Python for Data Science

This free Python course provides a beginner-friendly introduction to Python for Data Science. Practice through lab exercises, and you'll be ready to create your first Python scripts on your own!

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About This Python Course

This introduction to Python will kickstart your learning of Python for data science, as well as programming in general. This beginner-friendly Python course will take you from zero to programming in Python in a matter of hours.

Upon its completion, you'll be able to write your own Python scripts and perform basic hands-on data analysis using our Jupyter-based lab environment. If you want to learn Python from scratch, this free course is for you.

You can start creating your own data science projects and collaborating with other data scientists using IBM Watson Studio. When you sign up, you get free access to Watson Studio. Start now and take advantage of this platform.

Course Syllabus

Module 1 - Python Basics

    • Your first program
    • Types
    • Expressions and Variables
    • String Operations

Module 2 - Python Data Structures

    • Lists and Tuples
    • Sets
    • Dictionaries

Module 3 - Python Programming Fundamentals

    • Conditions and Branching
    • Loops
    • Functions
    • Objects and Classes

Module 4 - Working with Data in Python

    • Reading files with open
    • Writing files with open
    • Loading data with Pandas
    • Working with and Saving data with Pandas

General Information

  • This course is free.
  • It is self-paced.
  • It can be taken at any time.
  • It can be audited as many times as you wish.
  • There is only ONE chance to pass the course, but multiple attempts per question

Recommended skills prior to taking this course

  •  Basic Math

Course Staff

Python for Data Science instructor Joseph Santarcangelo, PhD
Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

Other Contributors

The following individual also contributed: James ReeveDaniel Rudnitski , John Gerassimou and Agatha Colangelo