25CSC1MN105 -DATA ANALYSIS AND VISUALIZATION THROUGH SPREADSHEETS--VV

Module 1

 

Introduction to Artificial Intelligence & Problem Solving 



  1. Introduction to AI – Evolution of AI, AI problems, AI Techniques, AI Applications

  2. Various AI Domains (Introduction only) 

  3. Problem Solving Techniques - Search Algorithms, Knowledge representation and reasoning (Concepts only) 

  4. Problem Solving Techniques - constraint satisfaction problems, Game playing (Concepts only) 

  5. Problem Solving Techniques - Machine learning, Simulated Annealing (Concepts only)

Module 2

Introduction to Neural Networks

 

  1. Introduction to Artificial Neural Network 

  2. Understanding Brain & Perceptron Model

  3. Single Layer Perceptron Model & Learning in Single layer Perceptron

  4. Model Multi-Layer Perceptron Model & Learning in Multi-layer Perceptron Model   



Module 3

Python Packages for AI 

  1. Pandas 

  2. MatplotLib 

  3. Keras 

  4. Scikit-learn: 

Module 4

 

 Machine Learning Fundamentals 

 

  1. Introduction to Machine learning-

  2. Applications of Machine Learning 

  3. Supervised machine learning- Classification, regression (concepts only) 

  4. Unsupervised machine learning 

  5. clustering, Dimensionality Reduction (concepts only) 

  6. Basics of reinforcement learning

  7. Definition and history of deep learning 

  8. Key differences between traditional machine learning and deep learning