Tools of Business
Analytics

• Introduction to R
• Introduction to Python
• Spreadsheet Modelling using Excel

Descriptive Analytics
and Data Visualisation

• Data visualisation methods and descriptive statistics

Statistical Foundations
for Business Analytics

• Introduction to probability modelling
• Basics of statistical sampling
• Statistical inference
• Hypothesis testing

Modelling for
Business Analytics

• Linear regression models
• Binary and count data regression models
• Generalised regression models
• Inference with regression models and model selection

Data Mining

• Data Analytics Life Cycle
• Anomaly Detection
• Association Rule Learning (Dependency Modelling)
• Principal Component analysis (PCA)
• Clustering / Classification / Regression / Summarisation

Machine Learning

• Neural Networks
• Multilayer Perceptron (MLP)
• Support Vector Machines (SVM)
• Nearest Neighbour Algorithms (KNN)
• Introduction to Artificial intelligence and Deep learning

Text Mining

• Information Retrieval
• Lexical Analysis
• Pattern Recognition
• Tagging
• Annotation
• Information Extraction
• Natural Language Processing (NLP)

Analytics Applications

• Marketing & Digital Media Analytics OR Finance Analytics
• HR Analytics OR Operations & Supply Chain Management

Prescriptive Analytics
using Optimisation and Simulation

• LP Simplex
• GRG and Evolutionary using Excel Solver
• Simulation

Big Data Analytics

• Data Management in Big Data Era
• Concept of Hadoop
• Data Stream Analytics
• Recommender System etc.

Business Forecasting
with Time Series Data

• Visualisation of time series data
• Time series decomposition
• Time series models and its applications

Ethical issues in
Data Analytics

• Understand the ethical implications of data analysis

3 Month Capstone
Project – Optional

• Apply your knowledge to a real-world business analytics problem