Best Free Data Analysis Courses

Find the best online Free Data Analysis Courses for you. The courses are sorted based on popularity and user ratings. We do not allow paid placements in any of our rankings.

Microsoft Excel Pivot Tables – The Beginner Course

Start analyzing data with Excel's most powerful data analysis tool, Pivot Tables. They're easier than you think!

Created by Matt Jackman - Digital Analytics and SEO Professional

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Students: 151181, Price: Free

What's this course about

Pivot Tables are one of the most powerful features in Excel. Once you learn how to use Pivot Tables, they'll change the way you use Excel.

If you're not familiar with Pivot Tables, they're a tool that allow you to summarize large sets of information quickly and easily. You can analyze thousands of rows in a matter of seconds that could otherwise take hours trying to figure out using complex formulas.

This is an introductory Pivot Table course and gives the information you'll need to start using Pivot Tables.

Who will benefit from this course

If you're somebody that uses Excel on a regular basis to track or maintain information, you will definitely benefit from learning Pivot Tables.

You don't have to be a master of Excel formulas to take this course, but you should have a sound understanding of how to navigate around Excel before you take this course.

This would be considered an intermediate Excel course and students should understand basic mathematical calculations (e.g. addition, subtraction, multiplication and division) and formulas in Excel.

What you'll learn in this course

  • How to create a Pivot Table
  • How to summarize information in different ways using Pivot Tables

By the end of this course, you'll be able to take your own information and leverage Pivot Tables to answer questions with ease!

Data Science, Machine Learning, Data Analysis, Python & R

FREE Course on Data Science, Machine Learning, Data Analysis, Data Visualization using Python and R Programming

Created by DATAhill Solutions Srinivas Reddy - Data Scientist

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Students: 65970, Price: Free

Interested in the field of Data Science, Machine Learning, Data Analytics, Data Visualization? Then this course is for you!

This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way.

We will walk you step-by-step into the World of Data Science. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.

Moreover, the course is packed with practical exercises which are based on real-life examples. So not only will you learn the theory, but you will also get some hands-on practice building your own models.

And as a bonus, this course includes both Python and R code templates which you can download and use on your own projects.

Master Data Analysis with Python – Intro to Pandas

Begin your data analysis journey with Python by mastering the fundamentals of the pandas library

Created by Ted Petrou - Author of Pandas Cookbook, Founder of Dunder Data

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Students: 34773, Price: Free

Master Data Analysis with Python - Intro to Pandas targets those who want to completely master doing data analysis with pandas. This course provides an introduction to the components of the two primary pandas objects, the DataFrame and Series, and how to select subsets of data from them.

This course is taught by expert instructor Ted Petrou, author of the highly-rated book Pandas Cookbook. Ted has taught over 1,000 hours of live in-person data science courses that use the pandas library. Pandas is a difficult library to use effectively and is often taught incorrectly with poor practices. Ted is extremely adept at using pandas and is known for developing best practices on how to use the library.

There are nearly 50 exercises available to help practice the material taught from the lectures. Detailed video and text solutions for each of the exercises are available so that you can see exactly how Ted thinks through the exercises to arrive at a solution.

All of the material and exercises are written in Jupyter Notebooks, which you will be able to download. This allows you to read the notes, run the code, and write solutions to the exercises all in a single place. Additionally, the full contents of the course are available as a 120-page document giving you access to the material from anywhere.

This course targets those who have an interest in becoming experts and completely mastering the pandas library for data analysis in a professional environment. This course does not cover all of the pandas library, just a small and fundamental portion of it. If you are looking for a brief introduction of the entire pandas library, this course is not it. It takes many dozens of hours, lots of practice, and rigorous understanding to be successful using pandas for data analysis.

This course assumes no previous pandas experience. The only prerequisite knowledge is to understand the fundamentals of Python.

This course is the first from the 10-part series Master Data Analysis with Python. The second part is titled Master Data Analysis with Python - Essential Pandas Commands.

Learn Data Analysis using Pandas and Python (Module 2/3)

Analyze and Manipulate data using using Python and powerful Pandas.

Created by Rakesh Gopalakrishnan - Over 260,000 Students

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Students: 33276, Price: Free

Are you completely new to Data science?

Have you been hearing these buzz words like Machine learning, Data Science, Data Scientist, Text analytics, Statistics and don't know what this is?

Do you want to start or switch career to Data Science and analytics?

