WEEK 1 - Basic concepts:
discrete probability,
introduction to probability distributions,
infinity and introduction to continuous probabilities,
WEEK 2 - Combinatorics
cumulative distibutions, permutations,
counting combinations,
binomial distribution and inclusion-exclusion,
WEEK 3 - Conditional Probability
discrete conditional probability,
continuous conditional probability + worksheet with solutions
Poisson distribution (and others),
WEEK 4 -
functions of random variables,
normal density,
review for the midterm + mock midterm with solutions.
WEEK 5 - Expected Value, Standard Deviation and Variance
expected value.
variance, coupon collector's problem,
sums of independent random variables,
WEEK 6 - Law of Large Numbers and Central Limit Theorem
Law of Large Numbers + solutions.
Central Limit Theorem: first glance,
Central Limit Theorem: applications,
WEEK 7 - Joint Distributions
joint distributions.
WEEK 8 - Markov Chains
random walks,
Markov chains, stationary distribution,
absorbin Markov chains, matrix methods.
WEEK 9 - Markov Chains - continued
hitting times, irreducible and reversible Markov chains,
Markov chains practice,
Markov Chain Monte Carlo.


Python primer + exercises
week 1
week 2
week 3
week 4
week 5
week 6
week 7
week 8 + 9