Best Courses to Learn Data Science in 2024

If you’re looking to dive into the exciting world of data science, you’ve come to the right place.

We’ve scoured the internet to bring you a curated list of the best courses available to help you learn data science and jumpstart your career. In this post, we’ll introduce you to some of the top online platforms, universities, and learning resources that offer top-notch data science courses.

Whether you’re a beginner looking to get started in data science or an experienced professional looking to upskill, there’s something here for everyone. So, without further ado, let’s get started!

If you see the terms specialization, track, nanodegree, bundle, program, etc. mentioned in this guide, know that they refer to a collection of courses. This guide mostly covers comprehensive programs which generally consist of multiple courses. Different MOOC and ed-tech platforms name them differently but they all refer to a collection of courses. Also, note that all the courses mentioned in this guide are self-paced courses.

Disclaimer: Data Science Parichay is reader supported. When you purchase a course through a link on this site, we may earn a small commission at no additional cost to you. Earned commissions help support this website and its team of writers and designers.

1. Datacamp – Data Scientist with Python

The Data Scientist with Python career track offered by Datacamp contains interactive courses to help you upskill as a Data Scientist with a focus on the Python programming language.

Program Details

This is a comprehensive beginner-friendly track with interactive courses and would be a great fit if you want to learn data science, especially with a focus on the Python programming language and its related tools and libraries for data and predictive analytics. The track consists of –

• 96 hours of content
• 25 courses
• 6 projects

Pros

• Beginner friendly – starts with the basics of Python and builds on it.
• Interactive courses – help you get hands-on learning.
• A good breadth of topics covered – Python, data analytics, data visualization, statistics, and machine learning.

Cons

• The track is Python focussed (which is not necessarily a con if that’s what you’re looking for) and does not cover other useful languages such as SQL, R, etc.

2. Udacity – Data Scientist Nanodegree Program

Unlike other MOOCs that offer MOOCs often in partnership with universities, Udacity focuses almost exclusively on tech-related courses and programs and partners with tech companies instead to build their programs. Their Data Scientist Nanodegree Program offers a great curriculum with a focus on relevant technologies used in the industry to take you from a beginner to an intermediate-level Data Science professional.

Program Details

This is an intermediate-level course that requires prior knowledge (at least at a basic level) of Python, SQL, and statistics. The course covers the following broad topics –

• Programming with Python and SQL (also has a section on Git)
• Probability and Statistics
• Mathematics relevant to data science and machine learning (calculus and linear algebra)
• Data Wrangling
• Data Visualization
• Machine Learning

The course has relevant real-world projects that would look great on a resume.

Pros

• Covers both Python and SQL.
• A dedicated section for the mathematics behind machine learning algorithms.
• Includes courses on Data Engineering and Software Development practices.

Cons

• An intermediate-level course that requires a basic knowledge of Python, SQL, and Statistics.

3. Coursera – IBM Data Science Professional Certificate

The program consists of 9 online courses that will provide you with the latest job-ready tools and skills, including open-source tools and libraries, Python, databases, SQL, data visualization, data analysis, statistical analysis, predictive modeling, and machine learning algorithms. You’ll learn data science through hands-on practice in the IBM Cloud using real data science tools and real-world data sets.

Program Details

This is a beginner-level course that does not require prior experience in data science or programming. Familiarity working with computers, high school math, and communication and presentation skills can be helpful. The following are some of the key course details –

• There are 10 courses in this program. Some of the key courses are – Python for Data Science, SQL and Databases for Data Science, Data Analysis with Python, Data Visualization with Python, and Machine Learning with Python.
• 5 months duration (assuming 4 hours per week of study)
• Includes hands-on lab sessions in the IBM Cloud environment and a capstone project.

Pros

• Beginner friendly – doesn’t require prior programming knowledge.
• Earn college credits upon completing this certificate. Note the credit is eligible for some universities that offer degrees on Coursera. Check the course page for more.

Cons

• Doesn’t have a specific section for statistics.

4. Coursera – Data Science Specialization offered by John Hopkins University

This Specialization covers the concepts and tools you’ll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. Unlike most of the courses mentioned in this guide that teach Data Science with a focus on the Python programming language, this specialization teaches Data Science with a focus on the R programming language.