If yes, then I have a new course for you. This is module # 2 of the Data Science series. In this course, I cover the absolute basics data analysis and manipulation techniques using Pandas. This course will not cover every syntax available in Pandas, but will take you a level where you can do basic to intermediate data analysis, before proceeding towards feeding it to a data science algorithm.

If are you new to data science, I would recommend you to please take Module # 1(Introduction to Data Science using Python) before starting with this course. We will go through commonly used terms and write plenty of code in Python. I spend some time walking you through different career areas in the Business Intelligence Stack, where does Data Science fit in, What is Data Science and what are the tools you will need to get started.

I will be using Python and Pandas in a series of such courses. I am not assuming any prior knowledge in this area. I have given some reading materials, which will help you solidify the concepts that are discussed in this lectures.

This course will the second data science course in a series of courses. Consider this course as a 101 level data manipulation course, where I cover enough to raise your curiosity in the field of Data Science and Analytics.

The other modules will cover more complex concepts. 

Fundamentals Data Analysis & Decision Making Models – Theory

Master handling Big Data, Analysis and presenting interactive DashBoards. Forecasting and

Created by Manish Gupta - Hospitality Finance Expert and Business Strategist

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Students: 25482, Price: Free

 Do you want to understand how big data is analysed and how decisions are made based on big data.

In this course we will be covering the various steps involved in data analysis in brief, Objective of this course to make you familiar with these steps and collect your feedbacks and questions.

I will then use those feedback and questions to make the detailed course better and relevant for you.

Introduction to Data Analysis for Government

Get started on your journey to become a government data analysis rockstar.

Created by Socrata Data Academy - Teaching program leaders and government information workers how to analyze data and proficiently use modern data analysis technologies

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Students: 16860, Price: Free

Data has exploded in the last few years, but educational resources for government information workers to take advantage of that data to improve program outcomes haven't kept up. This first course in the series Fundamentals of Data Analysis for Government focuses on the key components of setting up and executing a data analysis project.

What You'll Learn in this Course

  • How to frame a data analysis project
  • The power of simple descriptive statistics to guide decision making
  • Examples of data being effectively used in the public sector
  • Methods to download, evaluate, clean, and analyze data using Excel
  • How you can be influenced by biases, and can unintentionally introduce them into your analysis
  • The difference between structured, machine-readable data and unstructured, human-readable data

Contents and Overview

This course is ideal for government employees who have a strong qualitative understanding of their work but have yet to master the quantitative skills needed to leverage data in their day-to-day responsibilities. Through ~25 lectures and ~2 hours worth of content, you'll learn all of the fundamentals of government data analysis and establish a strong understanding of the concepts behind using data. Each chapter contains proficiency quizzes and hands-on exercises to practice while you're learning.

Starting with a high-level overview of a data analysis project framework, this course will take you through identifying the actual problem to solve, exploring and defining a conceptual model around the problem, analyzing data to support or reject that model, then communicating insights found from the data analysis to address the problem at hand. Students will see all steps of the framework completed through the lens of a real-world data project done in the City of New Orleans.

Students completing the course will have the knowledge to analyze data and utilize it to improve government program delivery.

With these basics mastered, students are able to continue their learning through the Socrata Data Academy courses online.

SQL for Data Analysis: Solving real-world problems with data

A simple & concise mySQL course (applicable to any SQL), perfect for data analysis, data science, business intelligence.

Created by Max SQL - Data and Insights Manager

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Students: 16662, Price: Free

Note on the Short Version of the Course

I have launched the course as a free, shortened version. It is an excellent introduction to the basics of handling data. Two points I want you to know:

1. The course so far is an in-depth view on a small & important part of SQL, rather than a light-touch overview of everything.

2. Technically, the full paid version is on the way. But I am finding it very difficult to find the time to complete the lessons (between other projects and work).

Therefore for those who need a comprehensive course now, I'd suggest signing up to a couple of courses now including this one while it's free. That way you can learn now but also enjoy all the additional lessons for free when they arrive.

Note on the Communicating

Udemy prevents instructors of Free courses from answering any questions from students. Therefore for now I cannot provide any feedback or respond to comments.

Summary

Forget the dry, old, textbook approach to learning code. Forget endlessly drilling syntax.

This course puts SQL in context and gets you solving real-world business problems from Day 1.

You'll play the role of a data analyst at Australia's largest fictional consumer bank, with a uniquely rich relational database at your fingertips. This context brings SQL to life and makes it easier for you to understand deeply and quickly.

