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.

Pre-Requisite

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

Examination

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