10 Best Python Data Science Courses Online [2025]

Do you want to be the one who does a fancy job in the 21st century? Become a data scientist. The data science job market is on the rise due to daily technological advancement. With over 70,000+ job openings for data scientists/analysts, you're in good hands if you're thinking about becoming a data scientist. Back in 2012 when HBR hailed Data Scientist as the sexiest job of the 21st Century, there were hardly any degrees, online courses, or even boot camps but now the coin has flipped. Now you can go for sought-after courses that will also teach you Python and Data Science so that you can have different skills to scale on. 

In this article, we'll list the 10 best Python data sciences courses in 2025. Before that, let's check why you must learn Python for Data Science.

What's the Use of Python in Data Science?

Python is a popular programming language in the field of data science due to its versatility and ease of use. It has a large and active community of users and developers, which means that there is a wealth of resources and libraries available for data scientists to use. 

One of the key benefits of using Python with Data Science is its strong support for numerical and scientific computing. This makes it an ideal language for working with data, whether it is in the form of structured datasets or unstructured text. Python also has a range of powerful libraries, such as NumPy and Pandas, which provide a wide range of tools for data manipulation, analysis, and visualization.

In addition, Python is a high-level language, which means that it is easy to read and write, making it accessible to a wide range of users. According to Statista, Python was the third most in-demand language by recruiters in 2022. Toptal’s Python hiring guide outlines what recruiters look for in a great Python developer. In addition, the official ranking for programming languages, the Popularity of Programming Language Index (PYPL), reinforces Python as the most popular programming language. This puts it above more familiar programming languages like Java. 

Overall, it is safe to say that learning Python and data science can be a valuable investment for those looking to advance their careers. Python is a highly sought-after skill in the job market, and being proficient in Python can open up a wide range of career opportunities in data science and related fields.

List of Best Python Data Science Courses

Let's get started with the list of the top Data Science with Python courses:

1. Complete Machine Learning & Data Science Program (IBM Certification)

If you’re looking for the best recommended Data Science with Python course, GeeksforGeeks got the exact course combo for you. This course, offered by GFG, is one of the most recommended Data Science courses which can provide you with a 360-degree learning experience that will help you achieve your dream of becoming a data scientist in no time. 

With the help of these two courses, you can start your preparation for becoming a data scientist. This 6-month live Data Science course is perfect for tech enthusiasts, students, and professionals alike who are eager to gain hands-on experience in the data science field. The complete Data Science course covers a wide array of topics, starting with Python programming basics and essential data science libraries like Numpy and Pandas. 

Not only you’ll get 24x7 doubt assistance for 6 months with the course but also a lifetime validity. So that you can come back whenever you want to oil your Data Science knowledge in the future. Register for the Complete Machine Learning & Data Science Program on GeeksforGeeks at a pocket-friendly fee and join the league of world-best data scientists at top companies like Accenture, Microsoft, IBM, Oracle, Amazon, Google, etc. 

• Course Link: Complete Machine Learning & Data Science Program
• Pre-requisite: Prior knowledge of Python programming language
• Duration: 26 Weeks
• Language:  English
• Level: Beginner to Intermediate
• Price: Paid (pocket-friendly)
• Certification: Available upon completion

2. IBM Data Science Professional Certificate (Coursera)

Looking to learn Data Science but with Python programming? You can check out IBM’s Data Science Professional Certification course through Coursera. The program will teach you the most up-to-date job-ready technologies and skills, such as open-source tools and libraries, Python, databases, SQL, data visualization, data analysis, statistical analysis, predictive modeling, and machine learning techniques. You'll learn data science by practically doing it on the IBM Cloud using actual data science tools and real-world data sets.

After completing this program, you will have a portfolio of data science projects that will give you the confidence to pursue an interesting career in data science.

