Introduction to Python for Data Science

  • Course level: Beginner


Python is an open-source, interpreted, high-level language and provides a great approach for object-oriented programming. It is one of the best languages used by data scientists for various data science projects/applications. Python provides great functionality to deal with mathematics, statistics and scientific function. It provides great libraries to deals with data science applications. 

One of the main reasons why Python is widely used in the scientific and research communities is because of its ease of use and simple syntax which makes it easy to adapt for people who do not have an engineering background.

This is an introductory course with Python programming for data analytics and it is designed to give you an understanding of the core fundamentals. We will cover the basics of using Python programming, development environment setup, its programming essentials as well as data manipulation. You’ll be introduced to major data science libraries such as Pandas, Numpy, Maplotlib, Scikit-learn. You’ll also have practise exercises to test your understanding. By the end of this course, you’ll gain more confidence working with data using Python.

What Will I Learn?

  • Set up your Python toolkits and environment to start coding 
  • Understanding the core fundamentals of Python and programming logics
  • Use Python for working with data
  • Understand Python functions and building blocks of programming
  • Gain knowledge and ability to code in Python
  • Leverage the main libraries for data analytics and visualisation

Topics for this course

20 Lessons

Getting Started?

Getting to know what is Python and how it plays a role in the Data Science industry, understand why we use it to work as a whole, and who needs Python as well as Understand about Python Environment, Libraries, and Anaconda Python distribution.
What is Python?
Why Python?
Who uses Python?
Environment set up and Libraries

Introduction to Python Programming?

Introducing Python programming, getting familiar with Python Keywords, Identifiers, Indentation, Comment, Variable, types, and Operators so that you are aware of the available resources and feature offers for python respectively.

Python Essentials?

In this topic, you’ll learn about data types (string, int, floats, boolean), conditional branching (if, elif, else), containers (lists, tuples, dictionaries, sets), and (for loops vs while loops) so you have a core fundamental of Python essentials, especially working with data and its programming logic.

Python Functions?

Learning about the concept and syntax of Function in Python, knowing about function types and arguments and how they can be used, and lastly, understanding what Anonymous function in Python is with its usage.

Python OOPs?

In this topic, you will learn about the concept and syntax of Object-Oriented Programming, knowing how to use producing reusable code with class, object method, inheritance.. etc that you are aware to not write redundancy code in python.

About the instructor

5.00 (2 ratings)

6 Courses

17 students


Material Includes

  • Learning docs
  • Materials
  • Quizzes an Exercises
  • Certificate of Completion


  • Generally, suitable for beginners without prior programming language skills or those who want to learn Python for data science.

Target Audience

  • Any interested learners who want to gain Python skills and knowledge for their Data Science career