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 Solutions Architect

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

27 Feb 2025 to 28 Feb 2025 (Full Time)

Duration: 2 days

When: Feb - 27, 28

Time : 9.00am - 5.30pm

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's HR L&D or equivalent staff can click here to register through Learning Partner's registration portal.

The HR L&D will need to generate a URL link and send it to the participant to register for the programme under Corporate-Sponsored. The participant must first log in to L3AP using Singpass before clicking on the URL link to complete their registration and declaration. Failure to do so will result in registration under Self-Sponsored.

Please refer to NUS Lifelong Learning Portal (L3AP) guide here.

Step 3

The Learning Partner will inform you whether you have been successful in enrolment.

Data Analytics for IT Professionals