With this new approach, you'll be surprised to see that SQL is fun and simple to learn. My course guarantee is that you'll go from zero to functional SQL coder within the weekend.

Best features in a nutshell

  • In plain English, with business context and fun analogies to explain the otherwise dry syntax.

  • Unique database, using a fictional bank relational database with incredibly rich transaction data to keep the course interesting and relevant.

  • Focuses deep on the absolute basics, to get you the strong foundations required for a data career.

  • Doesn’t cost money! If you sign up now while it’s free, you have lifetime free access, even as the course grows and becomes paid.

Read on for more detail

My story and building the course

My SQL learning experience was not ideal. When I started work I hadn’t the slightest idea what data was, let alone the power it brings to those who wield it skillfully. I took probably a year longer than necessary to master the SQL for data analytics. Even though I was practicing everyday on the job, I was slow to understand new concepts and struggled to remember new syntax.

Now as a full-time data analytics and insights manager, I have the hindsight to know it should have been much easier.

The main ingredients missing for me were:

  1. Structure

    1. What is important, what isn't, and why.

  2. Context

    1. Analogies, interesting examples, and plain English explanations. Bringing it to life!

So I’ve taken what was lacking in my learning experience and build a course around it. Specifically, here’s why my course stands out:

  • Structured

    • We learn what you need for on the job data analysis using SQL, no more less.

    • The topics are covered in an order that makes sense and helps you build on past learning.

    • You understand why each lesson is important, where it sits in the grand scheme of SQL.

  • In context

    • SQL shouldn’t have to be dry or boring, so I have used realistic business problems and analogies.

    • You’ll be playing the role of a data analyst at the largest fictional company in Australia, the Royal Bank of Australia, solving problems to drive sales, improve marketing reach, and manage customers.

    • Knowing why you’re learning the syntax, you’ll learn faster.

  • Hands on/practical

    • You’ll practice writing SQL in every single lesson.

We are going to have fun too, investigating cryptocurrency trading among customers, and even learning about Australian animals!

Why learn SQL?

Most successful companies today are data-driven.

  • They record every bit of information about their business (e.g. customers, sales).

  • They store that information (called data) in complex databases.

  • And they draw insights from the data to improve their business.

That’s where SQL comes in.

The only way to gather data and transform it into valuable business insights is to combine SQL and a smart analyst like you.

It's with SQL that companies know answers all sorts of where do my customers prefer to shop? Who was incorrectly charged fees? Why are sales going down?)

And as you may have noticed in the Promo, SQL is a great skill to build your career

Data careers, in data analysis (business analysis), data science, & data visualisation (business intelligence).

  1. SQL is needed to actually find and handle data in most organisations.

  2. The data handling and management skills learned via SQL are fundamental to understanding data in general, and are useful even if you don't use the SQL language (rare).

  3. Access to data can make you powerful in organisations. It's hard to argue with an analyst armed with well-prepped data and a solid numbers-based argument.

Marketing, product management, and tech sales:

  1. SQL (and the accompanying data skills) are a great way to stand out in marketing and product.

  2. Marketers and product managers propose changes to improve the business.

  3. Nowadays, any proposed change needs a strong case to support it.

  4. Data is the foundation of any strong business case.

  5. Therefore marketers and product managers with data skills can put together stronger cases, get more initiatives approved, and grow their career faster.

Why start with mySQL? mySQL is:

  • Very common, used by major companies and organisations across the world, such as Uber, Netflix, Spotify, and JPMorgan.

  • Free and easy to set up.

  • Similar to other forms of SQL like Microsoft SQL Server, PostGre SQL, Oracle SQL, Teradata SQL.

Data Visualization in Python Masterclass™ for Data Scientist

Matplotlib for Data Visualization and analysis with Python 2021 Edition

Created by Abbosjon Madiev - Computer Scientist

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Students: 12318, Price: Free

The only way to truly learn how to use Matplotlib for Data Visualization with Python is by actually getting your hands dirty and trying out the features yourself. That’s where this course comes in!

The hour-long course starts off with an introduction to Matplotlib, including how to install and import it in Python. We will then move on to learn how you can create and customize basic 2D charts in order to best tell your story. Furthermore, you will also learn what subplots are and how you can create as well as customize them with the help of the Matplotlib library.

We will explore the full spectrum of interactive and explorable graphic representations including various plots such as Scatter, Line, Bar, Stacked Bar, Histogram, Pie, and much more. The course also walks you through the basics of creating a 3D plot in Matplotlib and how you can start plotting images using the Python visualization library.