What you will learn about:

1. Learn about data science, the various activities of a data scientist’s job, and the methodology to think and work like a data scientist  
2. Develop hands-on skills using the tools, languages, and libraries used by professional data scientists  
3. Import and clean data sets, analyze and visualize data, and build and evaluate machine learning models and pipelines using Python 
4. Apply various data science skills, techniques, and tools to complete a project using a real-world data set and publish a report for stakeholders

• Pre-requisite: No prior knowledge of computer science or programming languages required
• Duration: 4 Months (under 10 hours of study a week)
• Language:  English
• Level: Beginner to Intermediate
• Price: Paid 
• Certification: Available upon completion (+ Digital badge from IBM)

3. Applied Data Science with Python - University of Michigan (Coursera)

Get yourself acquainted with Data Science with Python with the help of this Applied Data Science with Python course offered by the University of Michigan through Coursera. This skill-based specialization will introduce you to Data Science fundamentals. You need to have basic Python knowledge to start this specialization program. With this program, you will be able to apply statistics, machine learning, information visualization, text analysis, and social network analysis techniques through popular Python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networks to gain insight into your data.

What you’ll learn from this 5-course specialization - 

1. Learn the basics of the Python programming environment, including fundamental Python programming techniques such as lambdas, reading and manipulating CSV files, and the NumPy library.
2. How to apply the plotting, charting, and data representation in Python.
3. Develop knowledge of how to improve data analysis strategies with applied machine learning methods.
4. How Python helps to handle text mining and text manipulation using the Nltk framework.
5. Grasp the understanding of how the Networkx library is used for social network analysis and explore the connectivity of networks.

• Pre-requisite:  Prior knowledge of Python or Programming languages 
• Duration: 4 Months (Suggested pace of 10 hours/week)
• Language:  English
• Level: Intermediate
• Price: Paid
• Certification: Available upon completion

4. Master Python for Data Science (Linkedin Learning)

Become a proficient data scientist by mastering Python with the help of this course - Master Python for Data Science offered by Linkedin Learning. This 5-set course consists of Python fundamental courses that will help you learn how to use Python for data science tasks. From cleaning and manipulating data to building and evaluating machine learning models, you'll be equipped with the skills you need to succeed in the field.

The course instructors will guide you through interactive lessons and hands-on exercises, ensuring that you can apply your newfound knowledge to real-world situations. Plus, with a certificate of completion upon finishing the course, you can showcase your skills to potential employers and advance your career.

What you’ll learn about:

1. How to address business problems using Python tools and strategies.
2. How to use Python 3 to construct scripts, and modules, and integrate databases.
3. How to clean, convert, analyze, and visualize data.
4. Make predictions and automate everyday operations using machine learning approaches.
5. How to examine data sets using Python libraries such as Numpy and Pandas.
6. How Python can be used to explore data, consume data, and display data.
7. Create accurate and compelling data visualization dashboards.

• Pre-requisite: No Prior knowledge of Python language
• Duration: 10 Hours
• Language:  English
• Level: Intermediate
• Price: Paid
• Certification: Available upon completion

5. Data Scientist with Python (DataCamp)

Datacamp’s Data Scientist with Python is the next best Data Science with Python course on our list. This course teaches you how to use Python to import, clean, manipulate, and visualize data, which are important skills for anyone interested in a career in data science or research. 

The course starts with the fundamentals of Python for data science and includes interactive tasks to put your knowledge to the test. You will learn how to utilize popular Python data science libraries such as pandas, NumPy, Seaborn, Matplotlib, and more. You will work with real-world datasets to understand statistical and machine-learning techniques, such as hypothesis testing and developing prediction models, as you go. You will also learn about supervised learning with scikit-learn and apply your knowledge to diverse projects. By finishing this course, you will obtain the skills and information required to become a competent Python data scientist. This Datacamp course consists of 25 courses.

Hugo Bowne, Datacamp's Creator and Data Scientist, designed this course to help you develop your understanding of Data Science and obtain a competitive advantage in the IT business. This course will help you to grasp Python, which is a popular data science toolbox because of its interactive scripts for doing analysis. It will teach you data analysis abilities as well as how to become acquainted with fundamental Python ideas.

