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Python Basics for Data Science
About this courseSkip About this course
Please Note: Learners who successfully complete this IBM course can earn a skill badge —a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!
Kickstart your learning of Python for data science, as well as programming in general with this introduction to Python course. This beginner-friendly Python course will quickly take you from zero to programming in Python in a matter of hours and give you a taste of how to start working with data in Python. ~~~~
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 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 will receive free access to Watson Studio. Start now and take advantage of this platform and learn the basics of programming, machine learning, and data visualization with this introductory course.
At a glance
- Video Transcript: English
- Associated programs:
What you'll learnSkip What you'll learn
The objectives of this course is to get you started with Python as the programming language and give you a taste of how to start working with data in Python.
In this course you will learn about:
- What Python is and why it is useful
- The application of Python to Data Science
- How to define variables in Python
- Sets and conditional statements in Python
- The purpose of having functions in Python
- How to operate on files to read and write data in Python
- How to use pandas, a must have package for anyone attempting data analysis in Python.
Module 1 - Python Basics
Your first program
Expressions and Variables
Module 2 - Python Data Structures
Lists and Tuples
Module 3 - Python Programming Fundamentals
Conditions and Branching
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
Module 5 - Working with Numpy Arrays
Numpy 1d Arrays
Numpy 2d Arrays