Python For Data Science

Dates: To be advised

Duration: 2 Days

Course Overview

In an age where data is ubiquitous, it is critical to be well-versed in tools that will allow us to extract useful insights, decisions and products from the data that we collect. Python, with its wide array of libraries streamlining each part of the data science process, is an essential part of our quantitative toolkit. Building upon a review of basic Python syntax, this course focuses on how we can better work with, and make use of data using Python from cleaning messy datasets, exploring our data by way of visualisations and setting up machine learning models.

Learning Outcomes

At the end of the course, participants will be able to:

1. Use Python for basic data engineering to aggregate, clean and process data from local files, databases, and online
2. Create visualisations with popular python packages
3. Create basic to intermediate analytics models using Python
4. Use the above tools within the context of solving essential data science problems
5. Apply Python tools to import data from various sources, explore them, analyse them, learn from them, visualise them, and share them

Who Should Attend

Business/Data Analysts, Programmers, Executives

Prerequisites

Must be familiar with the Python programming language, or have attended the Introduction to Python training and statistics 101 at a pre-university level. 

Software Application

Anaconda for Windows / MacOS.

Course Conveners

(Click their photos to view their short biographies)

ccccc Danny Poo

Assoc Prof Danny PooAssoc Prof Danny Poo

ddddd Ai Xin

Dr Ai XinDr Ai Xin

ddddd Edmund Low

Dr Edmund LowDr Edmund Low

Additional Information 

Is there a preferred platform and what type of software do I need to install?
You can use Windows or MacOS as we will be using Anaconda. Installation instructions will be provided in the course materials ahead of the class.

Does the course require any technical background? 
Some knowledge of simple programming concepts, e.g. variables, loops, will be preferable. As part of the course will cover the basics of Python, participants without prior knowledge of the programming language can attend as well.

Is there an assessment at the end of the course?
Yes, participant is required to complete a short project using Python.

Course Fees

Singapore Citizens
39 years old or younger
40 years old or older
Singapore PRs
Enhanced Training Support for SMEs
International Participants

Total Nett Programme Fee Payable, Including GST, after additional funding from the various funding schemes

Participants must fulfill at least 75% attendance and pass all assessment components to be eligible for SSG funding.

This course is eligible for Union Training Assistance Programme (UTAP). NTUC members can enjoy up to 50% funding (capped at $250 per year) under UTAP. NTUC members aged 40 and above can enjoy higher funding support up to $500 per individual each year, capped at 50% of unfunded course fees, for courses attended between 1 July 2020 to 31 December 2025. Please click here for more information.

To enquire, email soc-ace@nus.edu.sg

To register, click Register

Course Codes
TSG 2020501975 (Classroom Learning)
TSG-2021006841 (Synchronous e-learning)

Course Fee Breakdown

Singapore Citizens

Singapore Citizens

39 years old or younger

Singapore Citizen

40 years old or older
Singapore PRs
Enhanced Training Support for SMEs
International Participants