AppM

Data Analytics for IT Professionals

Enquiry
Programme Code D21
Domain
Data Science & AI
Applications Management
Level
Foundation
Learning Partner(s)
NUS SCALE
Duration
2 Days
Format In-person
Rating
Competencies
Data Systems Architecture Data Management & Analytics
Job Roles
Delivery Manager Project Manager (Agile) ICT&SS Professional Digital Service Manager Digital Business Analyst Data Engineer

Overview

Gain a foundation in data analytics. Learn the overview of data and data analytics, data analytics process and project life cycle. Leverage on tools and technology used for data analytics and visualisation as well as machine learning and data visualisation techniques.

Key Takeaways

At the end of this programme, you will be able to:
  • Apply data analytics techniques using tools through hands-on sessions
  • Apply data visualisation techniques using tools through hands-on sessions
  • Gain insights from data using various machine-learning techniques

Who Should Attend

  • Please refer to the job roles section.
  • Targeted at data and IT professionals.

Prerequisites

Knowledge of data management and fundamental statistics.

Programme Structure

The programme is conducted virtually and covers the following topics:

Day 1
  • Big Data and Data Analytics
  • Tools and Technology
  • Data Analytics Process
  • Introduction to Machine Learning – Supervised and Unsupervised Learning
  • Overview - All about Data
    • Data concepts
    • Statistics Primer 
  • Analytics Project Life Cycle (CRISP-DM)
    • What is going with the data in each data analytics phase?
    • Model Development, Deployment, Scoring and Refresh
  • Hands-on Exercise Lab using Orange
  • Supervised Learning Models
    • Data Cleaning Concepts/Techniques
    • Exploratory Data Analysis
    • Data Preparation 
    • Linear Regression 
    • Model Evaluation R2
  • Hands-on Exercise Lab using Orange
  • Logistic Regression (Predicting HDB Prices)
  • Decision Tree, Random Forest
  • Model Evaluation 
  • Confusion Matrix, ROC, AUC


Day 2

  • Visualisation
    • Visualisation Concepts and Principles
    • Selecting the Visualisations
  • Hands-on Exercise Lab using Tableau
    • Creating Visuals and Dashboards
  • Unsupervised Learning Models
  • Clustering Using K-means
    • Concepts and Method
    • Application
  • Hands-on Exercise Lab Using Orange
  • NLP - Text Analytics
    • Concepts and Method
    • Application
      • Text Pre-processing 
      • Visualisation 
      • Stop Words 
      • Clustering 
      • Text Classification 
  • Hands-on Exercise Lab Using Orange

Fees


Full Fee

Full Programme Fee

S$1900

9% GST on Nett Programme Fee

S$171

Total Nett Programme Fee Payable, Incl. GST

S$2071

With effect from 1 Jan 2024


NOTE
Funding is available for this programme. Please visit the Learning Partner's website to find out about the updated programme fee funding breakdown, eligibility, terms and conditions.

 

Upcoming Classes

Class 1
05 Aug 2024 to 06 Aug 2024 (Full Time)
Duration: 2 days
When: Aug - 05, 06
Time : 9.00am - 5.30pm
Class 2
04 Nov 2024 to 05 Nov 2024 (Full Time)
Duration: 2 days
When: Nov - 04, 05
Time : 9.00am - 5.30pm
Class 3
27 Feb 2025 to 28 Feb 2025 (Full Time)
Duration: 2 days
When: Feb - 27, 28
Time : 9.00am - 5.30pm

How To Register


Agency-sponsored

Step 1 Apply through your organisation's training request system.

Step 2 Your organisation's training request system (or relevant HR staff) confirms your organisation's approval for you to take the programme.

Your organisation will send registration information to the academy.

Organisation HR L&D or equivalent staff can click here for details of the registration submission process.


Step 3 GovTech Digital Academy will inform you whether you have been successful in enrolment.