What you’ll learn from 25-set courses:

1. Learn how to use data types and variables in Python programs.
2. How to utilize lists to store, clean, and alter data with techniques such as slicing.
3. Understand how to work with big amounts of data effectively.
4. Use functions, loops, packages, and libraries to make the code more useful.
5. Learn how great Python developers may decrease the amount of code required to solve issues.

• Pre-requisite: Prior knowledge of Python and SQL
• Duration: 90 hours
• Language: English
• Level: Beginners to Intermediate
• Price: Paid
• Certification: Available upon completion

6. Python for Data Science - UC San Diego (edX)

If you want to know what tools to use to solve complex data science problems, then this course is the answer to all your questions. UC San Diego offers Python for Data Science through edX. This course will expose you to a set of powerful, open-source tools required for data analysis and data science. You will specifically learn how to use Python, Jupyter Notebooks, Pandas, Numpy, Matplotlib, and many other available tools. All of these techniques will be taught to you in the context of solving data science challenges.

What you’ll learn about:

1. How to find answers within large datasets by using Python tools to import data
2. How to use Python and Jupyter Notebooks
3. How to manipulate and analyze uncurated datasets
4. Basic statistical analysis and machine learning methods
5. How to effectively visualize results

• Pre-requisite: Prior experience with any programming language (Java, C, Pascal, Fortran, C++, Python, PHP, etc.) is expected. This includes a high school, or undergraduate equivalent, to an introduction to computer science course. Learners should be comfortable with loops if/else, and variables.
• Duration: 10 weeks (8 - 10 hours per week)
• Language: English
• Level: Advanced
• Price: Paid if you take a verified track, Free if you take an audit track but no certificate and a limited period
• Certification: Available (with verified track option)

7. Python Basics for Data Science (edX)

Looking for a beginners Python course that will lay a foundation for your future Data Science career? You can consider taking this edX course - Python Basics for Data Science offered by IBM. This beginner-friendly course will introduce you to Python language in a matter of hours and will be able to write your first set of Python scripts too. IBM also lets you create your own data science projects and collaborate with other data scientists using IBM Watson Studio. When you sign up for this course, you will receive free access to Watson Studio. With this introductory course, you can learn the basics of programming, machine learning, and data visualization.

What you will learn about:

1. What Python is and why it is useful
2. The Application of Python to Data Science
3. How to define variables in Python
4. Sets and conditional statements in Python
5. The purpose of having functions in Python
6. How to operate on files to read and write data in Python
7. How to use Pandas, is a must-have package for anyone attempting data analysis in Python

• Pre-requisite: Basic Maths
• Duration: 3 Weeks ( 4 - 10 hours per week)
• Language: English
• Level: Beginners 
• Price: Paid if you take a verified track, Free if you take an audit track but no certificate and a limited period
• Certification: Available (with verified track option)

8. Python for Data Science and Machine Learning Bootcamp (Udemy)

If you’re like thousands of other students who want to join a data science and machine learning boot camp to amp up their learning but can’t find a proper resource then this boot camp course is for you. Jump into the Data Science course with Udemy’s Python for Data Science and Machine Learning Bootcamp course. Other boot camps are usually too costly, but this course is not only pocket-friendly but also covers over 100 HD video lectures and detailed code notebooks for every lecture. 

The topics you’ll learn in this course are Programming with Python, NumPy with Python, Using pandas Data Frames to solve complex tasks, Using pandas to handle Excel Files, Web scraping with Python, Connect Python to SQL, Using matplotlib and seaborn for data visualizations, Use Plotly for interactive visualizations, Machine Learning with SciKit Learn, including Linear Regression, K Nearest Neighbors, K Means Clustering, Decision Trees, Random Forests, Natural Language Processing, Neural Nets, and Deep Learning, Support Vector Machines and much, much more!

