Artificial Intelligence Case Study Master Class with Python

Course Curriculum

Chapter 1: Course Introduction

Lecture 1: Course Overview in Animation

Lecture 2: Why to join this course?

Lecture 3: Meet Trainer for this Course

Lecture 4: Introduction of Python and Python Libraries

Lecture 5: Meet Trainer for this Course

Chapter 2: Python Programming Tutorials

Lecture 1: Brief Python Introduction

Lecture 2: Set Up – Python IDLE and Google Colab

Lecture 3: Data Type, Variable and Keywords

Lecture 4: How to produce output and Print Statement in Python

Lecture 5: how to take input from User

Lecture 6: List, Tuple, Set, Dictionary

Lecture 7: List Operations in details

Lecture 8: Tuple Operations in details

Lecture 9: Set Operations in details

Lecture 10: Dictionary Operations in details

Lecture 11: String Operation in Python

Lecture 12: Types of Operators

Lecture 13: Data Type Conversion

Lecture 14: Math library

Lecture 15: Importance of Indentation

Lecture 16: Sequential, Selection, Repetition

Lecture 17: Collections Module

Lecture 18: Queue Module

Lecture 19: Generation of Random Number and Range Functions

Lecture 20: isinstance, Use of format, Timeit(), round(), Slice and abs()

Lecture 21: Datetime and Calendar Module

Lecture 22: Exception Handling in Python

Lecture 23: Iterator

Lecture 24: Generator and Decorators

Lecture 25: Lambda, Map, Filter and Reduce Function

Lecture 26: Python CSV file Operations

Lecture 27: Zip Function

Lecture 28: eval(),exec(),repr() function

Lecture 29: List Comprehension, Sets, Frozensets and Assertion

Lecture 30: Logging Module

Lecture 31: Regular Expression

Lecture 32: Ternary Operator

Lecture 33: Create, Edit, Write, Read Text File

Lecture 34: User Define Functions and inbuilt Function

Lecture 35: Global and local Variables in Functions

Lecture 36: Switch Case

Lecture 37: Python Crash Course

Chapter 3: Numpy Library

Lecture 1: Numpy Library Tutorial 1

Lecture 2: Numpy Library Tutorial 2

Lecture 3: Numpy Library Tutorial 3

Lecture 4: Numpy Library Tutorial 4

Lecture 5: Numpy Library Tutorial 5

Lecture 6: Numpy Library Tutorial 6

Lecture 7: Numpy Library Tutorial 7

Lecture 8: Numpy Office Website

Chapter 4: Machine Learning

Lecture 1: What is Training, Testing and Model Evolution in Machine Learning

Lecture 2: Supervise Machine Learning

Lecture 3: Unsupervised Machine Learning

Lecture 4: Reinforcement Machine Learning

Chapter 5: Unmanned Ground Vehicle Working Flowchart

Lecture 1: Introduction of Artificial Intelligence AI

Lecture 2: Introduction of Unmanned Ground Vehicle

Lecture 3: Forward Path and Return Path for UGV

Chapter 6: Artificial Intelligence for Unmanned Ground Vehicle

Lecture 1: AI Design Part 1 Unmanned Ground Vehicle Path Finding

Lecture 2: AI Design Part 2 Bellman Equation

Lecture 3: AI Design Part 3 Markov Decision Tree

Lecture 4: AI Design Part 4 Q Learning

Lecture 5: AI for Part 5 Code for Displaying Path

Lecture 6: AI for Part 6 Explanation of Code

Chapter 7: Speech Recognition and Natural Language Processing

Lecture 1: Need of NLP and Speech Recognition for UGV

Lecture 2: Voice is Future of User Interface

Lecture 3: Set up Environment

Lecture 4: Speech to Text

Lecture 5: Speech to Test output

Lecture 6: Text to Speech

Lecture 7: Text to Speech Output

Lecture 8: Speech Recognition in Python using Google Speech API

Lecture 9: Restart your Computer with Speech Recognition

Lecture 10: Today’s Day using Speech Recognition

Lecture 11: Convert image to text and text to speech

Lecture 12: Difference Between Speech Recognition and Natural Language Processing

Lecture 13: NLP Tutorial