About this Course

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Learner Career Outcomes

60%

got a tangible career benefit from this course

20%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
Approx. 19 hours to complete
Chinese (Traditional)

Skills you will gain

Artificial Intelligence (AI)Search AlgorithmA.I. Artificial IntelligenceAlgorithms

Learner Career Outcomes

60%

got a tangible career benefit from this course

20%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Beginner Level
Approx. 19 hours to complete
Chinese (Traditional)

Offered by

Placeholder

National Taiwan University

Syllabus - What you will learn from this course

Week
1

Week 1

2 hours to complete

Introduction

2 hours to complete
9 videos (Total 118 min), 1 reading
9 videos
1-2 What is AI16m
1-3 Agents and Environments, PEAS, Environment Type19m
1-4 Different Level Of AI5m
1-5 Wave of AI:Debut, Knowledge Driven, Data Driven6m
1-6 The Classification of Agent, First Wave of AI (Artificial Neural Network)24m
1-7 Second Wave of AI (Expert System)12m
1-8 Third Wave of AI (Some Theory and Principle of Machine Learning)21m
1-9 Conclusion of AI and Machine Learning7m
1 reading
NTU MOOC 課程問題詢問與回報機制1m
Week
2

Week 2

2 hours to complete

Uninformed search

2 hours to complete
6 videos (Total 102 min)
6 videos
2-2 Problem Formulation (ii) - Abstraction18m
2-3 Search on Tree and Graph21m
2-4 Uninformed Search (i) - Breadth-First Search, Uniform-Cost Search18m
2-5 Uninformed Search (ii) - Depth-First Search, Depth-Limited Search, Iterative-Deepening Search14m
2-6 Uninformed Search (iii) - Iterative-Deepening Search, Bidirectional Search15m
1 practice exercise
Week 230m
Week
3

Week 3

2 hours to complete

Informed search

2 hours to complete
6 videos (Total 108 min)
6 videos
3-2 Best-First Search (ii) - A* Search16m
3-3 Best-First Search (iii) - Optimality of A*18m
3-4 Memory Bounded Search (i) - Iterative Deepening A*, RBFS21m
3-5 Memory Bounded Search (ii) - RBFS, Simplified Memory-bounded A*20m
3-6 Heuristic - Preformance, Generating Heuristics15m
1 practice exercise
Week 330m
Week
4

Week 4

2 hours to complete

Non-classic search

2 hours to complete
7 videos (Total 119 min)
7 videos
4-2 Steepest Descent19m
4-3 Simulated Annealing13m
4-4 Evolutionary Computation19m
4-5 Non-deterministic Actions - AND-OR Search, Partial Observations (i) - Sensor-less18m
4-6 Partial Observations (ii) - With Sensors11m
4-7 Partial Observations (iii) - Unknown Environments23m
1 practice exercise
Week 416m

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