Course10610547040 lectures
Artificial Intelligence for Economics
Prof. Adway Mitra, Prof. Dripto Bakshi and Prof. Palash Dey · IIT Kharagpur
About
AI/ML are increasingly being used in various disciplines of science, technology and humanities. They have a wide scope of application in Economics, a subject which has profound influence on the workings of modern society. This course aims to inform students of the key ideas of AI/ML and how they can be applied in the domain of Economics & Finance. The course will include various use-cases based on modern research papers, while also equipping them with the necessary theoretical tools for the same. These will include relevant algorithms in Artificial Intelligence including optimization and search, Machine Learning including predictive algorithms for different types of data, Game Theory and Mechanism Design.
Intended audience: UG/PG/PhD students of AI/ML with interest in Economics.UG/PG/PhD students of Economics with interest in AI/ML
Prerequisites: Basic Engineering/UG level Mathematics and StatisticsBasic Economics, AI or ML will be useful but not necessary.
Lectures
Week 1:
- Lecture 01 : Network Data - Some Stories !!
- Lecture 02 :The Stable Matching Algorithm
- Lecture 03 : Uncertainty in Financial Markets : Idea of Hedging
- Lecture 04 : Uncertainty in Financial Markets : Idea of Hedging (Contd.)
- Lecture 05 : Uncertainty in Financial Markets : Idea of Hedging (Contd.)
Week 2:
- Lecture 06 : Unconstrained Optimization
- Lecture 07 : Constrained Optimization
- Lecture 08 : Heuristic Search Techniques
- Lecture 09 : Multi-objective Heuristic Search and Game Trees
- Lecture 10 : Clustering and Segmentation
Week 3 :
- Lecture 11 : Decision Tree and Random Forest
- Lecture 12 : Linear Regression and Classifiers
- Lecture 13 : Uncertainty Modeling
- Lecture 14 : Neural Networks
- Lecture 15 : Deep Learning for Time Series Forecasting
Week 4:
- Lecture 16 : Causality in Time-Series
- Lecture 17 : Interventional Causality and Attribution
- Lecture 18 : Game Theory
- Lecture 19 : Game Theory (Contd.)
- Lecture 20 : Game Theory (Contd.) Games with Incomplete Information
Week 5 :
- Lecture 21 : Game Theory (Contd.) Games with Incomplete Information (Contd.)
- Lecture 22 : Game Theory - Sequential Games
- Lecture 23 : Game Theory – Rubenstein Bargaining
- Lecture 24 : Network Economics
- Lecture 25 : Network Economics (Contd.)
Week 6:
- Lecture 26 : Introduction to Auction Theory
- Lecture 27 : Second Price Auction
- Lecture 28 : First Price Auction
- Lecture 29 : Overview of Mechanism Design
- Lecture 30 : Groves Mechanism
Week 7 :
- Lecture 31 : VCG Mechanism
- Lecture 32 : Single Parameter Domain and Myerson Lemma
- Lecture 33 : Sponsored Search Auction
- Lecture 34 : Single Peaked Domain and Median Voting
- Lecture 35 : Dimensionality Reduction (Principal Component Analysis) – The Math Prerequisites
Week 8 :
Syllabus and materials
At NPTEL, as the course publishes them.
Credits and licence
- Institution
- IIT Kharagpur
- Department
- Computer Science and Engineering
- Taught by
- Prof. Adway Mitra, Prof. Dripto Bakshi, Prof. Palash Dey
- Level
- Graduate
- Language
- English
- Subjects
- Computer science, Engineering
- Source
- NPTEL
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
- Who can watch
- NPTEL gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed