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If you are reading this article, you probably want to learn data science and land your first job in data soon. So how do you learn data science?
After improving your basic math skills, you can start learning SQL or a programming language like Python or R. If you learn R, you will be able to perform statistical and data analysis. But Python is more versatile and easier to learn than R.
Here is a list of Python programming courses for beginners that will help you learn the fundamentals and start building projects. Let us begin!
1. Python for beginners – freeCodeCamp
He Python for beginners The course on freeCodeCamp's YouTube channel is a complete Python course for beginners. The course is over 4.5 hours long and will get you up and running with Python fundamentals by coding two simple games: Rock, Paper, Scissors, and Blackjack.
The course begins by exploring the fundamentals such as data types, variables, and operators. It then covers control flow, built-in functions, and data structures. The course also explores advanced concepts such as decorators, object-oriented programming, and functional programming.
This course does not assume any prior experience programming with Python. But it covers enough ground to help you feel confident about starting to build your own projects.
Link: Python for Beginners – Complete Course (Programming Tutorial)
2. Python – Kaggle
If you prefer to work with short, text-based lessons and run code snippets along the way, the Piton The Kaggle course is for you.
In addition to the basics of Python syntax and variables, the course covers the following topics:
- Features
- Booleans and conditionals
- Lisa
- Loops and List Comprehensions
- Strings and dictionaries
- Work with external libraries
Link: Learn Python | kaggle
3. Python Tutorial (with Mini Projects) – freeCodeCamp
In the first course, Python for beginners, you would have coded two simple game projects. He Python Tutorial for Beginners (with Mini Projects) It is a video course with 23 chapters, each of which focuses on a different topic.
Throughout the course, you will also work on several mini-projects. The course starts with the basics such as data types and built-in data structures. But it also covers the following topics:
- Features
- recursion
- Scope and closures
- Command line arguments
- Lambdas and higher order functions
- Object-oriented programming
- Errors and exceptions
- File operations
- Virtual environments
Link: Python Tutorial for Beginners (with Mini Projects)
4. Python Tutorial – W3Schools
He Python Tutorial At W3Schools you have short lessons along with quick practice exercises and examples that you can run in the browser.
The W3Schools Python tutorial covers the following topics:
- Control flow
- Integrated data structures
- Classes and objects
- Inheritance polymorphism
- Work with dates, JSON and RegEx
In addition to Python fundamentals, the Python tutorial also includes lessons on Python's data science libraries: NumPy, pandas, and matplotlib.
Link: Python Tutorial
5. Object-oriented programming with Python
From one or more of the courses so far, you should be familiar with object-oriented programming (OOP) in Python and it's time to learn more. Object-oriented programming with Python is available for free on the freeCodeCamp YouTube channel and is a complete course to learn the fundamentals of object-oriented programming with Python.
This course covers the following:
- Starting with classes
- Builder
- Class vs static methods
- Inheritance
- Getters and setters
- Object-oriented programming principles
Link: Object Oriented Programming with Python: Complete Course for Beginners
Ending
If you are a beginner in data science and looking to learn Python, I hope you found this list of courses helpful. Even while learning Python, make sure you work on interesting projects on the side so you can apply what you learn and also build your project portfolio.
Happy learning and coding!
twitter.com/balawc27″ rel=”noopener”>Bala Priya C. is a developer and technical writer from India. He enjoys working at the intersection of mathematics, programming, data science, and content creation. His areas of interest and expertise include DevOps, data science, and natural language processing. He likes to read, write, code and drink coffee! Currently, he is working to learn and share his knowledge with the developer community by creating tutorials, how-to guides, opinion pieces, and more. Bala also creates engaging resource descriptions and coding tutorials.
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