__Course Description__

Life is full of uncertainties. So is any real-life mission. Suppose, you are given responsibility of a mission module. How would you systematically evaluate the uncertainties involved in your module? One scientific approach is as follows. First, the events, that might be of your concern, need to be identified. Then they need to be kept under observation for a reasonable period of time. It would produce a data matrix where (i, j)^{th} cell contains required information about occurrence of the i^{th} event at the j^{th} time point. From this data, the uncertainties can be quantified using probabilistic and linear algebraic tools.

**Probability Topics -** Basic: Combinatorial analysis, Axioms of probability, Conditional probability, Independence, Distributions (discrete and continuous); Advanced: Random variables, Expectation, Law of large numbers, Limit theorems, Random walk, Markov chains.

**Linear Algebra Topics -** System of linear equations, Vector space, Linear transformation, Inner product, Determinants, Eigenvalues and eigenvectors, Matrix decomposition, Norms.

__Class Location and Time__ Calendar

**Location:** Room 2204 (at Core 2, 2nd Floor)

**Monday**9 - 9:55 AM**Tuesday**10 - 10:55 AM**Wednesday**11 - 11:55 PM

__Course Instructor__

__Grading Policy__

- 5-6 Assignments: 15%
- 5-6 Quizzes: 25% (Best 5 will be considered)
- Mid Semester: 25%
- End Semester: 35%

__Syllabus and References__

__Prerequisites__

Background reading material will be made available before the respective lecture, if required.