This document discusses artificial intelligence and provides an overview of an AI course. It defines AI and lists some of its applications such as gaming, natural language processing, and robotics. It also summarizes some key topics that will be covered in the course, including Python programming, statistics, data structures, object-oriented programming, linear algebra, machine learning techniques like neural networks and deep learning, and natural language processing. Real-world projects involving handwritten digit and image classification are also mentioned.

1. Artificial Intelligence
By Srinivas
AI
Demo
By Srinivas
srinib897@gmail.com

2. Leader’s Speak
AI is more important than fire and electricity - Sundar Pichai
AI is big threat to Humans - JackMaa
The Nation that leads the AI will be the future Leader - Putin

3. What is AI
artificial intelligence is the simulation of human intelligence
processes by machines, especially computer systems

4. Applications of AI
● Gaming
● Natural Language Processing
● Experts System
● Vision System
● Speech Recognition
● HandWritten Digit Recognition
● Intelligent Robots

5. Travelling Salesman Problem

6. What is NLP
The field of study that focuses on the interactions between
human language and computers is called Natural Language
Processing, or NLP for short

7. What is Computer Vision
Computer vision automatically extracts, analyzes, and
comprehends useful information from a single image or
an array of images

8. Research Areas

9. Real Time Applications of AI

10. Course Structure - Python
Learn Python programming fundamentals such as data types and
structures, variables, loops, and functions.

11. Course Structure - Statistics
Learn how to apply inferential statistics(sample Data to
population) and probability to important, real-world
scenarios, and building supervised learning models.

12. Course Structure - Data Structures
Learn the concepts of list based data structures, searching and
sorting, maps and hashes, trees and graphs. You'll also learn
about sets, dictionaries and other Python data structures. In this
lesson you'll learn a systematic approach to solving hard
computer programming problems as you do.

13. Course Structure - OOPS
Get an introduction to object-oriented programming, and learn
how to use classes and objects. Also learn the concepts of
inheritance, which makes it easy to extend your code.

14. Course Structure - Linear Algebra
In this section, you will learn the fundamentals of vectors in linear
algebra, intersection points and basic operations involving
vectors.

15. Course Structure - Artificial Intelligence
In this course you’ll learn the basics and applications of AI,
including: machine learning, probabilistic reasoning, computer
vision, and natural language processing.

16. FrameWorks

17. Deep Learning
Neural network
Convolutional Neural Network
Recurrent Neural Network

18. HandWritten Digit Classification
Image Processing
Dogs vs Cats Classification
Image augmentation
Text or document Classification
Object Recognition
ChatBot Making
NLTK - Natural Language processing
Projects - Deep Learning

19. Thank You!