Programme Content
Module No.
Module Topics
1
Introduction to the Course, Installing the software
2
Introduction to R
3
Introduction to Python
4
Introduction to Finance
5
Accounting Data Analysis
6
Understanding data in finance, sources of data, cleaning and pre-processing data
7
Understanding Machine Learning
8
Building Models Using Accounting Data
9
Fraud Analytics
10
News Analytics and Sentiment Analysis
11
Valuation Analytics
12
Time Series Analysis in R/Python
13
Understanding stock price behaviour
14
Introduction to Technical Analysis
15
Back-testing Trading Models
16
Valuation of Options
17
Portfolio Analytics
18
Building stock price forecasting models using Machine Learning and Deep learning
19
Introduction to Fintech
20
Introduction to Blockchain and Cryptocurrencies
21
Case Studies of some successful Fintech companies
Capstone Project Work
Indicative hands-on activities during live sessions
Decision Trees and other ML tools for Credit Scoring
Open AI / Generative AI Applications in Financial Analytics
Neural Network (NN) Models for Stock Price Prediction
Building a Trading Model and performing Back Testing
Value-at-Risk (VaR) Estimation
Back Testing of Portfolio Models (Modern Portfolio Theory)
Sentiment Analytics (text Analytics) using NLP or LLM
Valuation Analytics
ML model to analyse and identify financial fraud
