About the Course:

The aim of this course is to introduce the basics building blocks of Artificial Intelligence in order to design intelligent systems. The students will be introduced to the concepts of artificial agents in various kinds of environments such as fully observable, partially observable and adversarial. The course will touch upon various planning and decision making based methods and algorithms. This course will have equal focus on the theoretical concepts and hands-on exercises.

This course is focussed towards developing AI problem solving skills in the students so as to enable them to take advanced artificial intelligence courses for further studies. At the end of the course, the students would get experienced in applying various artificial intelligence methods for different applications.

Pre-requisutes:

As such there are no course based pre-requisite requirements of this course. However, basics of data structures and algorithms, probability theory and linear algebra is a much needed pre-requisite to follow the material in this course.

Course Credit Structure:

This course is a 500 level elective course open to all the departments and all streams of B.Techs, M.Techs and PhDs. The credit structure of this course is: 3-0-2-7-4 (4 Credits). There will be 3 lectures (150 minutes) and 2 labs (120 minutes) per week. Students are expected to invest 7 hrs of study time for this course per week. Don't get scared you do have 168 hrs/week to choose your study time from.

Reference Materials:

• Primary textbook - Stuart Russell and Peter Norvig, Artificial Intelligence - A Modern Approach, Third Edition, Prentice Hall

• Other reference books

  • Artificial Intelligence by Rich, Knight and Nair

  • A First Course in Artificial Intelligence by Deepak Khemani

Instructor:

Dr Shashi Shekhar Jha

Office: #215, 1st Floor, SRB

Office Hours: TBD (by appointment over email)

Teaching Assistants:

• Armaan Garg <armaan.19csz0002@iitrpr.ac.in>

• Shivam Kainth <shivam.20csz0006@iitrpr.ac.in>

Class Communication:

We will use Google Classroom for all course related communications including:

• Class annoucements

• Reading material/ slides/ class notes

• Submission of assignments

• Submission of projects/demos

• Attendance

• Online Quizzes/Exams

To get the classroom code, email the course TAs.

Tentative Grading Policy:

• Quizzes (2) - 20% | There will be 2 pre-announced quizzes in the course. The exact dates of quizzes will be available in the class schedule. No requests will be entertained for the change in the schedule of quizzes. Further, there will not be any make-up quizzes in the course.

• Assignments (2) - 20%| There will be at least 2 programming intensive assignments. Each assignment may span over 2-3 weeks. Hence, students should start working on the assignment as soon as they are announced.

• Mid-Term Exam - 20%| The syllabus for the mid-term exam will be everything covered till the last lecture just before the mid-terms.

• End-Term Exam - 20% | The syllabus for the end-term exam will be everything covered in the course. However, it will be announced in the class if some portions are not part of the end-term syllabus.

• Term Paper - 15% | Students need to submit a term paper by the end of the course. The term paper can be done either individually or in a group of two students. The evaluation of the term paper will be scattered throughout the course as per the term paper evaluation schedule. The final viva voce will be conducted at the end of the course. To know more about term paper click here

• Class Activity - 5% | There will be a few class activities during the course. Students are expected to participate enthusiastically in these in-class activities to secure the class activity weightage.

This is a tentative breakup of the grades and can change at the discretion of the instructor. However, any change in grading policy will be duly intimated in advance.

In order to successfully clear the course, a student is expected to secure at least 40% of the total weightage. For those who are auditing the course, they need to secure 40% of the total weightage of Quizzes, Mid-term and End-term exams in order to get a pass grade.

Academic Integrity and Honour Code:

• Any kind of plagiarism/cheating/copying etc. will attract an F grade in the course.

• Students are advised to read and understand about plagiarism and never indulge in the same.

• Students are encouraged to discuss and seek guidance (if needed) without breaking any academic integrity.

• All submissions ought to be the original work of the students.

• Any external source must be properly cited mentioning proper references.

Counselling Support:

• Any student experiencing any mental or emotional issues can seek the free and confidential clinical counselling by contacting the Counselling Cell of IIT Ropar.

  • Deepak Kr. Phogat (Clinical Psychologist, Counselor)

    • Common Office: 01, Medical Centre, Utility Block, Main Campus

    • Email: deepak.phogat @ iitrpr ac in

    • Phone: 01881-242264

  • Bhawna Suri (Counseling Psychologist, Counselor)

    • Email: bhawna @ iitrpr ac in

    • Phone: 01881-24-2261