Python Basics for Data Science (edX)

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.

This course is part of the following programs:

- Full Stack Application Development MicroBachelors Program

- Data Engineering Fundamentals Professional Certificate

- Applied AI Professional Certificate

- Python Data Science Professional Certificate

- IBM Data Science Professional Certificate

- Data Analyst Professional Certificate

- Data Engineering Professional Certificate

- DevOps and Software Engineering Professional Certificate

- Full Stack Developer Professional Certificate

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.

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

Module 5 - Working with Numpy Arrays

- Numpy 1d Arrays

- Numpy 2d Arrays