Meghnad Desai Academy of Economics (MDAE) in collaboration with Symbiosis International University, Pune launches

Certificate Program on "Introduction to Artificial Intelligence (AI) for Finance and Economics"

20 Hours | Live Interactive | Starts 18th June, 2022 |

Saturday | Time 11:00 AM to 1:00 PM (IST)

7 Day Money Back Guarantee

Course Overview:

This course is designed for introducing the beginners to fascinating world of AI and its applications to the Finance and Economics domain. It will cover some common techniques of machine learning followed by the discussion on specific use cases of those techniques for finance and economics applications.

1. At the end of the course you will learn

Understand the use of AI/ML for Finance/Economics.
Gain a perspective of different methods in Machine Learning which are suitable for applications of AI in economics.
Select and develop and appropriate method for an application in finance/economics.

2. Who should take up this course?

Anyone aspiring to learn use of AI in economics and finance

3. What are the course prerequisites?

Participants will need to have access to a laptop/PC.

A logical bent of mind

Key Features

Live Coaching

20 hours instructor-led, live interactive training.

Continuous Assessment

Pre-course and post course evaluation assignment.

Industry Project

1 Industry-led Live Project

Constant Learner Support

Lifetime recording access on LMS.

Alumni Status

Industry event invitations + student network access

Career Enhancement

1 session for resume building and interview tips

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Meet Your Course Faculty

Dr. Rahee Walambe

Associate Professor, Symbiosis Institute of Technology (SIT) Associate research Faculty, Symbiosis Centre for Applied Artificial Intelligence (SCAAI) Symbiosis International University (SIU), Pune, India.

Dr Ketan Kotecha

Professor, Symbiosis Institute of Technology (SIT) Head, Symbiosis Centre for Applied Artificial Intelligence (SCAAI) Symbiosis International University (SIU), Pune, India.

Session-Wise Course Curriculum

Session 1: Introduction to AI and applications in Finance/Economics

History of AI – key events and timelines
Current state of AI – capabilities & applications3. Use cases of AI/ML methods in Finance/Economics
Introduction to basic concepts and notations
Ethics in AI, Concerns of model explainability and Data privacy

Session 2-8: Learning Methods in AI

Data pre-processing – Outlier detection, Scaling, Missing value imputation, Curse of dimensionality & dimensionality reduction methods
Linear & Logistic Regression
Regularization & Model Selection
Tree-based methods
Other ML algorithms – SVM, KNN
Bagging & Boosting concepts
ANN – Basics of GD, Activation functions, Optimizers, Regularization – focus on MLP, CNN, RNN models, backpropagation
Clustering methods

Session 9-10: Applications and Case studies (some of these use cases will be covered)

Fraud Detection (Insurance, Finance)
Claims Prediction (Insurance)
Quitting behaviour and change of service provider of customers (Insurance, Banking)
Demand estimation/estimation of elasticities
Credit Scoring (Finance and Banking)
Load Forecasting
Operational Risks for Banks