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.
WEEK 1: Probability space: Experiments, sample space, events WEEK 2: Conditional probability: Baye’s 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
MOOCs stand for Massive Open Online Courses. These arefree online courses from universities around the world (eg. StanfordHarvardMIT) offered to anyone with an internet connection.
How do I register?
To register for a course, click on "Go to Class" button on the course page. This will take you to the providers website where you can register for the course.
How do these MOOCs or free online courses work?
MOOCs are designed for an online audience, teaching primarily through short (5-20 min.) pre recorded video lectures, that you watch on weekly schedule when convenient for you. They also have student discussion forums, homework/assignments, and online quizzes or exams.