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Data Mining and Analysis
Available- Catalog Number
- STATS 202-01
- Course Cost
- $4116.00
- Population
- Undergraduate, Graduate
- Summary
-
Data mining is used to discover patterns and relationships in data. Emphasis is on large complex data sets such as those in very large databases or through web mining. Topics: decision trees, association rules, clustering, case based methods, and data visualization.
Details
- Class Number
- 18046
- Units
- 3
- Interest Area
- Math and Data Science
- Course Format & Length
- In-Person, 8 weeks
- Instructors
- Linh Tran
- Dates
- -
- Prerequisites
-
Introductory courses in statistics or probability (e.g., Stats 60), linear algebra (e.g., Math 51), and computer programming (e.g., CS 105).
- Schedule
- Mon, Wed 4:30 PM - 5:50 PM
-
Introduction to Statistical Learning
Available- Catalog Number
- STATS 216V-01
- Course Cost
- $4116.00
- Population
- Undergraduate, Graduate
- Summary
-
Overview of supervised learning, with a focus on regression and classification methods. Syllabus includes: linear and polynomial regression, logistic regression and linear discriminant analysis; cross-validation and the bootstrap, model selection and regularization methods (ridge and lasso); nonlinear models, splines and generalized additive models; tree-based methods, random forests and boosting; support-vector machines; Some unsupervised learning: principal components and clustering (k-means and hierarchical). Computing is done in R, through tutorial sessions and homework assignments. This math-light course is offered remotely only via video segments (MOOC style). TAs will host remote weekly office hours using an online platform such as Zoom. There are four homework assignments, a midterm, and a final exam, all of which are administered remotely.
- Download syllabus (pdf)
Details
- Class Number
- 20669
- Units
- 3
- Interest Area
- Math and Data Science
- Course Format & Length
- Online, 8 weeks
- Instructors
- Kelly Bodwin, Hunter Glanz
- Dates
- -
- Prerequisites
-
Introductory courses in statistics or probability (e.g., Stats 60 or Stats 101), linear algebra (e.g., Math 51), and computer programming (e.g., CS 105).
- Schedule
- Tue, Thu 10:30 AM - 11:50 AM
-
Introduction to Stochastic Processes I
Available- Catalog Number
- STATS 217-01
- Course Cost
- $4116.00
- Population
- Undergraduate, Graduate
- Summary
-
Discrete and continuous time Markov chains, poisson processes, random walks, branching processes, first passage times, recurrence and transience, stationary distributions.
- Download syllabus (pdf)
Details
- Class Number
- 20919
- Units
- 3
- Interest Area
- Math and Data Science
- Course Format & Length
- In-Person, 8 weeks
- Instructors
- Will Hartog
- Dates
- -
- Prerequisites
-
A post-calculus introductory probability course e.g. STATS 116
- Schedule
- Tues, Thu 10:30am-11:50am
-
Introduction to Statistical Methods: Precalculus
Available- Catalog Number
- STATS 60-01
- Course Cost
- $6860.00
- Population
- High School, Undergraduate, Graduate
- Summary
-
Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of hypotheses, t-tests, correlation, and regression. Possible topics: analysis of variance and chi-square tests, computer statistical packages.
- Download syllabus (pdf)
Details
- Class Number
- 20161
- Units
- 5
- Interest Area
- Math and Data Science
- Course Format & Length
- In-Person, 8 weeks
- Instructors
- Olga Dekhtyar
- Dates
- -
- Schedule
- Mon, Tue, Wed, Thu, Fri 10:30 AM - 11:20 AM