Spring 2023
DATA C102 001 - LEC 001
Formerly Statistics 102
Data, Inference, and Decisions
Eaman Jahani, Ramesh Sridharan
Class #:25516
Units:4
Instruction Mode:
In-Person Instruction
Offered through
Data Science Undergraduate Studies
Current Enrollment
Total Open Seats:
-3
Enrolled: 253
Waitlisted: 0
Capacity: 250
Waitlist Max: 100
No Reserved Seats
Hours & Workload
3 hours of instructor presentation of course materials, 7 hours of outside work hours, 1 hours of instructional experiences requiring special laboratory equipment and facilities, and 1 hours of the exchange of opinions or questions on course material.
Final Exam
THU, MAY 11TH
03:00 pm - 06:00 pm
Other classes by Eaman Jahani
Other classes by Ramesh Sridharan
Course Catalog Description
This course develops the probabilistic foundations of inference in data science, and builds a comprehensive view of the modeling and decision-making life cycle in data science including its human, social, and ethical implications. Topics include: frequentist and Bayesian decision-making, permutation testing, false discovery rate, probabilistic interpretations of models, Bayesian hierarchical models, basics of experimental design, confidence intervals, causal inference, Thompson sampling, optimal control, Q-learning, differential privacy, clustering algorithms, recommendation systems and an introduction to machine learning tools including decision trees, neural networks and ensemble methods.
Class Notes
*Prerequisites for this course are ENFORCED.
*If you completed an approved alternate UC Berkeley prerequisite course or an approved transfer course, please submit an enrollment request for Data C102. See our Enrollment FAQ for details: https://docs.google.com/document/d/1pXOkvkOw7r_nqFP.. show more
*If you completed an approved alternate UC Berkeley prerequisite course or an approved transfer course, please submit an enrollment request for Data C102. See our Enrollment FAQ for details: https://docs.google.com/document/d/1pXOkvkOw7r_nqFP.. show more
*Prerequisites for this course are ENFORCED.
*If you completed an approved alternate UC Berkeley prerequisite course or an approved transfer course, please submit an enrollment request for Data C102. See our Enrollment FAQ for details: https://docs.google.com/document/d/1pXOkvkOw7r_nqFP2Xs_KPhiAYVxYBKSutA2hCHjyB3Y/edit?usp=sharing.
*This class uses 999 and 999L sections. In addition to the lecture, you must enroll in the DIS 999 and LAB 999 to enroll in the course. Selection and assignment into the actual sections happen outside of CalCentral. Instructors will provide more information during the first lecture. show less
*If you completed an approved alternate UC Berkeley prerequisite course or an approved transfer course, please submit an enrollment request for Data C102. See our Enrollment FAQ for details: https://docs.google.com/document/d/1pXOkvkOw7r_nqFP2Xs_KPhiAYVxYBKSutA2hCHjyB3Y/edit?usp=sharing.
*This class uses 999 and 999L sections. In addition to the lecture, you must enroll in the DIS 999 and LAB 999 to enroll in the course. Selection and assignment into the actual sections happen outside of CalCentral. Instructors will provide more information during the first lecture. show less
Rules & Requirements
Requisites
- Mathematics 54 or Mathematics 110 or Statistics 89A or Physics 89 or both of Electrical Engineering and Computer Science 16A and Electrical Engineering and Computer Science 16B; Statistics/Computer Science C100; and any of Electrical Engineering and Computer Science 126, Statistics 140, Statistics 134, Industrial Engineering and Operations Research 172. Statistics 140 or Electrical Engineering and Computer Science 126 are preferred.
Credit Restrictions
Students will receive no credit for DATA C102 after completing STAT 102, or DATA 102. A deficient grade in DATA C102 may be removed by taking STAT 102, STAT 102, or DATA 102.
Repeat Rules
Course is not repeatable for credit.
Reserved Seats
Current Enrollment
No Reserved Seats
Textbooks & Materials
See class syllabus or https://calstudentstore.berkeley.edu/textbooks for the most current information.
Guide to Open, Free, & Affordable Course Materials