Singapore University of Social Sciences

Python for Data Analytics

Python for Data Analytics (ANL252)

Applications Open: 01 May 2024

Applications Close: 15 June 2024

Next Available Intake: July 2024

Course Types: Modular Undergraduate Course

Language: English

Duration: 6 months

Fees: $1391.78 View More Details on Fees

Area of Interest: Business Administration

Schemes: Alumni Continuing Education (ACE)

Funding: To be confirmed

School/Department: School of Business


ANL252 Python for Data Analytics, as part of the Business Analytics programme, is designed to equip Business Analytics students with the skills and knowledge to use the Python programming language as a tool for data analytics tasks. At the end of this course, students will be competent in writing Python codes to manage and manipulate data, and performing visualisation and data analytics techniques using existing, accessible Python libraries. Since this course is designed to help students with little prior exposure to programming, it will focus on breadth rather than depth.

Level: 2
Credit Units: 5
Presentation Pattern: EVERY REGULAR SEMESTER


  • Introduction to Python
  • Variable input and output
  • Conditional statements and loops
  • User-defined functions and libraries
  • Array management using numpy
  • Plotting graphs using matlibplot
  • Importing, merging and subsetting datasets using pandas
  • Editing values in a dataset
  • Introduction to data mining library sklearn
  • Applying decision trees and clustering using sklearn
  • Introduction to SQL
  • Basic SQL in Python for querying data from database using sqlite

Learning Outcome

  • Discuss the various aspects of data analysis using Python programming.
  • Apply Python programming for data manipulation.
  • Explain the results from analysis or processing of data
  • Design Python programmes for performing data analytics.
  • Use Python programming language to develop a program with sound logic.
  • Prepare data for analysis using Python programming.
  • Analyse data using appropriate tools and techniques with Python programming.
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