What you’ll learn about:

1. Use Python for Data Science and Machine Learning
2. Use Spark for Big Data Analysis
3. Implement Machine Learning Algorithms
4. Learn to use NumPy for Numerical Data
5. Learn to use Pandas for Data Analysis
6. Learn to use Matplotlib for Python Plotting
7. Learn to use Seaborn for statistical plots
8. Use Plotly for interactive dynamic visualizations

• Pre-requisite: Prior programming experience required
• Duration: 25 Hours
• Language: English
• Level: Intermediate
• Price: Paid 
• Certification: Available upon completion

 9. Complete Data Science Training with Python for Data Analysis (Udemy)

If you’re looking for a complete guide on Data Science with Python, Udemy has the right course for you. The Complete Data Science Training with Python for Data Analysis is a full 12-Hour Python data science boot camp that will help you learn Statistical Modelling, Data Visualization, Machine Learning & Basic Deep Learning In Python. It explains how to store, mine, clean, and manipulate data using Python and its packages. To solve business challenges, Python-based data science methods are applied to real-life data.

This course will teach you advanced data science approaches as well as how to code using Python-based Jupyter Notebooks. It will teach you how to execute various statistical data analyses and data visualization for data modeling. Students will have a thorough grasp of data science methodologies as well as the best method for interpreting data.

What you’ll learn about:

1. Python data analysis using Anaconda. You’ll get to work within the iPython/Jupyter environment, a powerful framework for data science analysis.
2. Using data science packages like Numpy, Pandas, Scikit, and Matplotlib
3. Data Analysis Techniques and being able to read data from various sources and clean it
4. Performing data exploratory and pre-processing tasks in Python such as Tabulation, Pivoting, & Data Summarizing Become Skilled In Working With Real-World Data Collected From Various Sources
5. Carry out data visualization and understand which techniques to use while doing the most common statistical data analysis techniques in Python, such as T-tests and linear regression
6. Learn the Difference Between Machine Learning and Statistical Data Analysis
7. Apply Various Unsupervised Learning Techniques to Real-World Data
8. On real-world data, apply Supervised Learning techniques (both classification and regression)
9. Examine Machine Learning Model Accuracy and Generality
10. Create Simple Neural Networks and Deep Learning Algorithms
11. Use the H2o Framework to Implement Deep Neural Networks

• Pre-requisite: No prior Python or statistics or ML knowledge required
• Duration: 13 Hours
• Language: English
• Level: Beginners to Intermediate
• Price: Paid 
• Certification: Available upon completion 

10. Python A-Z™: Python For Data Science With Real Exercises! (Udemy)

Last but not least in our list of Data Science with Python courses is one of Udemy’s sought-after courses - Python A-Z™: Python For Data Science With Real Exercises. This course is the perfect one to learn A-Z of Python programming for data science and analytics. This Udemy Python for Data Science course will teach you to statistical analysis, data mining, and data visualization principles. It will teach you Python's essential programming ideas at the next level. You understand how to build lists, utilize functions, and tuples in Python to gather, store, and analyze data. Python packages and modules such as Numpy and arrays will be used.

What you’ll learn about: 

1. How to program in Python at a good level
2. How to code in Jupiter Notebooks
3. The core principles of programming
4. How to create variables
5. Learn about integer, float, logical, string, and other types in Python
6. How to create a while() loop and a for() loop in Python
7. How to install packages in Python
8. Understand the Law of Large Numbers
9. How to visualize data in Seaborn
10. How to create histograms, KDE plots, violin plots, and style your charts to perfection 

• Pre-requisite: No prior Python or statistics or ML knowledge required
• Duration: 11 hours
• Language: English
• Level: Beginners to Intermediate
• Price: Paid 
• Certification: Available upon completion

Note: This list is prepared by our internal team after a comprehensive research practice. You can opt for any of the course(s) mentioned in the list (or other than these), based on your own requirements & preferences, to start learning Data Science. Though, irrespective of the course you choose, be consistent and dedicated to the learning process to achieve the targeted goals.

Conclusion

Data science is a rapidly growing field with constantly evolving technologies and tools. This field is expected to continue to have a high demand for professionals in the coming decade, making it a secure career path for data scientists. The abundance of job opportunities and the dynamic nature of the industry are contributing factors to this projection. If you're considering becoming a data scientist who is thorough with data science and Python, you can definitely opt for one of the above courses to advance in your data science career.