5 Free Courses to Master Python for Data Science ( 2024)

Want to learn Python to kickstart your career in data? Here are five free courses to help you master Python for data science.

Studying Python can be very beneficial if you want to transition into a data-related career. There is a lot to learn, though, from machine learning and data analysis to mastering coding interviews and the fundamentals of Python programming. How do you locate the best sources to acquire them all?

We have put together a list of courses that will assist you in mastering Python for data science. These courses are suitable for both novice and seasoned Python users who want to brush up on their knowledge. You can learn the following through the recommended courses:

• Basics of Python
• Python data science libraries 
• Data analysis and machine learning with Python
• Data structures and algorithms with Python

Let’s get started.

1. Python for Beginners 

Gain familiarity with the fundamentals of Python programming by enrolling in Mosh’s Python for Beginners course. 

In about an hour, you can get up in running with the following basics:

• Variables 
• Receiving input 
• Type conversions 
• Strings 
• Operators and operator precedence 
• If statements 
• While and for loops 
• Lists and tuples

Link: Python for Beginners

2. Intermediate Python Programming 

Having mastered the fundamentals, you are ready to enroll in this Intermediate Python Programming course. The discussion of the different built-in data structures in Python opens this course. And proceeds to more advanced features of the language.

The topics covered in this course include:

• Python’s built-in data structures 
• Collections 
• Itertools 
• Lambda functions 
• Exceptions and errors 
• Logging 
• Working with JSON 
• Random number generation 
• Decorators 
• Generators 
• Multithreading and multiprocessing 
• Function arguments 
• Shallow vs. deep copy 
• Context managers

Link: Intermediate Python Programming

3. Data Analysis with Python

You can study about the different Python data science libraries after you have a firm understanding of the language. 

You can become proficient in all the required Python data science libraries by earning the freeCodeCamp certification in Data Analysis with Python.

• NumPy
• Pandas
• Matplotlib
• Seaborn

A few data analysis projects will also be built for you to work on. which you need to finish in order to get certified in Data Analysis with Python.

Link: Data Analysis with Python Certification

4. Machine Learning with Python and Scikit-Learn

At this point, you ought to feel at ease using Python data science libraries and writing Python programs. And you can now start exploring machine learning.

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You can learn about the theory (how machine learning algorithms operate) and the application of machine learning algorithms with sci-kit-learn by using Python and machine learning. Learn how to design and organize machine learning projects as well as create and implement machine learning applications in this course.

Here’s an overview of the topics covered: 

• Linear regression and gradient descent 
• Logistic regression for classification 
• Decision trees and random forests 
• How to approach machine learning projects 
• Gradient boosting machines with XGBoost
• Machine learning project from scratch 
• Deploying a machine learning project with class

Link: Machine Learning with Python and Scikit-Learn

5. Data Structures and Algorithms in Python

You must pass the coding interviews in the data science interview process in order to move on to the next round. You should first have a solid understanding of data structures in algorithms in order to overcome them and improve the effectiveness of your coding practice sessions.

This free course, Data Structures and Algorithms in Python, will teach you the fundamentals of data structures and algorithms with an emphasis on Python.

Just take a structures this data structures in algorithm scores the following this Data Structures and Algorithm Sports will help you learn the following topics 

• Binary search, linked lists, and complexity 
• Binary search trees, traversal, and recursion 
• Hash tables and Python dictionaries
• Sorting algorithms, divide and conquer 
• Recursion and dynamic programming 
• Graph algorithms 
• Python interview questions, tips, and advice

Link: Data Structures and Algorithms in Python

Wrapping Up of Master Python for Data Science

I hope these courses prove to be useful to you. A comprehensive list of courses that will help you become proficient in Python for data science has been compiled by us. 

If you remember, we have taken courses covering everything from the fundamentals of Python programming to data analysis and machine learning. To help you get ready for coding interviews, we have also included a course that will teach you the fundamentals of data structures in algorithms. Happy learning and coding!