Now, both R and Python are commonly used in the industry and are just tools to apply data science fundamentals and techniques. Depending on the industry you’re working in, you may have a preference for a specific toolset. For example, R is very commonly used in academia, research organizations, econometrics, etc.

Program Details

This is a beginner-level course. Some programming knowledge (in any language) is helpful. The following are some key course details –

• The specialization includes 10 courses including courses on the R programming language, Statistical Inference, Developing data products with R Shiny, etc.
• 11 months to complete (however, the FAQ mentions that most students complete the course in 3-6 months).
• Includes a hands-on capstone project.

Pros

• Dedicated sections on statistical inference and regression.
• Covers the basics of creating data products with R Shiny.

Cons

• The program is R focused and doesn’t cover Python and SQL (not necessarily a con if you’re looking to learn data science with R).

5. Dataquest – Data Scientist in Python

Gain the Python skills you need to start and grow your career as a data scientist. You’ll learn to create data visualizations, perform web scraping, build machine learning algorithms, and much more. This is a beginner-friendly course that teaches Data Science with a focus on Python. The following are some key program details –

Program Details

• The program includes 36 courses including courses on Command Line, Git, Probability and Statistics, SQL, and advanced topics like Deep Learning and Big Data.
• 8 months duration (assuming 10 hours per week).
• The program includes 28 projects.

Pros

• Interactive lessons.
• Dedicated sections on the Command Line, Deep Learning, and Big Data (analyzing large datasets in Spark).

Cons

• Relatively longer program (this is due to the breadth of the topics covered in the program, we really struggled to find a con for this program).

6. EdX – Professional Certificate in Data Science by Harvard University

This course teaches Data Science with a focus on the R programming language. The HarvardX Data Science program prepares you with the necessary knowledge base and useful skills to tackle real-world data analysis challenges.

Program Details

• The program includes 9 courses including courses on R programming, data wrangling with dplyr, data visualization with ggplot2, linear regression, and machine learning.
• Expected duration of 5-6 months (10 hours per week).
• Includes real-world case studies and a capstone project.

Pros

• Courses come with real-world case studies.
• Beginner-friendly.

Cons

• The program is R-focused.

7. EdX – MicroMasters Program in Data Science by UC San Diego

This program aims to develop a well-rounded understanding of the mathematical and computational tools that form the basis of data science and how to use those tools to make data-driven business recommendations. The program is Python-based.

Program Details

• The program includes 4 courses – Python for Data Science, Probability and Statistics in Data Science with Python, ML Fundamentals, and Big Data Analytics using Spark.
• Expected duration of 10 months (9-11 hours per week).

Pros

• The program focuses on the mathematical and applied side of data science.
• Earn college credits upon completing this certificate. Note the credit is eligible for some universities who have partnered with EdX and the course. Check the course page for more details.

Cons

• A relatively theoretical course with a limited number of projects.

8. Udemy – Python for Data Science and Machine Learning Bootcamp

One of the most popular courses on Udemy for Data Science. This course will guide you to learn how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!

Program Details

• The program includes sections on – Python programming, using Python for data analysis and visualization, ML with scikit-learn including commonly used algorithms, Big Data and Spark with Python, etc.
• 25 hours of on-demand video.

Pros

• Relatively inexpensive.
• Includes a section on big data

Cons

• Covers a good breadth of topics but has limited projects.

How to choose the right course for you?

Data Science is a vast topic in itself and it’s easy to get overwhelmed by the plethora of resources available online. And, we believe that there’s no one best course or program, objectively at least. But, you can choose the right program for you depending upon what your end goal is from a program. We have come up with a simple decision tree to help you pick a program from the list mentioned in this guide.

1. The first question to ask yourself is R or Python. If you have a preference (for example, due to the industry you work or want to work in), pick that. Otherwise, we recommend Python.
2. If you picked Python, you may ask yourself another question – Do you like interactive courses more, or traditional courses are your jam?

We do not rank one course over the other in the resulting buckets of the decision tree, go for the one you feel is the best fit for you.

Kudos on making it to the end of this guide! We hope it was helpful in deciding the right course for you to start your data science journey.

If there’s one thing we hope you take away from this guide is that pick the course that best suits your goals and once you’ve picked the right course for you (even if it’s not in this guide) please follow it through to completion. Having a growth mindset with a focus on learning and completing the tasks in the course will not only help you upskill in technical knowledge but will also make you a better professional ready to take on the world.