Programme Content
Programme Modules
Module 1. A: Foundation of Data Science
Introduction to Data Science, Business Analytics
Data Science Life Cycle
Data Types
Data Extraction Strategies
Data Transformation
Module 1. B: Effective Data Collection and Preparation Techniques
Data cleaning
Handling missing data and outliers
Data Visualization
Dashboarding using Excel, PowerBI, Tableau
Module 1. C: Leverage Descriptive Analytics for Monitoring and Analysing Business Data
Basic Statistical measures, probability, and random variable, binomial and normal distributions
Module 1. D: Inferential Conclusions via Statistics
Sampling, Hypothesis testing - one sample and two samples), ChiSquare Tests, ANOVA
Module 2. A: Building Data Science Infrastructure
Databases, SQL
NoSQL Database
Business Intelligence, OLAP Analysis
Hadoop Ecosystem
Map Reduce, in memory analytics
Module 2. B: Predictive Analytics: Anticipating Business Outcomes
Regression Analysis
Time Series Analysis
Dimensionality Reduction – PCA, Factor Analysis
Module 2. C: Unveiling the Power of Machine Learning
Market Basket Analysis
Unsupervised Learning – Clustering
Supervised Learning - Classification Models
Reinforcement Learning
Module 3. A: Deep Learning for Business
Neural Networks – MLP, Back Propagation
Natural Language Processing
Computer Vision
Autoencoders
Module 3. B: AI and Cognitive Analytics Applications
Recommendation Systems
Sentiment Analysis
Chatbots
Social Network Analysis
Introduction to cloud computing and cloud-based AI
Module 3. C: Advanced Artificial Intelligence
Explainable AI
Generative AI
Agentic AI
AI Ethics and Privacy
Note:
The in-campus modules are subject to the conditions/ unavoidable circumstances that prevail at the given point in time.
Modules/ topics are indicative only, and the suggested time and sequence may be dropped/ modified/ adapted to fit the participant profile & programme hours.
The session recordings may be made available on the LMS portal in a non-downloadable format for a limited period subject to the condition of faculty discretion regarding the allowance of recordings of their classes.
The programme curriculum includes individual assignments, simulations, group projects & presentations to apply and demonstrate classroom learnings.
Campus immersion will take place at the IIML Noida campus.
