the best data analysis courses online reviewed - both free and paid

16 Best Data Analysis Courses For Beginners 2021 [Reviewed]

Last Updated On: April 17, 2021

Tons of courses on Data Analysis out there, but unsure about where to spend your time to make the best use of your time and money? Or maybe looking for the best FREE courses on Data Analysis topics? 

I’ve analyzed around 50 courses and tutorials on Data Analysis with Python that people are talking about on Reddit, Quora, and Facebook groups; most enrolled courses on top platforms like Coursera, EdX, Udemy, DataCamp, LinkedIn Learning; and most viewed tutorials on YouTube. 

After analyzing them, I created this list of The Best 16 Data Analysis Courses and Tutorials of 2021 that you should know about. I took the courses that I didn’t take earlier and ranked them according to their quality and completeness. 

The main topics covered in these Data Analysis courses are Numpy, Pandas, and SciPy. As you must need Data Visualization skills to get the best out of Data Analysis, the Matplotlib and Seaborn topics were also considered, mostly Matplotlib. 

You’ll find some complete courses on Data Science, as I’ve discussed in Top Data Science Courses On The Internet in Python and R 2021. But I love to take courses that are dedicated to smaller topics, because they dive very deep into each topic, and contain lots of practice problems and projects. 

I couldn’t make this list of the Best Resources for Data Analysis any shorter because of the quality and uniqueness each serves. This is my ultimate list. Just take the ones you find best suits you. If you still can’t decide, take a look at the special recommendation section at the end of the article.

3 Best Numpy and Scipy Courses for Data Analysis

  1. Numpy Data Science Essential Training by LinkedIn Learning
  2. Using Python for Research by Harvard University on Edx
  3. Working with Multidimensional Data Using NumPy by PluralSight

9 Best Resources to Learn Pandas for Data Analysis

  1. The Complete Pandas Bootcamp 2021: Data Science with Python by Udemy
  2. Data Analysis with Pandas and Python by Udemy
  3. pandas Foundations by DataCamp
  4. Data Manipulation with Python [Skill Track] by DataCamp
  5. Doing Data Science with Python by PluralSight
  6. Data Analysis with Python by IBM on Coursera
  7. The Ultimate Pandas Bootcamp: Advanced Python Data Analysis by Udemy
  8. Pandas Essential Training by LinkedIn Learning
  9. Exploratory Data Analysis With Python and Pandas - Guided Project on Coursera

4 Best YouTube Tutorials to Learn Data Analysis

  1. Complete Python NumPy Tutorial by Keith Galli
  2. Pandas Tutorials by Corey Schafer
  3. Python SciPy Tutorial For Beginners by Edureka
  4. Data Analysis with Python by FreeCodeCamp

One thing you should know is that the official documentation is your best buddies after you’ve taken these courses and want to dive even deeper. Here are the documentations:

16 Best Resources to Learn Data Analysis 2021 - Free and Paid

1. Numpy Data Science Essential Training by LinkedIn Learning

The most detailed numpy course for Data Analysis
The most detailed numpy course for Data Analysis
  • Rating:  4.8/5
  • Total Number of Students: 27k
  • Number of Courses: 1 (7 Chapters)
  • Certificate: Available
  • Level: Beginner, Intermediate 
  • Time to Complete: 1 week at 10 hours per week
  • Video Material Length: 3 hours 54 minutes
  • Projects: 1 project
  • Prerequisites: Python Programming
  • Cost: $30 per month or $20 per month annually

What You Will Learn

  • Using Jupyter Notebooks, including basic operations, markdown, and mathematical typesetting
  • Basics of numpy arrays including data types
  • Indexing, slicing, broadcasting, boolean masking techniques
  • Matplotlib for drawing different plots to visualize data
  • Numpy methods and their usage
  • Linear algebra and statistics with numpy

Key Pros/ Why You Should Enroll

  • Explains each topic in details and shows lots of examples
  • Teaches enough that you can start using numpy fluently
  • A huge number of numpy methods covered
  • Explains the usage of jupyter notebook, which is very helpful in Data Analysis

At first, this course seemed very plain to me. But then it started throwing lots of methods and examples that will help to build you a strong base on numpy. The best thing about this course is that the instructor explains the numpy methods by showing you the official documentation.

