Artificial Intelligence

This introductory workshop on Artificial Intelligence gives an overview of many concepts, techniques, and algorithms in Fuzzy Logic, machine learning, and beginning with topics such as classification and linear regression and ending up with more recent topics such as working with neural network, network training, adaptive training, Best Meaning Fitting, Support Vector Machine etc. The course will give the student the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and when they work.


In this workshop participants will learn designing programmable systems, interafacing various sensors, working with ESP8266, HC05, node-red, IBM Watson IoT, MQTT, AWS IoT and man more.

Topics covered in the workshop:

Day 1: Session 1

Introduction to Artificial Intelligence
Applications of AI in PMU, DG Unit, Substation Placement, Electronics Optimization
Various methods used for AI
Getting Started with MATLAB
Basics of Programming with MATLAB
Control Structure, Functions in MATLAB
Getting started with Fuzzy Logic
Problem Formulation, Defuzzification & Rulebase
Analyzing Tipping problem using Fuzzy logic
Using Fuzzy logic toolbox
Washing Machine Problem using Fuzzy logic Toolbox
Using MATLAB programming for Fuzzy logic Analysis
Fuzzy logic applications in Electrical Engineering
Fuzzy Logic Applications in Communication Engineering

Day 1: Session 2

Getting Started with Machine Learning
Supervised Learning Introduction & Examples
Unsupervised Learning Introduction & Examples
Linear Regression & implementation
Introduction to Network Architecture
Designing Neural Network Model
Model Representation Methods
Single Layer Neural Network
Multilayer Neural Network Architecture
Introduction to Gradient Descent Algorithm
Single Line Training
Using nntool in MATLAB
Programming Neural Network with MATLAB

Day 2: Session 1

Getting started with Raw data Analysis
Character recognition Example
Analyzing the training by varying the training rate, number of training data sets and other factors
Applications of Machine Learning
Support Vector Machine
Working with SVM for Classification
Examples using SVM
Data Analysis using SVM
Applications of SVM

Day 2: Session 2

Introduction to Genetic Algorithm
Overview of Genetic Algorithm
Applications & Scope of GA
Fitness Function, Selection, Crossover & Mutation
Optimizing Nonlinear functions using gatool
Hybrid GA-NLP Method for optimization
Applications of GA in Electrical Engineering
Applications of GA in Electronics Engineering

Hardware Kit: This workshop does not include any hardware kit.

Requirements:

- A working Laptop/PC with minimum of 1 GB RAM, 100 GB HDD, intel i3+ processor
- MATLAB 2012 or above version preinstalled
- A Seminar Hall with sitting capacity of all participants along with charging plugs, proper ventilation
- Projector, Collar Mike and Speakers

Benefits:

- Digital toolkit of PPTs and study material for all participants
- Certificate of Participation for every participant.
- A competition will be organized at the end of the workshop and winners will be awarded by Certificate of Excellence.