Course Description

This comprehensive course is designed to provide a robust understanding of Artificial Intelligence (AI) and Python programming. You will start with foundational knowledge in AI, including its applications and the basics of Machine Learning (ML) and Deep Learning (DL). The course covers Python programming from fundamentals to advanced topics, and explores mathematical foundations crucial for AI, such as probability, statistics, and linear algebra. Learn about data processing, neural networks, and reinforcement learning. You will also gain practical experience with real-time tasks and projects that apply your skills in AI and Python to solve real-world problems.

What You Will Learn

• Introduction to Artificial Intelligence and its applications.
• Fundamentals of Python programming, including syntax, data types, and control flow.
• Advanced Python concepts such as functions, recursion, and modules.
• Mathematical foundations for AI, including linear algebra, calculus, and statistical methods.
• Data processing and big data handling for AI applications.
• Understanding and implementing neural networks, including CNNs and GANs.
• Exploring reinforcement learning and AI problem-solving techniques.
• Data analysis and visualization using Python libraries like NumPy, Pandas, and Matplotlib.
• Machine learning with Scikit-Learn, including both supervised and unsupervised learning techniques.
• Hands-on experience with real-time tasks and projects.

Course Curriculum

• Introduction to Artificial Intelligence
  • AI Introduction
  • AI Applications
  • Introduction to AI, ML, and DL
• Python Programming Fundamentals
  • Python Installation
  • Python Basics
  • Variables, Data Types & Operators
  • Basic Input & Output Operations
  • Control Flow Statements
  • Functions & Modules in Python
• Python Programming Advanced Concepts
  • Python Programming 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
• 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
• Data Understanding and Big Data
  • AI Data Understanding
  • AI Big Data
  • Data Collection from Different Sources, Data Cleaning
• AI: Vision & Classification
  • AI Vision: Classification & Retrieval
  • AI: Convolutional Neural Networks (CNN)
  • CNN & Generative Adversarial Networks (GAN)
  • Five Layers of Sequencer
• Neural Networks
  • AI: Introduction to Neural Networks
  • AI: Neural Networks in Practice: Optimization
  • Recurrent Neural Networks (RNN)
    • RNN Sequence Modelling
    • About RNNs
• 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
• 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
• Machine Learning with Scikit-Learn
  • Overview of Scikit Learn Library for Machine Learning in Python
  • Supervised Learning: Classification & Regression
  • Unsupervised Learning: Clustering

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