And, once you are done with this course, you will be able to create almost any kind of plot that you need with Matplotlib and Python.

Why you should take this course?

  • Updated 2021 course content: All our course content is updated as per the latest version of the Matplotlib library.

  • Practical hands-on knowledge: This course is oriented to providing a step-by-step implementation guide for making amazing data visualization plots rather than just sticking to the theory.

  • Guided support: We are always there to guide you through the Q/As so feel free to ask us your queries

Data Science with Analogies, Algorithms and Solved Problems

Machine learning, Data Mining, Data Science, Deep Learning, Data analysis, Data analytics, Python, Visualization

Created by Ajay Dhruv - Assistant Professor at VIT Mumbai, India

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Students: 9523, Price: Free

Interested to know about the field of Machine Learning?

Then this course is for you! This course has been designed such that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way.

We will walk you into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this field. While preparing this course special care is taken that the concepts are presented in fun and exciting way but at the same time, we dive deep into machine learning.

Here is a list of few of the topics we will be learning:

• Difference between Data Mining and Deep Learning

• Data and 5 Vs of Big Data

• Types of Attributes

• Outliers

• Supervised learning, Unsupervised learning, Reinforcement learning

• Python Libraries

• CNN, RNN, LSTM

• K - means Clustering Algorithm

• Bayesian Algorithm, ID3 Algorithm

• Simple Linear Regression

• Anaconda

• Visualization

Python for Data Analysis

Learn to wrangle data with Python!

Created by Bob Wakefield - Data Management Expert

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Students: 8784, Price: Free

You know Python. You know Excel. You may even know how to crunch numbers in R using the Tidyverse if you have a statistics background.

But when it comes to applying all this knowledge to the world of data science, you know you need more than these tools to be successful. What makes matters worse is that you are not exactly sure of what order you should be learning which data science tools. It can be a challenge to know exactly where to focus, and how to apply what you do know.

At Mass Street University, we guide statisticians and developers interested in exploring how to process and analyze data—efficiently. In Python for Data Analysis, we focus you on precisely what you need to know, and teach you how best to utilize what you already do know.

In the course, we will teach you how to combine your existing knowledge of Python with tools like Pandas and Numpy. If you have only worked with the basic Python data types, approaching some of the higher order data types can be intimidating. The structure of our course takes you from the simplest tools to the more complex to ensure you stay focused on what you need while you build on your font of data science knowledge.

JupyterLab is one tool you may not be familiar with, and it is a popular data analysis notebook that supports many languages, including Python. Notebook technology is relatively new to the world of data science, and we will go over how JupyterLab will allow you to write much smaller amounts of code efficiently.

There are a ton of data science tools that interact very well with Python to make data science a breeze when explored and taught properly. And at Mass Street University, we make sure that this dynamic is managed as efficiently as possible. Enroll today in Python for Data Analysis to stay focused on what you need to excel in data analysis.

The Ultimate Python and Pandas Data Analysis Course

This comprehensive course will be your guide to learning how to use the power of Python to analyze data!

Created by Online Training Plus - Succinct low-barrier courses for free

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Students: 7213, Price: Free

Analyze data quickly and easily with Python's powerful pandas library!

Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed.

This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!

  • Perform a multitude of data operations in Python's popular "pandas" library including grouping, pivoting, joining and more!

  • Possess a strong understanding of manipulating data sets

  • Learn methods and attributes across numerous pandas objects

Data Science is a rewarding career that allows you to solve some of the world's most interesting problems.

This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost!

We'll teach you how to program with Python and how to create amazing data visualizations.

SQL Mastery & Data Analysis

Monkeying to SQL Mastery with Workout & Bootcamp. ! A Teaser to my Upcoming Course.

Created by Maverick Learning - Data & Business Intelligence , Web & Mobile, Communications

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Students: 5865, Price: Free

Note: Since our Main Course on SQL Mastery is delayed by a few more days, I am uploading another lecture in this Free Teaser course, on Transactions.  This topic will add tremendous value to your understanding of Database concepts.

There 'may be' a Million Jobs in Data Science.

There ARE MULTI MILLION number Jobs needing Strong SQL Skills !! For every Python resource needed, there are 10-20 SQL resources need.

SQL is one of THE BASIC needs of any IT professional (Software, Analyst, Engineering, Data Management , Reporting or anything !).

