| Module Name | Download |
|---|---|
| noc20_cs42_assigment_1 | noc20_cs42_assigment_1 |
| noc20_cs42_assigment_10 | noc20_cs42_assigment_10 |
| noc20_cs42_assigment_11 | noc20_cs42_assigment_11 |
| noc20_cs42_assigment_12 | noc20_cs42_assigment_12 |
| noc20_cs42_assigment_13 | noc20_cs42_assigment_13 |
| noc20_cs42_assigment_2 | noc20_cs42_assigment_2 |
| noc20_cs42_assigment_3 | noc20_cs42_assigment_3 |
| noc20_cs42_assigment_4 | noc20_cs42_assigment_4 |
| noc20_cs42_assigment_5 | noc20_cs42_assigment_5 |
| noc20_cs42_assigment_6 | noc20_cs42_assigment_6 |
| noc20_cs42_assigment_7 | noc20_cs42_assigment_7 |
| noc20_cs42_assigment_8 | noc20_cs42_assigment_8 |
| noc20_cs42_assigment_9 | noc20_cs42_assigment_9 |
| Sl.No | Chapter Name | MP4 Download |
|---|---|---|
| 1 | Introduction: What to Expect from AI | Download |
| 2 | Introduction: History of AI from 40s - 90s | Download |
| 3 | Introduction: History of AI in the 90s | Download |
| 4 | Introduction: History of AI in NASA & DARPA(2000s) | Download |
| 5 | Introduction: The Present State of AI | Download |
| 6 | Introduction: Definition of AI Dictionary Meaning | Download |
| 7 | Introduction: Definition of AI Thinking VS Acting and Humanly VS Rationally | Download |
| 8 | Introduction: Definition of AI Rational Agent View of AI | Download |
| 9 | Introduction: Examples Tasks, Phases of AI & Course Plan | Download |
| 10 | Uniform Search: Notion of a State | Download |
| 11 | Uniformed Search: Search Problem and Examples Part-2 | Download |
| 12 | Uniformed Search: Basic Search Strategies Part-3 | Download |
| 13 | Uniformed Search: Iterative Deepening DFS Part-4 | Download |
| 14 | Uniformed Search: Bidirectional Search Part-5 | Download |
| 15 | Informed Search: Best First Search Part-1 | Download |
| 16 | Informed Search: Greedy Best First Search and A* Search Part-2 | Download |
| 17 | Informed Search: Analysis of A* Algorithm Part-3 | Download |
| 18 | Informed Search Proof of optimality of A* Part-4 | Download |
| 19 | Informed Search: Iterative Deepening A* and Depth First Branch & Bound Part-5 | Download |
| 20 | Informed Search: Admissible Heuristics and Domain Relaxation Part-6 | Download |
| 21 | Informed Search: Pattern Database Heuristics Part-7 | Download |
| 22 | Local Search: Satisfaction Vs Optimization Part-1 | Download |
| 23 | Local Search: The Example of N-Queens Part-2 | Download |
| 24 | Local Search: Hill Climbing Part-3 | Download |
| 25 | Local Search: Drawbacks of Hill Climbing Part-4 | Download |
| 26 | Local Search: of Hill Climbing With random Walk & Random Restart Part-5 | Download |
| 27 | Local Search: Hill Climbing With Simulated Anealing Part-6 | Download |
| 28 | Local Search: Local Beam Search and Genetic Algorithms Part-7 | Download |
| 29 | Adversarial Search : Minimax Algorithm for two player games | Download |
| 30 | Adversarial Search : An Example of Minimax Search | Download |
| 31 | Adversarial Search : Alpha Beta Pruning | Download |
| 32 | Adversarial Search : Analysis of Alpha Beta Pruning | Download |
| 33 | Adversarial Search : Analysis of Alpha Beta Pruning (contd...) | Download |
| 34 | Adversarial Search : Horizon Effect, Game Databases & Other Ideas | Download |
| 35 | Adversarial Search: Summary and Other Games | Download |
| 36 | Constraint Satisfaction Problems: Representation of the atomic state | Download |
| 37 | Constraint Satisfaction Problems: Map coloring and other examples of CSP | Download |
| 38 | Constraint Satisfaction Problems: Backtracking Search | Download |
| 39 | Constraint Satisfaction Problems: Variable and Value Ordering in Backtracking Search | Download |
| 40 | Constraint Satisfaction Problems: Inference for detecting failures early | Download |
| 41 | Constraint Satisfaction Problems: Exploiting problem structure | Download |
| 42 | Logic in AI : Different Knowledge Representation systems - Part 1 | Download |
