EE 178 : Syllabus

Here is a rough syllabus (precise schedule will depend on the progress in class, and suggestions/feedback are welcome).

  1. Probability spaces

    1. Sample spaces.

    2. Probability law.

    3. Conditional probablity.

    4. Bayes rule.

    5. Independence.

  2. Random variables

    1. Definitions.

    2. Pmf, pdf, cdf.

    3. Important probability distributions.

    4. Joint distributions.

  3. Expectation

    1. Definition.

    2. Conditional expectation.

    3. Correlation and covariance.

  4. Limit theorems

    1. Law of large numbers.

    2. Central limit theorem.

  5. Random processes

    1. Basic Concepts.

    2. Markov chains.

    3. Bayesian networks.

Homeworks will be assigned on Friday, due on Friday of the following week.

There will be a midterm on October 23rd 7–9pm, and a final exam on December 11th 7–10pm.