Overview

Class Central Tips

This programme is ideal for analysts, traders, brokers, consultants and other industry professionals who are seeking the adoption of artificial intelligence, machine learning, and data science in their work environments, and want to learn the essential skills to keep pace with these technological advances.

This programme aims to demonstrate the applications of AI-based models in the finance domain. This includes the application of Python programming in solving real-life wealth management problems to improve investment decisions with AI.

In this programme, you’ll build a solid practical foundation in the finance domain and learn how to deploy AI and machine learning-based models to solve a variety of problems in the finance domain, including wealth-management, algorithmic trading, investment banking, and more.

As you advance through the programme, you’ll learn:
- Fundamentals of financial risk management and tackle financial problems
- Basics of Python and R programming
- Application of artificial intelligence and machine learning-based models to the finance domain.
- Application of these skills in the fields of financial risk management, investments, algorithmic trading, wealth management, sentiment analysis and more, through a hands-on, project based approach.

Syllabus

Course 1: Programming for AI and Data Analytics
- In this course, you will build essential Python and R skills, the most important programming languages in artificial intelligence and data science. You’ll gain familiarity with the coding environments, the basic syntax and semantics of the languages, and different libraries of Python and R. You’ll also learn to perform data exploration tasks and interpret basic inferential statistics results using Python and R. Finally, you’ll be able to work on datasets and represent data using different types of charts and plots.

Course 2: Corporate Finance and Risk Management
- In this course, you will learn and develop the necessary knowledge and skills on the basic and advanced topics related to corporate finance and risk management. You will learn the basics of cash flow discounting and will be able to conduct the valuation of a set of given cash flows using MS Excel. You will be able to understand and apply the concept of risk in estimating the cost of capital for risky projects. You will be able to compare the profitability of different projects using criteria such as NPV, IRR, Payback period, etc. Lastly, you will gain a comprehensive understanding of the concept of market efficiency and its implications for financial markets.

Course 3: Wealth Management and Portfolio Investing
- In this course, you will learn the basic and advanced concepts related to wealth management and portfolio investing. Through hands-on practice, you’ll expand your knowledge of essential topics such as portfolio optimization, asset pricing models, and portfolio performance evaluation. You will also be able to conduct portfolio analysis and optimization using MS Excel, and compare the portfolios for their risk-adjusted performance.

Course 4: Machine Learning and AI
- In this course, you will learn machine learning concepts and algorithms. This course will cover applications of machine learning concepts and popular supervised and unsupervised learning techniques.

Course 5: Algorithmic Portfolio Management
- In this course, you will learn the basics of algorithmic portfolio management and technical trading strategies. You will be introduced to the concepts related to time-series modelling. You’ll gain hands-on experience and working knowledge on topics related to security price forecasting and volatility prediction. You will be able to apply the selected ML algorithms to construct high-performance portfolios.