CS 344 and CS 386: Artificial Intelligence
(Spring 2017)

(Picture source: http://www.extremetech.com/wp-content/uploads/2012/08/Google500KmilesLexus.jpg.)

This page serves as the primary resource for CS 344 (Artificial Intelligence) and CS 386 (Artificial Intelligence Lab).


  Shivaram Kalyanakrishnan
  Office: Room 220, New CSE Building
  Phone: 7704
  E-mail: shivaram@cse.iitb.ac.in

Teaching Assistants

  A. Siddharth
  Office: 402, New CSE Building, Desk 40
  E-mail: siddarth@cse.iitb.ac.in

  Ashish Ramteke
  Office: SynerG Lab, KReSIT Building, Desk B-2
  E-mail: ashishr@cse.iitb.ac.in

  Pragy Agarwal
  E-mail: pragy@cse.iitb.ac.in

  Amit Kumar
  E-mail: raavan@cse.iitb.ac.in

  Krishna Murthy Bukkapatnam
  E-mail: krishnam@cse.iitb.ac.in

  Mihir Kulkarni
  Office: GRC Lab, Machine 76; Hostel 2, Room 227
  E-mail: mihirk@cse.iitb.ac.in

  Vaibhav Bhosale
  E-mail: vaibhavb@cse.iitb.ac.in

  Anand Dhoot
  E-mail: ananddhoot@cse.iitb.ac.in

Class Meetings

Lectures will be held in 103, New CSE Building, Tuesdays 9.00 a.m. – 10.25 a.m. and Thursdays 10.00 a.m. – 11.25 a.m. CS 344 is officially assigned to Slot 4, and will be treated as such for scheduling examinations and so on.

Lab sessions will be held in Software Lab 2, New CSE Building, during Slot L2: 2.00 p.m. – 4.55 p.m. Tuesdays.

The instructor's office hours will immediately follow class lectures and labs. Meetings can also be arranged by appointment.

Course Description

Artificial Intelligence (AI) surrounds us today: in phones that respond to voice commands, programs that beat humans at Chess and Go, robots that assist surgeries, vehicles that drive in urban traffic, and systems that recommend products to customers on e-commerce platforms. This course aims to familiarise students with the breadth of modern AI, to impart an understanding of the dramatic surge of AI in the last decade, and to foster an appreciation for the distinctive role that AI can play in shaping the future of our society.

The course will provide a historical perspective of the field of AI and discuss of its foundations in logic, knowledge representation and reasoning, search, and learning. A small selection of specialised topics will also be taken up; these could include, for example, speech and natural language processing, robotics, crowdsourcing, computer vision, and multiagent systems. The theory and lab components will proceed in step to equip students with the knowledge and skills to design and apply solutions based on AI.

Students interested in gaining more depth are encouraged to follow this basic course with advanced ones on topics such as machine learning, information retrieval and data mining, sequential decision making, robotics, speech and natural language processing, computer vision, and game theory.


CS 344 and CS 386 are core courses in the CSE undergraduate programme. They can only be taken by CSE B.Tech. students in their third (or higher) year.


Grades for CS 344 will be decided based on four class tests with a combined worth of 45 marks; a mid-semester examination worth 20 marks; and an end-semester examination worth 35 marks.

Grades for CS 386 will be decided based on 6–8 lab assignments, each worth 10–20 marks.

Academic Honesty

Students are expected to adhere to the highest standards of integrity and academic honesty. Acts such as copying in the examinations and sharing code for the lab assignments will be dealt with strictly, in accordance with the institute's procedures and disciplinary actions for academic malpractice.

Texts and References

Artificial Intelligence: A Modern Approach, Stuart J. Russell and Peter Norvig, 3rd edition, Pearson, 2010.



This page will serve as the primary source of information regarding CS 344 and CS 386, their schedules, and related announcements. The Moodle pages for these courses will be used for sharing additional resources for the lectures and assignments, and also for recording grades.

E-mail is the best means of communicating with the instructor; students must send e-mail with ``[CS344]'' in the header, with a copy marked to the TAs.

Class Schedule

Lab Assignments and Schedule

Students are expected to complete each lab assignment within the lab slot (by 5.00 p.m. on the allotted day). Submissions must be uploaded on Moodle in the format specified.

If a submission is not made by 5.00 p.m., a "carry over" will be counted against the assignment. Assignments that are carried over will only be evaluated after the student attends a session with a TA or the instructor to explain their submission and demonstrate its working. A special lab session will be announced to evaluate carry over assignments.

A student may carry over up to two lab assignments without any penalty. A third carry over will incur a penalty of 2 marks; a fourth carry over will incur a penalty of 4 marks; subsequent carry overs will incur a penalty of 6 marks.

Below is the schedule for lab assignments.