Programme Content
Module 1: Introduction to Data Analytics
Foundations of data analytics
Types of analytics and their applications Business value of data
Module 2: AI/ML, GenAI & Agentic AI Fundamentals
What is AI/ML?
Supervised/unsupervised learning algorithms Generative AI overview
Use cases in analytics
Agentic AI concepts
Module 3: Data Literacy for Decision-Makers
Understanding data types
Data quality
Sources of quality data
Identifying outliers and anomalies Data-driven culture
Module 4: Data Sourcing & Cleaning
Data sources
Data life cycle and ingestion pipelines
Cleaning techniques Data wrangling
Introduction to semantic layers/governed data models
Module 5: Stats Foundations
Histograms
Distributions
Sampling
Probability basics
Inference vs prediction
Linear algebra essentials (vectors, matrices, dot product, eigen intuition)
Module 6: Data Visualisation & Analytics
Foundations of Visualisation
Charts and dashboards
Business storytelling
Power BI/Tableau basics
Interactive dashboards in Power BI and Tableau Using GenAI for automated insights
Module 7: KPI Frameworks & Business Metrics
Defining KPIs
Linking KPIs to strategy Generative AI for KPI insights
Module 8: Forecasting & Trend Analysis
Time series basics
Forecasting models Scenario planning
Module 9: Optimisation & Decision Models
Module 10: Applied Predictive Analytics
Predictive modelling basics
Ensemble methods (Random Forest, Gradient Boosting) Regression
Classification
AutoML tools
Business use cases
Module 11: Prompt Engineering for Business
Effective prompts
Use cases in analytics
Prompt patterns for BI (analysis, comparison, summarisation)
Module 12: Reporting & Dashboards
Real-time dashboards
Dashboard summaries
Generative AI assistants
Automated KPI monitoring with alerting workflows
Auto-generated hybrid reports: visuals + narrative + recommendations
Module 13: Marketing Analytics
Channel performance (paid, organic, attribution basics) Campaign analysis
Agentic AI for automated campaign optimisation
Module 14: Customer Analytics
Customer Lifetime Value (CLV) and churn basics
Segmentation
Generative AI for customer insights
AI-driven personalisation and engagement workflows
Module 15: Product Analytics
Usage metrics
Funnels
A/B testing
Agentic AI for automated product insights, alerts, and feature optimisation recommendations
Module 16: Financial & Risk Analytics
Financial modelling
Risk scoring
GenAI for financial summaries
Agentic AI for real-time fraud detection and risk mitigation workflows
Module 17: Supply Chain & Operations Analytics
Inventory analysis
Logistics KPIs
GenAI for supply chain planning
Agentic AI for autonomous inventory management and logistics orchestration
Module 18: HR Analytics
Workforce planning and optimisation
Attrition prediction
Talent acquisition analytics
Employee engagement and sentiment analysis (NLP) Performance management insights
Generative AI for JD creation and resume screening
Agentic AI for autonomous recruitment workflows and life cycle management
