Basic Python for Data Science

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Course Objectives

Upon completion of this course, users are expected to understand basic programming syntax and operators in python and have some fundamental ideas on how to use Python for data manipulation and data exploratory. Apart from that, users are able to use Python to perform a basic end to end data science process using sample data sets. This course will help students on starting their data science journey by using Python.


This three days course focuses on getting users to get familiar with basic Python knowledge for data science. The course will cover basic Python programming syntax and operators which required in data science operation and provide hand-on exercises to enhance the understanding of the discussed topics.

Target Audience

This course is suitable for those who wish to learn Python for data science.

Training Outline

Introduction and set up
  • Brief overview of data science
  • Introduction to Python
  • Set up and Installation
Python Variables and Types
  • Variables Assignment
  • Number
  • String
  • List
  • Tuples
  • Dictionary
  • Set
Condition and Flow
  • Boolean Expression
  • For loop
  • While loop
  • Break
  • Continue
  • Introduction to function in Python
  • How declare a user-defined function
  • How to call and access a user-defined function
  • Return Statement in function
  • Introduction to Lambda function
Python modules and packages
  • How to install Python modules and packages
  • Overview of common Python modules and packages for data science
  • Introduction to Pandas Package which used for data manipulation and data exploratory:
    • How to read in excel of csv file
    • Concept of data frame
    • Basic operation in Pandas for data manipulation and exploratory
  • Introduction to Sklearn Package which used for data science and machine learning.
Use sample datasets to perform basic end-to end data science process
  • Use sample datasets to demo basic data manipulation and exploration using Python Pandas package.
  • The data manipulation and exploration operations included select and delete attributes,
    select and delete rows etc.
  • Prepare train and test data to build a simple machine learning algorithm.
  • Demo how to build and evaluate machine learning algorithm using Python Sklearn package.


Basic knowledge of programming is preferable.