| 43 | Logic in AI : Syntax - Part - 2 | Download |
| 44 | Logic in AI : Semantics - Part - 3 | Download |
| 45 | Logic in AI : Forward Chaining - Part 4 | Download |
| 46 | Logic in AI : Resolution - Part - 5 | Download |
| 47 | Logic in AI : Reduction to Satisfiability Problems - Part - 6 | Download |
| 48 | Logic in AI : SAT Solvers : DPLL Algorithm - Part - 7 | Download |
| 49 | Logic in AI : Sat Solvers: WalkSAT Algorithm - Part - 8 | Download |
| 50 | Uncertainty in AI: Motivation | Download |
| 51 | Uncertainty in AI: Basics of Probability | Download |
| 52 | Uncertainty in AI: Conditional Independence & Bayes Rule | Download |
| 53 | Bayesian Networks: Syntax | Download |
| 54 | Bayesian Networks: Factoriziation | Download |
| 55 | Bayesian Networks: Conditional Independences and d-Separation | Download |
| 56 | Bayesian Networks: Inference using Variable Elimination | Download |
| 57 | Bayesian Networks: Reducing 3-SAT to Bayes Net | Download |
| 58 | Bayesian Networks: Rejection Sampling | Download |
| 59 | Bayesian Networks: Likelihood Weighting | Download |
| 60 | Bayesian Networks: MCMC with Gibbs Sampling | Download |
| 61 | Bayesian Networks: Maximum Likelihood Learning" | Download |
| 62 | Bayesian Networks: Maximum a-Posteriori Learning | Download |
| 63 | Bayesian Networks: Bayesian Learning | Download |
| 64 | Bayesian Networks: Structure Learning and Expectation Maximization | Download |
| 65 | Introduction, Part 10: Agents and Environments | Download |
| 66 | Decision Theory: Steps in Decision Theory | Download |
| 67 | Decision Theory: Non Deterministic Uncertainty | Download |
| 68 | Probabilistic Uncertainty & Value of perfect information | Download |
| 69 | Expected Utility vs Expected Value | Download |
| 70 | Markov Decision Processes: Definition | Download |
| 71 | Markov Decision Processes: An example of a Policy | Download |
| 72 | Markov Decision Processes: Policy Evaluation using system of linear equations | Download |
| 73 | Markov Decision Processes: Iterative Policy Evaluation | Download |
| 74 | Markov Decision Processes: Value Iteration | Download |
| 75 | Markov Decision Processes: Policy Iteration and Applications & Extensions of MDPs | Download |
| 76 | Reinforcement Learning: Background | Download |
| 77 | Reinforcement Learning: Model-based Learning for policy evaluation (Passive Learning) | Download |
| 78 | Reinforcement Learning: Model-free Learning for policy evaluation (Passive Learning) | Download |
| 79 | Reinforcement Learning: TD Learning | Download |
| 80 | Reinforcement Learning: TD Learning and Computational Neuroscience | Download |
| 81 | Reinforcement Learning: Q Learning | Download |
| 82 | Reinforcement Learning: Exploration vs Exploitation Tradeoff | Download |
| 83 | Reinforcement Learning: Generalization in RL | Download |
| 84 | Deep Learning : Perceptrons and Activation functions | Download |
| 85 | Deep Learning : Example of Handwritten digit recognition | Download |
| 86 | Deep Learning : Neural Layer as matrix operations | Download |
| 87 | Deep Learning : Differentiable loss function | Download |
| 88 | Deep Learning : Backpropagation through a computational graph | Download |
| 89 | Deep Learning : Thin Deep Vs Fat Shallow Networks | Download |
| 90 | Deep Learning : Convolutional Neural Networks | Download |
| 91 | Deep Learning : Deep Reinforcement Learning | Download |
| 92 | Ethics of AI : Humans vs Robots | Download |
| 93 | Ethics of AI : Robustness and Transparency of AI systems | Download |
| 94 | Ethics of AI : Data Bias and Fairness of AI systems | Download |
| 95 | Ethics of AI : Accountability, privacy and Human-AI interaction | Download |
| 96 | Wrapup | Download |
| Sl.No | Chapter Name | English |
|---|---|---|
| 1 | Introduction: What to Expect from AI | Download Verified |
| 2 | Introduction: History of AI from 40s - 90s | Download Verified |
| 3 | Introduction: History of AI in the 90s | Download Verified |
