Why Data Analytics?

“Meanwhile, e-commerce platforms Lazada and Shopee are hiring for roles in data analytics, business development and product development amid the rise of online shopping.”
– The Straits Times, 7 June 2020

Even our tech giants are also hiring talents in data analytics, it goes to show how important these roles are and the demand for such talents in the coming future.

Over 5,000 jobs in the pipeline for digital sector, jobs are in fields like Data Analytics.
– EDB, 5 June 2020

Explore this growing Data Analytics industry through our Data Analytics course taught by industry experts.

Supported By:

TeSA Logo

Data Analytics Course
Administered by the Infocomm Media Development Authority (IMDA), the CITREP+ funding support is eligible for Singapore Citizens and Permanent Residents. Valid for courses commencing from 1 April 2019. Terms and conditions apply. Please visit www.imtalent.sg/citrep for full details.



  • Course will span across 7 lessons, each lesson will be 3 hours
  • Consist of 3 hours of assignments & capstone project
  • No prior programming/technical background is required

Course Fees

Course fees will be S$2500 before funding support.

Funding Support

Eligible Singaporeans/PRs can apply for funding support up to 90% (T&C applies). ONLY Eligible Singaporeans who fits the criteria as a Student/Full-Time NSF/Just ORD can apply for funding support up to 100% (T&C applies). For more info, click here!

Course Schedule

Data Analytics Course – December 2020 Bootcamp: (Live Webinar)

  • Dec Week 1: 7, 8, 9, 10, 11, 12, 13 Dec
  • Dec Week 2: 14, 15, 16, 17, 18, 19, 20 Dec
  • Pick either Week 1 or Week 2’s bootcamp
  • 9AM – 12PM or 12:15PM – 3:15PM or 3:30PM – 6:30PM or 7PM – 10PM
  • You can pick one of the time slots above
  • Kindly note that you have to commit to the time slot chosen for the entire bootcamp

Course Outline

Learning Objectives:

  • Basic programming in Python
  • Learn about Databases


  • Python Data Types
  • Python Data Structures
  • Python Fundamental Concepts
  • Pandas Introduction
  • Why Databases
  • Types of Databases

Learning Objectives:

  • Basic programming in SQL
  • Use SQL to mine data and create projections from data in SQL
  • Work with Databases to collect and provide projection using SQL


  • Databases
  • SQL Syntax and Statements
  • Working with Databases

Learning Objectives:

  • Applied Statistics
  • Manipulate data using Numpy
  • Develop new or modify existing algorithms using Numpy
  • Able to diagnose unintended outcomes produced by analytical models
  • Able to diagnose and clean data to produce better outcomes


  • Numpy
  • Statistics
  • Combinatorics
  • Exploratory Data Analysis

Learning Objectives:

  • Derive insights using visualization
  • Evaluate and use prospective analytics use and platforms for their functional capabilities and ability to meet requirements of the analytic environment
  • Facilitate changes to statistical models to optimise performance and yield intended outcomes
  • Uncover underlying relationships among different variables such as correlation and covariance
  • Learn features, pros and cons of various statistical approaches, algorithms, tools and applicability of various data models


  • Exploratory Data Analysis 2
  • Scikit-Learn library
  • Bootstrapping
  • Group project and further EDA

Learning Objectives:

  • Develop new algorithms and leverage on machine learning to isolate trends and optimize data-driven decision making
  • Develop and apply regression models, including linear, multiple and other machine learning models in Python
  • Diagnose unintended outcomes produced by analytical models
  • Conduct statistical modelling of data to derive patterns / solutions
  • Perform coding and configuration of software agents or programs based on a selected model or algorithm


  • Supervised Learning
  • Unsupervised Learning
  • Machine Learning Concepts
  • Model Evaluation

Learning Objectives:

  • Develop dashboards in Tableau
  • Able to produce and provide insights from Data in a meaningful manner


  • Types of Dashboards
  • Dashboard providers
  • Analyzing dashboard & insight solutions
  • Documentation, Planning & Design
  • Dashboard Metrics
  • Tableau
  • Data Manipulation
  • Vizzes & Charts
  • Dashboard Creation & Formatting
  • Dashboard Publishing

Learning Objectives:

  • Tableau Dashboard Presentation


  • Capstone Project Presentation
  • Capstone Project Review & Feedbacks

As Seen On

Course Instructors

Shu Min
AI Engineering Analyst

Take Your First Step Today

Apply Now

Kick-start Your Career in Data Analytics!

Learn the ins and outs of data analytics in Singapore with data analytics experts! Don’t get left out with different trends and practices that veteran analyst have been using. Choose to learn with Smartcademy today.

Emerging Industry
Demand for Data Analyst is booming right now.
High Salary
Salary can go up to S$120k for a mid-level Data Analyst.
Future Prospects
Data is the new oil.

According to EDB, some 50,000 ICT jobs are expected to be created in Singapore in the next few years. Michael Page also released that demand for technology jobs in Singapore rose by over 20% in the past 12 months.

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