Python is often considered to be one of the most powerful, adaptable, and easy-to-learn high-level programming languages for developing websites, operating system components, applications to games and so much more.

Today, companies like Amazon, Intel, and Dell count on Python developers to make their business run and the Python job market is booming!

[ You might also like: 10 Best Udemy Computer Science Courses ]

No matter your level of proficiency, here are three amazing resources to upgrade your Python knowledge and your earning potentials.

1. Python for Absolute Beginners (4 Hrs)

In this basic Python for Absolute Beginners course, you will learn useful programming fundamentals while getting up to momentum with one of the powerful languages in existence.

  • Implement Python debugging strategies.
  • Create, sort, and modify Python lists.
  • Learn Python data types and perfectly use code commenting.
  • Perform arithmetic operations in Python.

2. The Complete Python Pro Bootcamp for 2021 (60 Hrs)

freestar.config.enabled_slots.push({ placementName: “tecmint_incontent”, slotId: “tecmint_incontent” });

In this Complete Python Pro Bootcamp for 2021 course, you will learn how to build 100 projects over 100 days, create desktop applications, develop games like Pong, Blackjack, and Snake, develop fully-fledged websites and applications, and much more.

You will soon come to know why coders at startups like Dropbox depend on Python because it eases the process of developing and iterating upon application is a slice of cake.

  • Working with Python Variables to Manage Data.
  • Understanding data types and manipulate strings.
  • Learn Python loops, functions, and Karel.
  • Python Scripting and Automation.

3. Python for Data Science and Machine Learning Bootcamp (60 Hrs)

In this Python for Data Science and Machine Learning Bootcamp course, you will be presented with a unique combination of projects that will guide you on what machine learning is all about and how you can use Python to develop machine learning projects.

    • Apply different machine learning algorithms.
    • Master Python’s packages and libraries to facilitate computation.
    • Understand classification, regression, and clustering.
    • Execute your own machine learning models.
    • Learn to use Matplotlib for Python Plotting
    • Learn to use Pandas for Data Analysis

You may also like

Leave a Comment