This way, you better understand why something works while others don’t. On the other hand, this is helpful for absolute beginners who don’t have experience in learning from the documentation.

2. Using Python for Research by Harvard University on Edx

Using Python for Research by Edx
The most practical way of learning Numpy
  • Rating:  4.8/5
  • Total Number of Students: 280k
  • Number of Courses: 1 (5 weeks)
  • Certificate: Available
  • Level: Beginner, Intermediate
  • Time to Complete: 1 month at 10 hours per week
  • Projects: 7 case studies and 1 final project
  • Prerequisites: Python programming
  • Cost: Free on audit (limited access) or $169

What You Will Learn

  • Python basics warm-up
  • Numpy library to manipulate mathematical data
  • Matplotlib library for visualizing data
  • How to use Python for research purpose with 7 different famous case studies
  • Case studies on statistical learning like regression and random forest

Key Pros/ Why You Should Enroll

  • Contains real-world case studies that help to learn numpy and matplotlib by practicing
  • Each video tutorial follows up with lots of quiz problems. So you understand the topics very efficiently
  • The only quality course till now that focuses more on practical learning than showing various methods, which you can read from the official documentation
  • You get to know how really Python helps in research!

This is an amazing course to learn numpy for Data Analysis because of the bunch of real-world case studies it offers and the huge number of practice problems after each video tutorial.

I recently solved a project problem for a client where the project was very similar to one of the case studies discussed here. So this course surely contains some real-world values! Note that to participate in the case studies, you must purchase the course.

3. Working with Multidimensional Data Using NumPy by PluralSight

numpy course by a google engineer on pluralsight
Numpy course by a Google engineer
  • Rating:  4.6/5
  • Number of Courses: 1 (4 sections)
  • Certificate: Available
  • Level: Beginner, Intermediate
  • Time to Complete: 1 week at 10 hours per week
  • Video Material Length: 1 hour 43 minutes
  • Projects: None
  • Prerequisites: Python programming
  • Cost: $29/m or $25/m annually

What You Will Learn

  • Basic to advanced applications of numpy in Data Analysis
  • Image manipulation with numpy
  • Complex indexing, broadcasting, and miscellaneous operations
  • Relation of numpy library with other Data manipulation libraries like Pandas and SciPy.

Key Pros/ Why You Should Enroll

  • Focuses more on multidimensional data
  • Learn how images are actually 3-dimensional arrays of numbers and how they are manipulated in computer vision
  • Various complex but commonly used high dimensional data indexing and slicing methods

The course instructor is a Google engineer and the course content is really satisfactory. It felt like a premium YouTube tutorial, to be honest. Because there’s no quiz or project that you can attend to sharpen your understanding. You surely will get some new aspects of data analysis, so it won’t be a waste of money.

4. The Complete Pandas Bootcamp 2021: Data Science with Python by Udemy

one of the best data analysis courses on udemy
detailed instructions on vast topics
  • Rating: 4.6 (2k ratings)
  • Total Number of Students: 13k
  • Number of Courses: 1 (31 sections)
  • Certificate: Available
  • Level: Beginner
  • Time to Complete: 1.5 months at 10 hours per week 
  • Video Material Length: 33.5 hours
  • Projects: Available
  • Prerequisites: None/ Python programming
  • Cost: $12

What You Will Learn

  • Basics of Jupyter Notebook, Python programming, Numpy, and Statistical concepts
  • Deep dive into Pandas library with lots of examples
  • Data cleaning, manipulating, and visualizing 
  • Matplotlib and Seaborn for Data Visualization
  • Time series analysis
  • Machine Learning concepts

Key Pros/ Why You Should Enroll

  • By far the most complete course on Data Manipulation
  • Includes the prerequisites as an appendix to discuss Python, Numpy, and Statistical concepts (I still prefer learning them separately)
  • Extends to various machine learning concepts to show the application of Pandas library
  • The newest course on Data Analysis with Python till now
  • Covers a lot of topics of Pandas

Top Review

extremely thorough & comprehensive. it is obvious that a lot of care and attention has gone into the preparation of the course and material. good, prompt, support to any questions raised as well.

