Data Analytics Essentials (DAE) with Python

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Online ‘Live’ Session: 9:30am to 5:30pm (SGT / UTC +8) 4 Lessons Click on preferred date to register

Course Information

  • Duration: 4 Day / 32 Hours
  • Certification:Participants will be awarded a Certificate of Competency in Data Analytics Essentials (DAE) upon meeting the requirements and passing the examination.
  • Who Should Attend: Aspiring Data Scientist, Data Analyst, HR Analyst, and Anyone interested in pursuing a career in the areas of Business Analytics / Data Analytics and would like the opportunity to learn in a supportive and encouraging environment.

Course Objective

Data Analytics Essentials (DAE) is a 4-Day program designed to allow participants acquire the essential knowledge on how to use business analytics to make better business or organisational decisions.


It is preferred that participants attend and successfully completed Python Programming Essentials (PPE)


Participants are required to attempt an examination upon completion of course. This exam tests a candidate’s knowledge and skills related to Data Analytics Essentials (DAE) based on the syllabus covered
Module 1 Introduction to Data Analytics
Topics Covered
  • Data Analytics Overview
  • Concepts of Data Analytics
  • Importance and Advantages of Data Analytics
  • Developing / Application of Data Analytics Strategies

Module 2 Different Types of Analytics and Application
Topics Covered
  • Data Analytics Maturity Model
  • Understanding Descriptive, Predictive and Prescriptive Analytics
  • Different Application of analytics method
  • Concepts of Text Analytics and Web Analytics
  • Different Application of Analytics Methods

Module 3 Different Types of Analytics and Application
Topics Covered
  • Data / information architecture
  • ETL Architecture
  • What is Data Warehouse
  • Business intelligence vs Data Analytics
  • Application of Analytics in an Organisation
  • Case Studies

Module 4 Deep Dive into Python Programming for Data Analytics
Topics Covered
  • Introduction to Python Programming
  • Fundamentals of Python Programming for Data Analytics
  • Understanding Python Modules e.g. NumPy, Pandas, Matplotlib

Module 5 Data Mining and Processes for Data Analytics
Topics Covered
  • Fundamentals of Data Mining
  • Objectives of Data Mining
  • Key aspects of Data Mining
  • Concepts of Knowledge Discovery in Databases (KDD)
  • Models in Data Mining
  • Data Mining Model vs Statistical Model
  • Data Mining Processes

Module 6 Data Mining Techniques
Topics Covered
  • Descriptive Analytics: Clustering Models
  • Descriptive Analytics: Association Models
  • Descriptive Analytics: Visualisation
  • Predictive Analytics: Classification Models
  • Predictive Analytics: Regression Models

Module 7 Introduction to Machine Learning
Topics Covered
  • Supervised Learning vs Unsupervised Learning
  • Linear Regression Analysis
  • Logistic Regression Analysis
  • Random Forest Analysis

Data Analytics Essentials (DAE) involves rigorous usage of real-time case studies, hands-on exercises and group discussion