over 20 years of experience in Healthcare, Pharmaceuticals and start-ups specialising in Artificial Intelligence.

- YULIA PAK - Real Estate and Portfolio Strategy Consultant with over 12 years of experience in Commercial Real Estate advisory, currently working with clients who deploy IoT technologies to improve management of their real estate portfolio.

Hope you will enjoy the course and let me know  in the comments of each section how I can improve the course!

Artificial Intelligence for Finance, Accounting & Auditing

Gain hands-on skills using 8 AI techniques (no coding!), and position yourself for this digital age (Level 1)

Created by AI Ascent LLC. Course Instructor: Ivy Munoko, ACCA, CISA - AI Instructor

"]

Students: 994, Price: $89.99

Students: 994, Price:  Paid

This course will provide students and professionals a 360 degree view of the current Artificial Intelligence techniques used in Business, Finance, Accounting and Auditing. Through a mix of lectures, hands-on exercises (code free!), case studies, reflection exercises and knowledge-check quizzes, this course will provide a quick and deep overview of Artificial Intelligence (AI) in business.

In this digital age, all careers have a computing element as digitization and automation comes to the forefront of business processes. Those who complete this course will be able to reposition themselves to initiate and implement AI innovation within their teams, and confidently walk into this AI age.

The 8 AI techniques that will be covered in this course include:

  • Chatbot (hands-on software: IBM Watson)

  • Natural Language Processing (hands-on software: RapidMiner with add-ons)

  • Machine Learning (hands-on software: RapidMiner)

  • Machine Vision (hands-on software: Google Apps)

  • Speech Recognition (hands-on software: IBM Watson and Cortana)

  • Internet of Things (hands-on software: MATLAB and ThingSpeak)

  • Robotic Process Automation with Intelligence layer (hands-on software: Automation Anywhere)

  • Smart Analytics (software: MindBridge Ai)

Artificial Intelligence Introduction

Introduction to AI, ML, Data Science , BI and Analytics for Non-Technicals, Leaders, Managers, freshers and Beginners

Created by Sudhanshu Saxena - Data Scientist, Machine Learning & Big Data Consultant

"]

Students: 376, Price: $19.99

Students: 376, Price:  Paid

Section 1-L1:

To learn the strategy of various skills of current and future world like Artificial Intelligence, Machine learning, Data Science, we are starting from understanding data. To expertise in Artificial Intelligence needs to be understood the basics of data. In this INTRODUCTION section, we will talk about

What is the data?

How does data divide into multiple parts?

Types of data!

How do and where the data generate from?

What kind of data available globally?

How we can deal with the data?

Apart from that, we will discuss the Characteristics of the structured data.

Sources of the Structured data.

Section 1-L2:

The questions you should seek are, How Machine Learning, Artificial Intelligence can handle this.

As we understood the Data, its type, and the structured data, here we will talk about the Unstructured Data.

This second lecture will be covering Types of Unstructured data.

Advantages and disadvantages of unstructured data.

Problem faced in storing unstructured Data

Section 1-L3:

Out of all available data, the most crucial data is Semi-structured Data which allows the user to have a flexible Schema. In the previous lecture, we talked about what kinds of data can be deal with, the type of data, its advantages--disadvantages of unstructured data.

Here we will be learning about the most useful type of data called -Semi-Structured Data.

Characteristics of Semi-structured Data

Source of Semi-structured Data.

Advantages and disadvantages of Semi-structured data.

Section 2-L4:

In the previous section, we understood the Data, its type, Advantages-Disadvantages of different kinds of data and where data comes from.

So here, in this section, we will cover: -

What is Big Data? Why even we care about it?

What can be done with this Bigdata?

The Hype around Big Data?

Section 2-L5:

This lecture is intended to cover the term Bigdata-Why any data called Bigdata?

How to identify if my data is Bigdata?

What are the properties of the Bigdata?

Do I see the similar properties in my Data also?

What are the characteristics of Bigdata?

How do you store the Bigdata?

Where to store Bigdata?

What tools and tricks are used to handle Bigdata?

Four dimensions of Bigdata?