- Douglas Smith

This course is a gem for Data Analysis with Pandas. The only thing you may dislike is the accent of the instructor. Other than that, contains a huge amount of information. Although the main focus is Pandas library, the instructor spent a lot of time making it the perfect course. Covers all the prerequisites and also follows some Machine Learning topics to add some extra spice.

Although this course seems a complete course to Data Analytics, still, you’ve to take different courses on other topics. Because, the course surely dives deep into Pandas and serves necessary knowledge to cope up with the flow, but it’s not possible to cover those extra topics within a few hours of lectures.

5. Data Analysis with Pandas and Python by Udemy

The most famous Data Analysis course on Udemy till now
The most famous Data Analysis course on Udemy
  • Rating:  4.7/5 (13k ratings)
  • Total Number of Students: 150k
  • Number of Courses: 1 (15 sections)
  • Certificate: Available
  • Level: Beginner, Intermediate
  • Time to Complete: 1 month at 10 hours per week 
  • Video Material Length: 20.5 hours
  • Projects: Available
  • Prerequisites: Numpy library, Python programming (optional)
  • Cost: $12

What You Will Learn

  • A crash course on Python and Jupyter notebook
  • A huge number of topics in Pandas library with lots of examples
  • Time series analysis
  • Data visualization with Matplotlib
  • Options and settings in Pandas library

Key Pros/ Why You Should Enroll

  • A complete course on Data Analysis with Pandas library
  • The most famous course on Data Analysis on Udemy till now
  • An in-depth explanation of each topic
  • Includes a special section: options and settings in Pandas

Top Review

Fantastic class for someone coming in with no experience in pandas. I was able to utilize what I was learning as I went (along with my best friend google) to solve a business problem at work.

- Philip Higgins

This is the most enrolled and a bestseller course for Data Analysis with Pandas on Udemy. It ties with the previous course in my view except that it is a bit older. The course quality is amazing, so is the instructor. This course is more engaging than the previous one. Instead of adding a bunch of topics to make the course more appealing, the instructor focused more on the best practices of using pandas.

6. pandas Foundations by DataCamp

pandas foundational course by datacamp
A decent introduction to Pandas
  • Rating:  4.8/5
  • Total Number of Students: 180k
  • Number of Courses: 1 (4 chapters)
  • Certificate: Available
  • Level: Beginner, Intermediate
  • Time to Complete: 1 week at 10 hours per week
  • Projects: 1 case study
  • Prerequisites: Python programming
  • Cost: $12/m

What You Will Learn

  • Basics of DataFrame in Pandas including visualization with pandas
  • Statistical exploratory data analysis
  • Basics of Time Series analysis
  • Solving a case study with common data analysis and visualization techniques

Key Pros/ Why You Should Enroll

  • It prepares you for the data analysis with pandas environment so that you can easily dive deep into the topic
  • Teaches all the necessary basics within a very short time including EDA and Time Series
  • The best environment for those who want to learn by doing
  • Before even diving deep into data analysis, you’ll already have solved a case study with data manipulation and visualization

DataCamp has a different approach to Data Analysis. This course builds the foundation and then proceeds to the main skill track listed below. A huge number of practice problems build a strong foundation in the Pandas library. The content quality is the best till now. Best pandas tutorial for beginners who like learning by doing.

7. Data Manipulation with Python [Skill Track] by DataCamp

The best data analysis courses for learning by doing
Best data analysis courses for learning by doing
  • Rating:  4.8/5
  • Total Number of Students: 80k
  • Number of Courses: 4
  • Certificate: Available
  • Level: Beginner, Intermediate
  • Time to Complete: 1 month at 10 hours per week
  • Projects: Available
  • Prerequisites: Python programming
  • Cost: $12/m

What You Will Learn

  • Data analysis from basics to advanced including visualization and working with databases
  • Data manipulation, aggregation, slicing-indexing, and visualizing DataFrames in pandas
  • Combining information from multiple sources, merging data tables, and advanced merging like ordered and time-series data merging
  • Exploratory data analysis with visualization using a project
  • Basics of SQL with Python using SQLAlchemy