Anyone and Everyone - whether you are a Startup Enthusiast/Entrepeneur, Developer, Analyst, Call Center employee, Manager, Leader or just about ANYONE looking to tap the power of Software to scale up your business, career or launch your own startup, you MUST have strong SQL Skills.

MySQL is an opensource and ABSOLUTELY FREE Database system that pretty much is used by a MAJORITY of Startup companies (along with PhP).

This course is a Teaser for my upcoming course on SQL Mastery & Data Analysis, planned to publish  by end of November.

This teaser will give a sneak preview of my main course. I have worked on Data Management multi-year projects for Credi Card (Providian, Amex etc.), Banking (Credit Suisse,  Wells, BoFA etc.) and many other corporations and have crunched upto billions of rows in processing (for a SINGLE transaction table !). I am on a mission to prepare an  Easy to Understand and Wholesome course  on SQL Mastery that anyone (from the Smartest to the Dumbest in the room) can conquer easily. I want everyone to just Monkey their way to SQL Mastery without feeling confused or intimidated by it.

In this Course, I First attempt to explain Database and SQL concepts from a Layman's perspective or a Managerial view - without specific Tool or Language semantics. After the concepts, I move on to MySQL specific workings in the main course.

I plan to include plenty and plenty of working sql code for learning and practice.

Any FEEDBACK or SUGGESTIONS received, will be considered in the main course.

Big Data Analysis With Pandas Data Frame

Real World Projects: Data Analysis

Created by Saima Aziz - Instructor

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Students: 3572, Price: Free

Welcome to Data Analysis using Python. My name is Saima Aziz and I will be the instructor for this course. I have more than 25 years of teaching experience.

In this course, you will apply your coding skills to a wide range of datasets to solve real world projects using Pandas Data Frame, such as:

Covid-19 datasets,

London housing datasets,

Car datasets,

Police datasets,

Udemy courses datasets.

You will increase your chances of success in data science by experimenting with Python projects. That way, you're learning by actually doing instead of just watching videos.

Building projects will help you tie together everything you are learning. Once you start building projects, you will immediately feel like you are making progress.

Where should I start? What makes a good project? What do I do when I get stuck?

I have carefully designed the content of the course to be comprehensive and fully compatible with industrial requirements and easy to understand.

If you get stuck, don't give up! There is enough material in the course to help you solve the problems, and your hard work will pay off.

Excel – Data Analysis for Business

Unlock your BI Mind

Created by HG Martin - Business Analyst

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Students: 1897, Price: Free

Do you deal with data at work? Do you aspire to be a Data or Business Analyst? Then this course can help you. This course will cover not only the technical skills to improve your analysis in Excel, but also insights and examples based on real world scenarios that will help unlock your hidden BI Mind.

First, we will look at principles of Data management, cleaning, preparation as well as the mindset and work process that will allow you make an impact in your job. Using these skills, you will be able to effectively manage large data sets in Excel.

After this, we will slowly build up technical skills. We will begin by learning how to link data sets from various sources, for example, internal and external to your place of work, a vital part of your analysis toolbox.

Then we will build up abilities in dealing with conditional scenarios, layering techniques upon each other to tackle any problem.

Finally, we will use all the skills learned to tackle a challenge question derived from the real world.

After completing this course, you will both be ready to tackle more challenging problems at your own work and have a good foundation to build upon for any future up-skilling.

Learn Statistical Data Analysis with Python

Perform Statistical Data Analysis Techniques with the Python Programming Language. Practice Notebook included.

Created by Valentine Mwangi - Data Science Curriculum Designer

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Students: 1774, Price: Free

By the end of this course, you will have achieved the following learning outcomes:

  • I can explain and calculate the importance of measures of central tendency.

  • I can explain and calculate the importance of measures of dispersion.

  • I can identify the relative strengths and weaknesses of the measures of tendency.

  • I can identify the relative strengths and weaknesses of the measures of dispersion.

  • I can create and interpret a histogram, a bar chart, a box plot, and a frequency table.

  • I can identify and describe scatter plots and line graphs to determine the relationships between two variables.

  • I can calculate and interpret the Pearson correlation coefficient to determine the relationships between two variables. 

These are some of the basics statistical data analysis techniques that you will get to use while working on data science projects. For example, in order to check for model assumptions while working on a predictive solution, you will need to apply the above techniques i.e. to test for normality of variables in a dataset, you can plot a histogram or a pair plot, to check for correlation, you can calculate the Pearson correlation coefficient etc.

In addition, these techniques will also be important while also working on data analysis projects where the creation of a descriptive analysis report will be a necessity.