| 4 | Introduction: History of AI in NASA & DARPA(2000s) | Download Verified |
| 5 | Introduction: The Present State of AI | Download Verified |
| 6 | Introduction: Definition of AI Dictionary Meaning | Download Verified |
| 7 | Introduction: Definition of AI Thinking VS Acting and Humanly VS Rationally | Download Verified |
| 8 | Introduction: Definition of AI Rational Agent View of AI | Download Verified |
| 9 | Introduction: Examples Tasks, Phases of AI & Course Plan | Download Verified |
| 10 | Uniform Search: Notion of a State | Download Verified |
| 11 | Uniformed Search: Search Problem and Examples Part-2 | Download Verified |
| 12 | Uniformed Search: Basic Search Strategies Part-3 | Download Verified |
| 13 | Uniformed Search: Iterative Deepening DFS Part-4 | Download Verified |
| 14 | Uniformed Search: Bidirectional Search Part-5 | Download Verified |
| 15 | Informed Search: Best First Search Part-1 | Download Verified |
| 16 | Informed Search: Greedy Best First Search and A* Search Part-2 | Download Verified |
| 17 | Informed Search: Analysis of A* Algorithm Part-3 | Download Verified |
| 18 | Informed Search Proof of optimality of A* Part-4 | Download Verified |
| 19 | Informed Search: Iterative Deepening A* and Depth First Branch & Bound Part-5 | Download Verified |
| 20 | Informed Search: Admissible Heuristics and Domain Relaxation Part-6 | Download Verified |
| 21 | Informed Search: Pattern Database Heuristics Part-7 | Download Verified |
| 22 | Local Search: Satisfaction Vs Optimization Part-1 | Download Verified |
| 23 | Local Search: The Example of N-Queens Part-2 | Download Verified |
| 24 | Local Search: Hill Climbing Part-3 | Download Verified |
| 25 | Local Search: Drawbacks of Hill Climbing Part-4 | Download Verified |
| 26 | Local Search: of Hill Climbing With random Walk & Random Restart Part-5 | Download Verified |
| 27 | Local Search: Hill Climbing With Simulated Anealing Part-6 | Download Verified |
| 28 | Local Search: Local Beam Search and Genetic Algorithms Part-7 | Download Verified |
| 29 | Adversarial Search : Minimax Algorithm for two player games | Download Verified |
| 30 | Adversarial Search : An Example of Minimax Search | Download Verified |
| 31 | Adversarial Search : Alpha Beta Pruning | Download Verified |
| 32 | Adversarial Search : Analysis of Alpha Beta Pruning | Download Verified |
| 33 | Adversarial Search : Analysis of Alpha Beta Pruning (contd...) | Download Verified |
| 34 | Adversarial Search : Horizon Effect, Game Databases & Other Ideas | Download Verified |
| 35 | Adversarial Search: Summary and Other Games | Download Verified |
| 36 | Constraint Satisfaction Problems: Representation of the atomic state | Download Verified |
| 37 | Constraint Satisfaction Problems: Map coloring and other examples of CSP | Download Verified |
| 38 | Constraint Satisfaction Problems: Backtracking Search | Download Verified |
| 39 | Constraint Satisfaction Problems: Variable and Value Ordering in Backtracking Search | Download Verified |
| 40 | Constraint Satisfaction Problems: Inference for detecting failures early | Download Verified |
| 41 | Constraint Satisfaction Problems: Exploiting problem structure | Download Verified |
| 42 | Logic in AI : Different Knowledge Representation systems - Part 1 | Download Verified |
| 43 | Logic in AI : Syntax - Part - 2 | Download Verified |
| 44 | Logic in AI : Semantics - Part - 3 | Download Verified |
| 45 | Logic in AI : Forward Chaining - Part 4 | Download Verified |
| 46 | Logic in AI : Resolution - Part - 5 | Download Verified |
| 47 | Logic in AI : Reduction to Satisfiability Problems - Part - 6 | Download Verified |
| 48 | Logic in AI : SAT Solvers : DPLL Algorithm - Part - 7 | Download Verified |
| 49 | Logic in AI : Sat Solvers: WalkSAT Algorithm - Part - 8 | Download Verified |
| 50 | Uncertainty in AI: Motivation | Download Verified |