Key Pros/ Why You Should Enroll

  • A very well structured skill track and provides high-quality materials
  • The cheat sheets are very helpful as a guideline when you start solving a project
  • A huge number of high-quality practice problems, which is the best thing about DataCamp
  • Talks about how to manage Databases with Python, which is a very common skill of Data Analysts
  • Very efficient video tutorials that teach a lot of methods within a very short time without making it overwhelming

This skill track is one of my favorites from DataCamp. Anyone who loves learning by doing, this is the best choice for you. They provide some cheat sheets that consist of all the methods you may need in different types of problems. In fact, these cheat sheets are very popular. Also, you’ll have lecture slides as PDFs which will be very helpful when you complete the skill track but can’t remember anything. 


You must take this skill track after the previous course. I think this is the best value for money. One thing to keep in mind, don’t rush! The practice problems are mostly self-explanatory, so you may complete them quickly to earn a certificate. Don’t do that! In fact, try to start over all the practice problems once you finish the skill track, without watching the videos again.

8.  Doing Data Science with Python by PluralSight

doing data  science with python
Contains unique topics like Git and Kaggle
  • Rating:  4.6
  • Number of Courses: 1 (9 sections)
  • Certificate: Available
  • Level: Beginner, Intermediate
  • Time to Complete: 1 month at 10 hours per week (Make sure to normalize to 10hrs per week)
  • Video Material Length: 6.5 hours
  • Projects: Available
  • Prerequisites: Python programming
  • Cost: $29/m or $25/m annually

What You Will Learn

  • Extracting data from databases, using APIs, and by web scraping
  • Exploratory data analysis with statistics and distribution theorems
  • Feature engineering in detail
  • Building and evaluating predictive models with a Machine Learning approach
  • Using Git for projects and submitting to Kaggle

Key Pros/ Why You Should Enroll

  • The most practical approach for learning data analysis
  • Covers some unique topics like Git and Kaggle
  • Shows various data extraction methods that you will use in your projects
  • Dives deeper into both Data Analysis and Machine Learning models which is exactly what I wanted
  • The end section shows your way next so that you can keep improving yourself

I liked the data extraction part the most. These are the most common ways you’ll be collecting data. You’ll also be using Git for updating your projects. Similarly, the Machine Learning models for the data analysis part was very detailed. A couple of uniqueness of this course is using Git and Kaggle. So this course should be a good choice for you.

9. Data Analysis with Python by IBM on Coursera

The best data analysis course on Coursera
The best data analysis course on Coursera
  • Rating:  4.7/5 (15k ratings)
  • Total Number of Students: 170k
  • Number of Courses: 1 (7 weeks)
  • Certificate: Available
  • Level: Beginner, Intermediate
  • Time to Complete: 2 weeks at 10 hours per week
  • Projects: 1 project, 5 assessments
  • Prerequisites: Python programming
  • Cost: Free (Audit) or $39/month or $33/month annually

What You Will Learn

  • Importing and exporting data from and to files and databases
  • Data wrangling including pre-processing, dealing with missing data, data formatting, normalization, binning, etc.
  • Exploratory data analysis with statistics
  • Various data analysis model development like linear regression, polynomial regression, ridge regression, prediction, decision making, etc
  • Model evaluation and refinement to tackle common problems

Key Pros/ Why You Should Enroll

  • Offers the most practical environment compared to all the other courses
  • Not only teaches data analysis models but also how to evaluate and refine the models
  • Quizzes within and after each video tutorial, at the end of every week, assessment after each week, and a final project; that’s a lot of practice problems!
  • Peer graded assessments help you to see how others solved a similar problem, hence a broader view on topics
  • The community help to answer your questions, which is very important to know many things that you may not get from any courses. Try to read the top discussions on the community each week

To get the best out of this course, make sure to practice them by yourself as most of the lab problems are self-explanatory. And there are some typos, ignore them. Otherwise, this course offers a lot of practical approaches. Especially, the Model Development week and the Model Evaluation week will be very helpful for you. A little bit of statistics knowledge is recommended.

