5 Free Courses to Master Python for Data Science

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



5 Free Courses to Master Python for Data Science
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Learning Python is super helpful if you’re looking to switch to a data career. But there is a lot to learn: from the basics of Python programming to data analysis, machine learning, and cracking coding interviews. So how do you find the best resources to learn them all?

To help you, we’ve compiled a list of courses to help you master Python for data science. Whether you are a beginner or an experienced professional looking to refresh your Python skills, these courses are for you. The suggested courses will help you learn the following:

  • 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 

 

The Python for Beginners course from Mosh will help you become familiar with the absolute basics of Python programming. 

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 

 

Now that you know the basics, you can take this Intermediate Python Programming course. This course starts out by discussing the various Python built-in data structures. 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

 

Once you have a good grasp of Python, you can proceed to learn about the various Python data science libraries. 

The Data Analysis with Python certification from freeCodeCamp will help you learn all the necessary Python data science libraries:

  • NumPy
  • Pandas
  • Matplotlib
  • Seaborn

You will also get to build a few data analysis projects. Which you should complete to receive the Data Analysis with Python certification.

Link: Data Analysis with Python Certification

 

4. Machine Learning with Python and Scikit-Learn

 

You should now be comfortable programming with Python and working with Python data science libraries. And you can now start exploring machine learning.

Machine Learning with Python and Scikit-Learn will help you learn about the theory (how machine learning algorithms work) and the implementation of machine learning algorithms with scikit-learn. This course will also learn how to approach and plan machine learning project, build, and deploy machine learning applications.

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

 

In the data science interview process, you should first crack coding interviews to proceed to the next stages. To crack them and to make your coding practice sessions more effective, you should first have a strong foundation in data structures in algorithms.

Data Structures and Algorithms in Python is a free course that’ll help you learn the essential data structures and algorithms—with focus 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

 

Hope you find these courses helpful. We’ve put together a list of courses that are both comprehensive and will help you become proficient in Python for data science. 

If you can recall we had courses that started from the very basics of Python programming up to data analysis and machine learning with Python. We’ve also included a course to help you learn the  foundations of data structures in algorithms—to prepare for coding interviews. Happy learning and coding!
 
 

Bala Priya C is a developer and technical writer from India. She likes working at the intersection of math, programming, data science, and content creation. Her areas of interest and expertise include DevOps, data science, and natural language processing. She enjoys reading, writing, coding, and coffee! Currently, she's working on learning and sharing her knowledge with the developer community by authoring tutorials, how-to guides, opinion pieces, and more.