List of topics we will cover :
- Introduction to Artificial Intelligence
- AI Applications and History
- Intelligent Agents and Agent Types
- PEAS Representation
- Turing Test
- Problem Solving Using State Space Search
- Breadth First Search (BFS)
- Depth First Search (DFS)
- Uniform Cost Search
- Iterative Deepening Search
- Greedy Best First Search
- A* Search Algorithm
- Heuristics and Admissibility
- Knowledge Representation Techniques
- Propositional Logic
- Predicate Logic
- Inference Rules
- Resolution Principle
- Forward and Backward Chaining
- Semantic Networks
- Frames and Scripts
- Logical Reasoning in AI
- Unification
- Non-monotonic Reasoning
- Expert Systems Architecture
- Knowledge Base and Inference Engine
- Machine Learning Basics
- Supervised vs Unsupervised Learning
- Classification and Regression
- Overfitting and Underfitting
- Cross Validation
- Artificial Neural Networks
- Perceptron Model
- Activation Functions
- Backpropagation Algorithm
- Multi-layer Perceptron (MLP)
- Fuzzy Logic Systems
- Fuzzy Sets and Membership Functions
- Defuzzification Methods
- Genetic Algorithms
- Selection, Crossover, Mutation
- Fitness Function
- Natural Language Processing Basics
- Parsing and Syntax Analysis
- Ambiguity in NLP
- Planning in AI
- STRIPS Representation
- Goal Stack Planning
- Game Playing in AI
- Minimax Algorithm
- Alpha-Beta Pruning
- Robotics Fundamentals
- Sensors and Actuators
- Motion Planning
- Bayesian Learning
- Bayes Theorem
- Naive Bayes Classifier