10. The Ultimate Pandas Bootcamp: Advanced Python Data Analysis by Udemy

A very promising data analysis course by Udemy
A very promising data analysis course by Udemy
  • Rating: 4.6 (150 ratings)
  • Total Number of Students: 20k
  • Number of Courses: 1 (15 section)
  • Certificate: Available
  • Level: Beginner, Intermediate
  • Time to Complete: 2 months at 10 hours per week 
  • Video Material Length: 32 hours
  • Projects: 50+ skill challenges
  • Prerequisites: Python Programming (Optional)
  • Cost: $12

What You Will Learn

  • Basics of Jupyter Notebook, Numpy library, and necessary Python programming
  • Data manipulation with Pandas library A-Z, the same topics as you’ve seen in earlier Udemy courses
  • Regex: A very helpful skill for data scraping and analyzing
  • Common visualization techniques with Matplotlib
  • Some formats of data (JSON, HTML, Excel, etc) and how to handle them 

Key Pros/ Why You Should Enroll

  • Covers a lot of topics. One of the most completed tutorials
  • Around 50+ skill challenges help to learn and implement the topics 
  • Covers some extra topics than others like Regex and Data Formats
  • Prerequisites are also covered and so it will be easy for you to cope up with the course

Top Review

excellent course, very good explanation and walk through the courses and mini-projects.

- Bouredja Amine

This is another very promising course on Data Analysis. The instructions are very detailed and in-depth! Though you might want to watch it at 1.5X speed. The course contains some prerequisites sections on Python programming, numpy library, data visualization with Matplotlib, though very basic, but helpful to continue the course. Worth trying it out.

11. Pandas Essential Training by LinkedIn Learning

A detailed course focused on pandas library
A detailed course focused on pandas library
  • Rating:  4.6/5
  • Total Number of Students: 20k
  • Number of Courses: 1 (12 sections)
  • Certificate: Available
  • Level: Beginner, Intermediate
  • Time to Complete: 1 week at 10 hours per week
  • Video Material Length: 2 hours 14 minutes
  • Projects: 1 project
  • Prerequisites: Python programming
  • Cost: $30 per month or $20 per month annually

What You Will Learn

  • Basics of series and DataFrames of Pandas library
  • Reading CSV files, validation, and basic analysis
  • Plotting the data using pandas and seaborn
  • Details on indexing, groupby, and reshaping data
  • Solving a final project to apply the knowledge

Key Pros/ Why You Should Enroll

  • A quick course with examples of various methods
  • Teaches enough to start working with Data Analysis
  • Good for exploring the data analysis field

This course is kind of the same quality as the numpy course discussed at the top. But with lots of quality and detailed courses on Pandas data analysis, this course couldn’t outperform others like the numpy course. Still, I’m listing it here because it contains enough knowledge to start working with data analysis. If you enroll in both the numpy course and this one, then it will be value for money.

12. Exploratory Data Analysis With Python and Pandas - Guided Project on Coursera

A guided project focused on Exploratory Data analysis (EDA)
A guided project focused on Exploratory Data analysis (EDA)
  • Rating:  4.7 (200 ratings)
  • Total Number of Students: 6k
  • Number of Courses: 1
  • Certificate: Available
  • Level: Beginner, Intermediate
  • Time to Complete: 1 week at 10 hours per week
  • Projects: 1 guided projects
  • Prerequisites: Python programming
  • Cost: $10

What You Will Learn

  • Exploratory data analysis step by step using Pandas, Numpy, Matplotlib, and Seaborn
  • Basic data exploration
  • Univariate and Bivariate analysis
  • Dealing with duplicate and missing data, a very common scenario in Data Analysis
  • Correlation analysis of numerical variables

Key Pros/ Why You Should Enroll

  • It’s kind of one on one project
  • See how a data Scientist solves an exploratory data analysis problem
  • Working on a cloud computer gives a real-life experience

Top Review

Simple yet very organized, and elegant Data Analysis project. I really liked it!

