Decision-Making Under Uncertainty


Prof. N. Gautam

IIT Madras

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SKU: IIT Madras Category:


We are often faced with situations where we need to make decisions that have implications for personal and institutional goals. When there is uncertainty involved, we could either go with our gut feeling or take an analytical approach by characterizing the uncertainty, defining an objective, and evaluating the risk/payoffs of choices. This course is about the latter and is presented through the usage of example problem instances.


Any Interested Learners


Undergraduate course in probability (including topics on random variables and expected value); calculus and algebra


Most industries would find this useful (examples in course are in retail, supply chain and hospitality)


N. Gautam is a Professor at Syracuse University in the department of electrical engineering and computer science. He received his B. Tech. in Mechanical Engineering at IIT Madras followed by an M.S. and Ph.D. in Operations Research from the University of North Carolina at Chapel Hill. Since 1997 he has taught courses in applied probability, stochastic systems, queuing models, decision-making, operations research, and statistics while being on the faculty at Pennsylvania State University and Texas A&M University. Gautam spent a semester at Singapore University of Technology and Design where he developed and taught a stochastic modeling course. He has given seminars in institutions around the world and is involved in research on topics related to this course. He is a Fellow of the Institute of Industrial and Systems Engineering.

Additional information



Total hours


Certification Process

1. Join the course
Learners may pay the applicable fees and enrol to a course on offer in the portal and get access to all of its contents including assignments. Validity of enrolment, which includes access to the videos and other learning material and attempting the assignments, will be mentioned on the course. Learner has to complete the assignments and get the minimum required marks to be eligible for the certification exam within this period.

COURSE ENROLMENT FEE: The Fee for Enrolment is Rs. 1000 + GST

2. Watch Videos+Submit Assignments
After enrolling, learners can watch lectures and learn and follow it up with attempting/answering the assignments given.

3. Get qualified to register for exams
A learner can earn a certificate in the self paced course only by appearing for the online remote proctored exam and to register for this, the learner should get minimum required marks in the assignments as given below:

Assignment score = Score more than 50% in at least 3/4 assignments.
Exam score = 50% of the proctored certification exam score out of 100
Only the e-certificate will be made available. Hard copies will not be dispatched.”

4. Register for exams
The certification exam is conducted online with remote proctoring. Once a learner has become eligible to register for the certification exam, they can choose a slot convenient to them from what is available and pay the exam fee. Schedule of available slot dates/timings for these remote-proctored online examinations will be published and made available to the learners.

EXAM FEE: The remote proctoring exam is optional for a fee of Rs.1500 + GST. An additional fee of Rs.1500 will apply for a non-standard time slot.

5. Results and Certification
After the exam, based on the certification criteria of the course, results will be declared and learners will be notified of the same. A link to download the e-certificate will be shared with learners who pass the certification exam.


Course Details

Week 1: Background and introduction: risk, uncertainty and variability; probability, random variables and expectation; optimization criteria; types of decisions.
Week 2: One-time decisions: secretary problem; utility function; decision trees; TV game shows; Monte Hall problem; project evaluation.
Week 3: Repeated decisions: newsvendor problem; buffering to manage uncertainty; safety stock for inventory; route planning; exploration vs exploitation.
Week 4: Sequential adaptive decision-making: strategic and operational; stochastic programming; Simpson’s Paradox; Markov decision process.

Books and References

Hillier & Lieberman, “Introduction to Operations Research”;
Wayne Winston, “Introduction to Probability Models: Operations Research Volume II”;
Denardo, “Science of Decision Making”


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