Course Name: Advanced Probability Theory

Course abstract

The course introduces the concept of probability through Kolmogorov’s Axioms. It develops the concept of probability density function, cumulative distribution function, and introduces the concept of a random variable. Different theoretical probability distributions, both discrete and continuous are introduced, and their properties are studied. Different generating functions, viz. MGF, PGF, and characteristic functions of different variables are discussed. It also introduces functions of one or two random variables, and derived random variables, such as t, chisq, F are studied in details. The concept of Order Statistics is introduced, and derivation of distribution of range, median etc. are discussed. Different limit theorems are discussed in detail.


Course Instructor

Media Object

Prof. Niladri Chatterjee

Prof. Niladri Chatterjee is a professor of Department of Mathematics, IIT Delhi. He is B.Stat and M.Stat from Indian Statistical Institute Kolkata. He is an M.Tech in Computer Science and PhD in Computer science from University College London. His major research interests are Statistical Modeling, Big Data, Artificial Intelligence, Machine Learning, Natural Language Processing among others. He has more than 30 years of research and teaching experience. He is also member of several Government committees related to data science. He is currently Chair Professor in AI and Machine Learning.
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Teaching Assistant(s)

No teaching assistant data available for this course yet
 Course Duration : Jan-Apr 2021

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 Syllabus

 Enrollment : 18-Nov-2020 to 25-Jan-2021

 Exam registration : 15-Jan-2021 to 12-Mar-2021

 Exam Date : 25-Apr-2021

Enrolled

2850

Registered

38

Certificate Eligible

12

Certified Category Count

Gold

0

Silver

1

Elite

1

Successfully completed

10

Participation

11

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 Jan 2020 and Jan2021 course
Advanced Probability Theory - Toppers list

ISHAN NIMIT MANKODI 75%

INDIAN INSTITUTE OF TECHNOLOGY,MADRAS

JANAKI S 60%

SRI SAI RAM ENGINEERING COLLEGE

Enrollment Statistics

Total Enrollment: 2850

Registration Statistics

Total Registration : 38

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.