- Salih K

Guided project is a relatively new topic on Coursera. It’s a project focusing on only one major topic, and shows how exactly you need to solve that problem. On your browser, there will be a split-screen. In one section, you will write and run your code, on the other section, the instructor will show you the steps. Note that the instructions are pre-recorded video, not live.

The best thing about guided projects is that you work in exactly the same environment as the instructor. And the project is focused on one topic. This one is a good practice project once you’ve taken any of the detailed courses listed above.

13.  Complete Python NumPy Tutorial by Keith Galli

The best numpy tutorial on YouTube is by Keith Galli
The best numpy tutorial on YouTube
  • Rating:  4.7/5
  • Level: Beginner
  • Time to Complete: <1 week at 10 hours per week 
  • Video Material Length: 1 hour
  • Prerequisites: Python programming
  • Cost: Free

Keith Galli is relatively a new YouTuber and I have been following him since his <10k subs. He created some valuable tutorials. I have some pretty good feelings about this channel!

This 1-hour tutorial contains the numpy basics with some engaging examples. In fact, it has been uploaded to FreeCodeCamp for the quality he created! The best YouTube tutorial for those who want to explore the numpy library.

14.  Pandas Tutorials by Corey Schafer

The most detailed free pandas tutorial
The most detailed free pandas tutorial
  • Rating:  4.8/5
  • Level: Beginner
  • Time to Complete: 2 weeks at 10 hours per week 
  • Video Material Length: 11 tutorials, each around 30 minute
  • Prerequisites: Python programming, Numpy
  • Cost: Free

Corey Schafer, a very famous Python Instructor on YouTube, created this amazing detailed tutorial on Data Analysis with Pandas tutorial series. If only the Pandas section is taken under consideration, this tutorial playlist might be one of the best 5 courses of this article. The only downside is the lack of practice problems or projects, which is common for all YouTube tutorials.

15. Python SciPy Tutorial For Beginners by Edureka

the only SciPy tutorial worth listing here
Python SciPy tutorial
  • Rating:  4.5/5
  • Level: Beginner
  • Time to Complete: 1 day
  • Video Material Length: 20 minutes
  • Prerequisites: Python programming, Numpy
  • Cost: Free

This is the only course or tutorial I could find that focuses only on the SciPy library and worth listing here. It’s just the basics of the SciPy library. So after completing this tutorial, you should start reading the official documentation of the SciPy library.

There are very few tutorials on SciPy, and none of them is as detailed as I want. You may keep an eye on my programming website Machine Learning Wiki, where I will be writing about SciPy soon.

16.  Data Analysis with Python by FreeCodeCamp

The best free data analysis course online for beginners
The best free data analysis course
  • Rating:  4.7
  • Level: Beginner
  • Time to Complete: 1 month at 10 hours per week
  • Video Material Length: 4.5 hours
  • Projects: Jupyter notebooks available
  • Prerequisites: Python programming
  • Cost: Free

FreeCodeCamp brings premium courses for free for everyone to use. This course briefly contains almost all the topics of Data Analysis. So this is the best tutorial for exploring the field! Make sure to use the jupyter notebooks to get the best out of this tutorial.

Conclusion and Special Recommendation

As I’ve listed the best 16 online courses for Data Analysis, and each of them is better than the others, it might be confusing for you to choose where to spend your valuable time. Here are some suggestions from my experience assuming you’re a complete beginner in Data Analysis:

If you’ve any better suggestions for Data Analysis courses than mine, feel free to contact me and I’ll update the list after reviewing.


Related Course Reviews

FAQ

Which is the best data analysis course on Coursera?

By far, the best data analysis course on Coursera is Data Analysis with Python by IBM. It does not only teach data analysis models but also how to evaluate and refine the models

Which is the best free data analysis course for beginners online?

Data Analysis with Python by FreeCodeCamp on YouTube is the best free Data Analysis course. It briefly contains almost all the topics you need to learn. Best for those who want to explore the field.

What are the best data analysis certification courses?

Data Manipulation with Python Skill Track by DataCamp contains the most completed and quality courses for Data Analysis. Make sure to start with the pandas Foundations course. Although I prefer taking separate course on each major topic.