Course Name: Artificial Intelligence : Search Methods for Problem Solving

Course abstract

For an autonomous agent to behave in an intelligent manner it must be able to solve problems. This means it should be able to arrive at decisions that transform a given situation into a desired or goal situation. The agent should be able to imagine the consequence of its decisions to be able to identify the ones that work. In this first course on AI we study a wide variety of search methods that agents can employ for problem solving. In a follow up course – knowledge representation and reasoning - we will go into the details of how an agent can represent its world and reason with what it knows. These two courses should lay a strong foundation for artificial intelligence, which the student can build upon.


Course Instructor

Media Object

Prof.Deepak Khemani

Prof. Deepak Khemani is Professor at Department of Computer Science and Engineering, IIT Madras. He completed his B.Tech. (1980) in Mechanical Engineering, and M.Tech. (1983) and PhD. (1989) in Computer Science from IIT Bombay, and has been with IIT Madras since then. In between he spent a year at Tata Research Development and Design Centre, Pune and another at the then youngest IIT at Mandi. He has had shorter stays at several Computing departments in Europe.Prof Khemani’s long-term goals are to build articulate problem solving systems using AI that can interact with human beings. His research interests include Memory Based Reasoning, Knowledge Representation and Reasoning, Planning and Constraint Satisfaction, Qualitative Reasoning, and Natural Language Processing.
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Teaching Assistant(s)

No teaching assistant data available for this course yet
 Course Duration : Jul-Oct 2021
  View Course
 Syllabus
 Enrollment : 20-May-2021 to 02-Aug-2021
 Exam registration : 17-Jun-2021 to 17-Sep-2021
 Exam Date : 23-Oct-2021

Enrolled

21228

Registered

788

Certificate Eligible

119

Certified Category Count

Gold

0

Silver

8

Elite

47

Successfully completed

64

Participation

479

Success

Elite

Silver

Gold




Legend

AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75 AND FINAL SCORE >=40
BASED ON THE FINAL SCORE, Certificate criteria will be as below:
>=90 - Elite + Gold
75-89 -Elite + Silver
>=60 - Elite
40-59 - Successfully Completed

Final Score Calculation Logic

  • Assignment Score = Average of best 8 out of 12 assignments.
  • Final Score(Score on Certificate)= 75% of Exam Score + 25% of Assignment Score
    Note:We have taken best assignment score from both July 2020 and July 2021 courses
Artificial Intelligence : Search Methods for Problem Solving - Toppers list
Top 1 % of Certified Candidates

MAHATHI GHANTASALA 87%

National Institute of Technology,Puducherry


Top 2 % of Certified Candidates

SRITABH PRIYADARSHI 84%

SCHOOL OF ENGINEERING


Top 5 % of Certified Candidates

SAGAR ASWIN DOSHI 78%

Continental Automotive Components (India) Pvt. Ltd

YOGESH GUPTA 76%

CDAC

NIKHIL JANYANI 75%

NITTE MEENAKSHI INSTITUTE OF TECHNOLOGY

PRATYUSH SHARMA 75%

NITTE MEENAKSHI INSTITUTE OF TECHNOLOGY

JAGANATHAN ANNAMALAI PARAMESHWARAN 75%

GREESHMA G 75%

NITTE MEENAKSHI INSTITUTE OF TECHNOLOGY

Enrollment Statistics

Total Enrollment: 21228

Registration Statistics

Total Registration : 787

Assignment Statistics



Assignment

Exam score

Final score

Score Distribution Graph - Legend

Assignment Score: Distribution of average scores garnered by students per assignment.
Exam Score : Distribution of the final exam score of students.
Final Score : Distribution of the combined score of assignments and final exam, based on the score logic.