Section 2-L6:

if we understand the data its size and types of data, we should know who is creating this data. This section is covering all aspects of Bigdata including:

How much bigdata I am (an individual) accumulating?

How tough it is for us to deal with this kind of data?

What are the challenges in handling this kind of Bigdata?

Section 2-L7:

we will also cover the Model of BigData generation?

This lecture describes how this Big-data gets generated

Why this data is huge now?

What do organizations want?

Which all companies are working on Bigdata?

Get answers to all these questions in this video.

Section 3-L8:

This new section is intended to describe what is Analytics and why it came into existence and Understanding Analytics from scratch. To understand that we will seek the answers to all possible questions like

What are the four major questions we want to answer?

What kind of analytics are possible?

What is the difference among all this Analytics-Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics?

Section 4-L9

As data is the basic foundation of AI, with its existence, types analysis and analytics Business intelligence plays an important role in using huge sized data. To understand BI we will cover

How to answer the first basic question of analytics?

How to get started with analytics?

What all organizations can achieve with Business Intelligence?

What are the Functions of Business Intelligence?

How to implement a Business Intelligence system in an organization?

What kind of data Business Intelligence require?

Section 5- L10

Here you are ready to learn why and what Artificial Intelligence is?

we will start from

Understanding Artificial Intelligence from scratch covering all questions like

What are the different definitions of Artificial Intelligence?

Why it is needed to create Artificial Intelligence?

What are the types of AI?

How to see through Artificial Intelligence?

Applications of Artificial Intelligence.

Section 6-L11:

Machine learning is a part of AI and Data Science. It is necessary to understand ML if you are dealing with AI. here we will be Understanding Machine Learning from scratch.

Different definitions of Machine Learning.

Types of Machine Learning

How each type of ML is different from another and where are they going to use?

How does the computer understand the data?

Section 6-L12

Where we can use and see ML applications in our Daily Life

How to use Machine Learning in real-time applications.?

ML use case in similar Pins

ML use case in face recognition.

ML use case in people you may know

ML use case in spam Email filtering

ML use case in Product recommendations

ML use case in online fraud detections

ML use case in Disease identifications

ML use case in Personalised treatment

ML use case in clinical trial research

ML use case in character recognitions

Section 7: L13

This section is all about AI from very scratch, we discuss all sections of AI, ML and now we talk about Data Science, How does data science relate to Artificial Intelligence? To answer this question, we will discuss

What is Data Science?

The definition of Data Science?

How does Data Science connect with analysis?

Components of Data Science.

Data Science Lifecycle.

Use of Mathematics in Data Science?

Use of Machine Learning in Data Science.

Difference between Business Intelligence and Data Science.

The Complete Artificial Intelligence for Cyber Security 2021

Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications

Created by Hoang Quy La - Electrical Engineer

"]

Students: 230, Price: $89.99

Students: 230, Price:  Paid

*** AS SEEN ON KICKSTARTER ***

Learn key AI concepts and intuition training to get you quickly up to speed with all things AI. Covering:

  • How to start building AI with no previous coding experience using Python.

  • How to solve AI problems in cyber security field.

Here is what you will get with this course:

1. Complete beginner to expert AI skills – Learn to code self-improving AI for a range of purposes. In fact, I will code together with you. Every tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means.

2. Coding step– Plus, you’ll get a template which shows all the steps and all detailed explanations on each step.

3. Intuition Tutorials – Where most courses simply bombard you with dense theory and set you on your way, you will develop a deep understanding for not only what you’re doing, but why you’re doing it. That’s why I don’t throw complex theories at you, but focus on building up your intuition in coding AI making for infinitely better results down the line.

4. Real-world solutions – You’ll achieve your goal in not only 1 project but in more than 10. Each module is comprised of varying structures and difficulties, meaning you’ll be skilled enough to build AI adaptable to any projects in real life, rather than just passing a glorified memory “test and forget” like most other courses. Practice truly does make perfect.

5. In-course support – I fully committed to making this the most accessible and results-driven AI course on the planet. This requires me to be there when you need my help. That’s why I will support you in your journey, meaning you’ll get a response from me within 72 hours maximum.