With the advent of machine learning, data mining, and many other modern applications of computer science, we are increasingly seeing the influence of probability theory on computer science. This course is aimed at providing a brief introduction to probability theory to CS students so that they can grasp recent CS trends more easily.
Week 1 : A brief axiomatic introduction to discrete probability theory – Karger’s Mincut Week 2 : Random Variables – Quicksort Week 3 : Markov’s and Chebyshev’s Inequalities – Randomized Median Week 4 : Chernoff Bounds – Parameter Estimation & Quicksort Revisited
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.