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Data Science · Year 2 · Theoretical computer science and statistics
S4 Probability and statistical modeling
Build a solid probabilistic foundation, then learn to estimate, test and model.
269hours of coursework
27weeks at 10 h
3steps
7new courses
1universities
Target skills
- Random variables, common distributions, limit theorems
- Discrete-time Markov chains and Monte Carlo methods
- Estimation, confidence intervals, hypothesis tests
- Linear regression, ANOVA, experimental design, generalized linear models
Semester project
A complete study in R: frame a question, fit a linear model or GLM, check the residuals and write a reproducible report.
Courses this semester
- 1University of Colorado BoulderIntermediateR, Python, Jupyter Notebooksacademic credit
Stated prerequisites: Calculus through Calculus II (multivariate preferred) and some R or Python experience
Show the 3 courses
Course Level Length Rating (reviews) Probability Foundations for Data Science and AI Intermediate 43 h 4.5 (300) Discrete-Time Markov Chains and Monte Carlo Methods Intermediate 33 h 4.5 (22) Statistical Estimation for Data Science and AI Intermediate 29 h 4.0 (99) - 2University of Colorado BoulderIntermediateR, Jupyter Notebooksacademic credit
Stated prerequisites: Calculus through Calculus II (multivariate preferred) and some R programming experience
Show the course
Course Level Length Rating (reviews) Statistical Inference and Hypothesis Testing in Data Science Applications Intermediate 37 h 4.6 (55) - 3University of Colorado BoulderIntermediateR, Jupyter Notebooksacademic credit
Stated prerequisites: Calculus, basic linear algebra and probability theory
Show the 3 courses
Course Level Length Rating (reviews) Modern Regression Analysis in R Intermediate 45 h 4.3 (40) ANOVA and Experimental Design Intermediate 40 h 4.0 (23) Generalized Linear Models and Nonparametric Regression Intermediate 42 h 4.2 (26)
Reading
Introduction to Probability, 2nd ed.J. K. Blitzstein, J. HwangThe most teachable probability textbook: distributions, conditional expectation, Markov chains, Monte Carlo.Free online version
R for Data Science, 2nd ed.H. Wickham, M. Çetinkaya-Rundel, G. GrolemundGetting started with R and the tidyverse before Statistical Modeling.Free, CC BY-NC-ND 3.0
Things to watch
- All three blocks are from CU Boulder and are eligible for academic credit.
- Foundations of Probability and Statistics requires calculus up to Calculus II level: S2 covers it.
- The inference course is taken on its own, because the specialization's other two courses are already in Foundations of Probability and Statistics.
With Coursera Plus
This semester takes 269 hours, about 6 months at 10 hours a week. A Coursera Plus subscription gives access to most of its courses during that time.