   ##### Course Curriculum

Click on the subject to see the full course curriculum.

##### Math

Students will learn concepts of mathematics that are most useful for understanding higher-level (i.e., quantitative aspects of) economics and finance.

These concepts are as follows –

1) Functions, Limits and Continuity
a) Introduction to Functions
b) Some common functions – 1/x, x^n, ln x, e^x, step function, saw-tooth function
c) Graphing functions
d) Limits (concept, left-hand, right-hand, etc)
e) Continuity
f) Concept of Asymptotes – Horizontal, Vertical and Slant with examples and how to find them

2) Differentiation
a) Concept of the derivative … as rate of change, as slope of tangent, etc
b) Simple rules to find derivatives explained conceptually (product, chain, etc)
c) Application of the rules to find derivatives
d) Implicit derivatives
e) Derivatives of higher order
f) Concept of partial derivatives

3) Application of derivatives
a) Increasing, decreasing
b) Maxima minima
c) Convexity, concavity

4) Anti-derivatives
a) Concept (Riemann), definition and relation to derivatives (Fundamental Theorem)
b) Common methods of integration – substitution, partial fractions and parts
c) Definite integrals and Area Under the Curve

5) Optimization
a) Level set of f (x, y) – convex level set of a quasi-concave function
b) Unconstrained Optimization in two variables
c) Constrained Optimization in two variables – Lagrangian Mulitpliers

6) Linear Algebra
a) Vector Space – spanning of R2 and R3, linear independence, basis, and rank
b) System of linear equations Ax = b – solve by substitution
c) Matrices – (+, -, *, / operations), elementary row and column operations, inverse, rank
d) Solve Ax = b using Cramer’s Rule and Gauss elimination method

7) Basic Principles of Counting
a) Fundamental Theorem of Counting
b) Permutations and Combinations
c) Inclusion-Exclusion Principle

##### Statistics

Students will learn concepts of statistics that are most useful for understanding higher-level (i.e., quantitative aspects of) economics and finance. These concepts are as follows:

1) Random variables

1. Random variables and their types
2. Discrete distributions: Binomial, Poisson
3. Continuous distributions: Normal
4. Cumulative Distribution function (cdf), probability mass function (pmf), probability distribution function(pdf).
5. Expectation and Variance of Random variables
6. Sampling distribution of sample means
7. Mean, Median, Skewness and Kurtosis

2) Jointly Distributed Random Variables

1. Jointly distributed random variables and their types
2. Marginal density – Conditional probability
3. Conditional expectation (mean) and conditional variance
4. Covariance, Correlation and Statistical independence.

3) Elements of Hypothesis Testing

1. Elements of hypothesis testing
2. Standard Normal distribution
3. Testing hypothesis about the mean when the population variance is known
4. Confidence intervals
5. Law of Large Numbers, Discrete distributions: Binomial, Poisson
6. Chi square distribution – comparing sample variance with that of the population
7. Students t- distribution when the sample size is small
8. Size and power of a test

Duration & Structure – Blended Learning Model with self paced recorded videos, virtual live classes as well as in-room training. There will be 48 hours of training (24 hours per course)

Course Dates – To be decided

Who can apply? Students in their first, second or third year of graduation – Students must have secured a minimum 50% in their 12th standard. Students appearing in 12th grade can also apply for this course.

Fees – Rs. 24,000 plus applicable taxes

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Economics Data Science 