This course will introduce the basic foundational aspects of probability theory primarily to an electrical engineering audience. In communications, signal processing and networking applications, probability theory and models play a vital role in design and implementation. This course will prepare a student to take courses such as Digital/Wireless Communications, Adaptive Signal Processing and Communication Networks.
INTENDED AUDIENCE
NIL
PRE-REQUISITES
Basic calculus
INDUSTRY SUPPORT
This course is not directly relevant to industries. It is a fundamental course in probability.
CORE/ELECTIVE COURSE
Elective course; For Masters in Communications Engineering, it is core
UG/PG COURSE
UG OR PG
2310 students have enrolled already!!
COURSE INSTRUCTOR
R Aravind is a faculty member in the Department of Electrical Engineering at the Indian Institute of Technology Madras. Aravind has a PhD in electrical engineering from the University of California, Santa Barbara. His research interests include image and video processing and compression.
Andrew Thangaraj received his B.Tech in Electrical Engineering from the Indian Institute of Technology (IIT), Madras, India in 1998 and a PhD in Electrical Engineering from the Georgia Institute of Technology, Atlanta, USA in 2003. He was a post-doctoral researcher at the GTL-CNRS Telecom lab at Georgia Tech Lorraine, Metz, France from August 2003 to May 2004. From June 2004, he has been with the Department of Electrical Engineering, IIT Madras, where he is currently a professor. Since Jan 2012, he has been serving as Editor for the IEEE Transactions on Communications. Since Oct 2011, he has been serving as NPTEL coordinator at IIT Madras. He has played a key role in initiating and running NPTEL online courses and certification. He is currently a National MOOCs Coordinator for NPTEL in the SWAYAM project of the MHRD.
COURSE LAYOUT
WEEK 1: Probability space: Experiments, sample space, events
WEEK 2: Conditional probability: Bayes' rule
WEEK 3: Independence: Independent and dependent events, conditional independence
WEEK 4: Discrete random variables: PMF, important discrete distributions
WEEK 5: Continuous random variables: PDF, CDF, important continuous distributions
WEEK 6: Multiple random variables: Joint distribution, independence
WEEK 7: Transformation of random variables: CDF method, PDF method
WEEK 8: Expectations: mean, variance, correlation, covariance
SUGGESTED READING
1. Introduction to Probability by Dimitri P. Bertsekas and John N. Tsitsiklis
2. Probability, Random Variables and Stochastic Processes by Athanasios Papoulis, S. Unnikrishna Pillai
CERTIFICATION EXAM
The exam is optional for a fee.
Date and Time of Exams: April 28 (Saturday) and April 29 (Sunday) : Morning session 9am to 12 noon;
Exam for this course will be available in one session on both 28 and 29 April.
Registration url: Announcements will be made when the registration form is open for registrations. The online registration form has to be filled and the certification exam fee needs to be paid. More details will be made available when the exam registration form is published.
CERTIFICATE
Final score will be calculated as : 25% assignment score + 75% final exam score
25% assignment score is calculated as 25% of average of Best 6 out of 8 assignments.
E-Certificate will be given to those who register and write the exam and score greater than or equal to 40% final score. Certificate will have your name, photograph and the score in the final exam with the breakup. It will have the logos of NPTEL and IIT Madras. It will be e-verifiable at nptel.ac.in/noc.
