Artificial Intelligence

Master Artificial Intelligence: From Fundamentals to Cutting-Edge Innovations

Course Curriculum

1. Introduction to Artificial Intelligence

  • AI Introduction
  • AI Applications
  • Introduction to AI, ML, and DL

2. Python Programming Fundamentals

  • Python Installation
  • Python Basics
  • Variables, Data Types & Operators
  • Basic Input & Output Operations
  • Control Flow Statements
  • Functions & Modules in Python

3. Python Programming Advanced Concepts

  • Operators in Python
  • Bitwise, Identity, Membership Operators
  • Lists, Tuples, Sets, and Dictionaries
  • Lists & Implementation
  • Tuples
  • Sets & Hands-On
  • Dictionaries & Hands-On
  • Control Statements
  • Simple if, if-else, elif Statements
  • Loops: While, For Loops with Example Programs
  • Built-in Functions
  • Functions & Recursion
  • Modules and Packages in Python
  • Colab Practice
  • Jupyter Notebook Programs on Advanced Datatypes
  • Tuple Operations

4. Artificial Intelligence: Mathematical Foundations

  • AI Mathematical Foundations
  • AI: Probability, Statistics & Linear Algebra
  • AI: Vectors, Scalars, and Matrices Representation
  • AI: Differential & Integral Calculus
  • Linear Regression & Implementation

5. Data Understanding and Big Data

  • AI Data Understanding
  • AI Big Data
  • Data Collection from Different Sources, Data Cleaning

6. AI: Vision & Classification

  • AI Vision: Classification & Retrieval
  • AI: Convolutional Neural Networks (CNN)
  • CNN & Generative Adversarial Networks (GAN)
  • Five Layers of Sequencer

7. Neural Networks

  • AI: Introduction to Neural Networks
  • AI: Neural Networks in Practice: Optimization
  • Recurrent Neural Networks (RNN)
  • RNN Sequence Modelling
  • About RNNs

8. Reinforcement Learning

  • Introduction to Reinforcement Learning
  • AI Problem Solving
  • Constraint Satisfaction Problems
  • Uninformed Search
  • Informed Search Algorithms
  • A* Search
  • Cryptarithm Problems
  • Uniform Cost Search & Iterative Depth First Search
  • Puzzle Solving Using A* Search

9. Data Analysis & Visualization in Python

  • Introduction to NumPy for Numerical Computing
  • Introduction to Pandas for Data Manipulation and Analysis
  • Data Transformation & Visualization
  • Introduction to Matplotlib for Visualization

10. Machine Learning with Scikit-Learn

  • Overview of Scikit Learn Library for Machine Learning in Python
  • Supervised Learning: Classification & Regression
  • Unsupervised Learning: Clustering

11. Real-Time Tasks

  • Tic-Tac-Toe Game Implementation
  • Grocery Shop Management System
  • Library Management System using Tkinter
  • Student Management System using Tkinter
  • Employee Record Management System
  • Detection of Alzheimer’s Disease
  • Respiratory Disease Classification
  • Crop Disease Prediction
  • Traffic Sign Recognition