AI Mastery: From Search Algorithms to Advanced Strategies

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Dr. R. Anto Arockia Rosaline,Dr.Devipriya Ananthavadivel

4:20:14

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1 - Introduction to Artificial Intelligence

1 - Introduction to AI.mp4

08:04

2 - AI techniques.mp4

04:45

3 - Problem solving with AI.mp4

06:21

4 - AI Models.mp4

06:31

5 - Data acquisition and learning aspects in AI.mp4

09:55

6 - Problem solving process.mp4

04:01

7 - Formulating problems.mp4

04:10

8 - Problem types and characteristics and Problem space and search.mp4

04:44

9 - Toy ProblemsTictactoe problems.mp4

08:01

10 - Missionaries and Cannibals Problem.mp4

06:14

11 - Real World ProblemTravelling Salesman Problem.mp4

04:50

2 - Basic Introduction to Data Structure and Search Algorithms

12 - Basic introduction to trees.mp4

16:14

13 - Basic introduction to Graphs.mp4

11:48

14 - General Search Algorithms.mp4

06:13

15 - Uninformed Search Methods.mp4

10:56

16 - Informed search.mp4

12:52

3 - Adversarial Search Problems and Intelligent Agent

17 - Adversarial Search Methods Game Theory Mini Max Algorithm.mp4

11:13

18 - Constraint satisfactory problems and CSP as a search problem Room colouring.mp4

14:35

19 - Intelligent Agent.mp4

19:03

4 - Knowledge Representation

20 - Knowledge Representation.mp4

09:18

21 - Knowledge based agents and The Wumpus world.mp4

07:37

22 - Propositional Logic.mp4

15:59

23 - Predicate logic.mp4

08:16

24 - Unification.mp4

07:27

25 - Knowledge representation using rules.mp4

07:37

26 - Knowledge representation using semantic nets and Frames.mp4

06:50

27 - Uncertain Knowledge and reasoning Methods.mp4

09:27

5 - Planning and Expert System

28 - Planning Simple planning agent Blocks world problem Mean Ends analysis.mp4

08:40

29 - Machine Learning.mp4

08:33

Description

Search Algorithms, Adversarial Search Problems, Knowledge Representation, Planning and Expert System

What You'll Learn?

Formulate a problem in terms of navigating a state space and outline how a range of AI methodologies can be employed to reach a solution.
Utilize relevant search methodologies to address a practical issue in the real world.
Develop a range of gaming strategies aimed at solving practical adversarial search problems in real-world scenarios.
Illustrate different knowledge representation methods for resolving intricate AI challenges.
Create an expert system that employs advanced techniques in Artificial Intelligence.

Who is this for?

This course caters to anyone intrigued by Artificial Intelligence, regardless of their level of expertise.

What You Need to Know?

No Pre-requisite and Co- requisite Courses are required

More details

Description
Embark on a thorough exploration of Artificial Intelligence (AI) in this meticulously designed course, suitable for both beginners and intermediate learners. Covering a diverse range of topics, it establishes a strong foundation in AI theory and algorithms while also delving into practical applications.
Commencing with an overview of AI and its techniques, participants will delve into problem-solving approaches, encompassing both theoretical concepts and real-world implementations. Dive into engaging toy problems like Tic-tac-toe and the Travelling Salesman Problem to gain hands-on problem-solving experience.
Detailed lectures will introduce participants to general search algorithms, both uninformed and informed search methods, and adversarial strategies using game theory, including the Mini Max Algorithm. Additionally, the course explores Constraint Satisfactory Problems (CSP) and the pivotal role of intelligent agents in decision-making processes.
Understanding knowledge representation is vital in AI, and this course provides comprehensive coverage. From foundational propositional and predicate logic to advanced techniques like knowledge representation using rules, semantic nets, and frames, participants will gain insight into how AI systems store and process information.
As the course progresses, participants will delve into uncertainty in knowledge and reasoning, explore machine learning algorithms, and grasp the fundamentals of expert systems. By course completion, participants will possess a firm understanding of AI theory and practical skills applicable to real-world scenarios.
Whether you're a student, professional, or enthusiast, this course empowers you with the knowledge and tools to navigate the dynamic field of Artificial Intelligence confidently. Join us on this educational journey and discover AI's potential to revolutionize industries and shape the future.
Who this course is for:
This course caters to anyone intrigued by Artificial Intelligence, regardless of their level of expertise.

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Artificial Intelligence

Dr. R. Anto Arockia Rosaline

Instructor's Courses

Dr.R.Anto Arockia Rosaline currently working as an Assistant Professor in the Department of Computing Technologies, SRM Institute of Science and Technology, Kattankulathur Campus has 20 years of experience in teaching and research. She received PhD in Computer Science from VIT University. Her areas of interests are Artificial Intelligence, Data Analytics, Data Science, Machine Learning, Text Analytics. She has guided a number of U.G. and P.G. projects. She has presented papers in various International conferences and published number of papers in refereed International Journals. She has delivered invited talk in various forums. She is a member of Computer society of India and IEI. She has received the Active participation Women award. She has also received three Best paper awards for the Oral presentation in various conferences. She has received Grants for the oral presentation in International conference.

Dr.Devipriya Ananthavadivel

Instructor's Courses

Dr. A.Devipriya is currently working as an Assistant Professor in the Department of Computing Technologies, SRM Institute of Science and Technology, Kattankulathur. She has received Ph.D degree in Information and Communication Engineering from Anna University, Chennai. She is having more than 18 years of experience in Teaching. She has completed AI & ML 6 months Course in Xebia Academy, Delhi and Design Thinking Course in Taylor’s University. She has successfully completed and being eligible to take Design the Thinking as a credit course to the students. Her areas of interest is Artificial Intelligence, Machine Learning and Internet of Things.

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