| 51 | Uncertainty in AI: Basics of Probability | Download Verified |
| 52 | Uncertainty in AI: Conditional Independence & Bayes Rule | Download Verified |
| 53 | Bayesian Networks: Syntax | Download Verified |
| 54 | Bayesian Networks: Factoriziation | Download Verified |
| 55 | Bayesian Networks: Conditional Independences and d-Separation | Download Verified |
| 56 | Bayesian Networks: Inference using Variable Elimination | Download Verified |
| 57 | Bayesian Networks: Reducing 3-SAT to Bayes Net | Download Verified |
| 58 | Bayesian Networks: Rejection Sampling | Download Verified |
| 59 | Bayesian Networks: Likelihood Weighting | Download Verified |
| 60 | Bayesian Networks: MCMC with Gibbs Sampling | Download Verified |
| 61 | Bayesian Networks: Maximum Likelihood Learning" | Download Verified |
| 62 | Bayesian Networks: Maximum a-Posteriori Learning | Download Verified |
| 63 | Bayesian Networks: Bayesian Learning | Download Verified |
| 64 | Bayesian Networks: Structure Learning and Expectation Maximization | Download Verified |
| 65 | Introduction, Part 10: Agents and Environments | Download Verified |
| 66 | Decision Theory: Steps in Decision Theory | Download Verified |
| 67 | Decision Theory: Non Deterministic Uncertainty | Download Verified |
| 68 | Probabilistic Uncertainty & Value of perfect information | Download Verified |
| 69 | Expected Utility vs Expected Value | Download Verified |
| 70 | Markov Decision Processes: Definition | Download Verified |
| 71 | Markov Decision Processes: An example of a Policy | Download Verified |
| 72 | Markov Decision Processes: Policy Evaluation using system of linear equations | Download Verified |
| 73 | Markov Decision Processes: Iterative Policy Evaluation | Download Verified |
| 74 | Markov Decision Processes: Value Iteration | Download Verified |
| 75 | Markov Decision Processes: Policy Iteration and Applications & Extensions of MDPs | Download Verified |
| 76 | Reinforcement Learning: Background | Download Verified |
| 77 | Reinforcement Learning: Model-based Learning for policy evaluation (Passive Learning) | Download Verified |
| 78 | Reinforcement Learning: Model-free Learning for policy evaluation (Passive Learning) | Download Verified |
| 79 | Reinforcement Learning: TD Learning | Download Verified |
| 80 | Reinforcement Learning: TD Learning and Computational Neuroscience | Download Verified |
| 81 | Reinforcement Learning: Q Learning | Download Verified |
| 82 | Reinforcement Learning: Exploration vs Exploitation Tradeoff | Download Verified |
| 83 | Reinforcement Learning: Generalization in RL | Download Verified |
| 84 | Deep Learning : Perceptrons and Activation functions | Download Verified |
| 85 | Deep Learning : Example of Handwritten digit recognition | Download Verified |
| 86 | Deep Learning : Neural Layer as matrix operations | Download Verified |
| 87 | Deep Learning : Differentiable loss function | Download Verified |
| 88 | Deep Learning : Backpropagation through a computational graph | Download Verified |
| 89 | Deep Learning : Thin Deep Vs Fat Shallow Networks | Download Verified |
| 90 | Deep Learning : Convolutional Neural Networks | Download Verified |
| 91 | Deep Learning : Deep Reinforcement Learning | Download Verified |
| 92 | Ethics of AI : Humans vs Robots | Download Verified |
| 93 | Ethics of AI : Robustness and Transparency of AI systems | Download Verified |
| 94 | Ethics of AI : Data Bias and Fairness of AI systems | Download Verified |
| 95 | Ethics of AI : Accountability, privacy and Human-AI interaction | Download Verified |
| 96 | Wrapup | Download Verified |
| Sl.No | Language | Book link |
|---|---|---|
| 1 | English | Download |
| 2 | Bengali | Not Available |
| 3 | Gujarati | Not Available |
| 4 | Hindi | Not Available |
| 5 | Kannada | Not Available |
| 6 | Malayalam | Not Available |
| 7 | Marathi | Not Available |
| 8 | Tamil | Not Available |
| 9 | Telugu | Not Available |