Spring 2022
DATA C102 001 - LEC 001
Formerly Statistics 102
Data, Inference, and Decisions
Nika Haghtalab, Ramesh Sridharan
Jan 18, 2022 - May 06, 2022
Tu, Th
09:30 am - 10:59 am
Internet/Online
Class #:29193
Units: 4
Instruction Mode:
Online
Time Conflict Enrollment Allowed
Offered through
Data Science Undergraduate Studies
Current Enrollment
Total Open Seats:
0
Enrolled: 280
Waitlisted: 0
Capacity: 280
Waitlist Max: 100
No Reserved Seats
Also offered as:
STAT C102
Hours & Workload
3 hours of instructor presentation of course materials per week, 7 hours of outside work hours per week, 1 hours of instructional experiences requiring special laboratory equipment and facilities per week, and 1 hours of the exchange of opinions or questions on course material per week.
Final Exam
THU, MAY 12TH
11:30 am - 02:30 pm
Other classes by Nika Haghtalab
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
*Lectures will be online, and all other class activities will be in person.
*This course will allow time conflicts with the lecture, but students are expected to attend their in-person lab and discussion.
*There is no final exam, so final exam conflicts are allowed.
<.. show more
*This course will allow time conflicts with the lecture, but students are expected to attend their in-person lab and discussion.
*There is no final exam, so final exam conflicts are allowed.
<.. show more
*Lectures will be online, and all other class activities will be in person.
*This course will allow time conflicts with the lecture, but students are expected to attend their in-person lab and discussion.
*There is no final exam, so final exam conflicts are allowed.
*This course will have two Out-of-Class midterm times on February 24 from 7-9pm and April 14 from 7-9pm.
*Prerequisites for this course are ENFORCED.
*If you have satisfied one or more of the prerequisites for Data C102 outside of UC Berkeley OR you are a graduating senior in Spring 2022 who will be declared in Data Science and you have not yet satisfied the Modeling, Learning & Decision Making requirement, please submit an enrollment request for Data C102 at:
https://forms.gle/Y6UN9vNLoijKqnJ68
*This class uses 999 and 999L sections. In addition to the lecture, you must enroll in the DIS 999 and LAB 999L to enroll in the course. Selection and assignment into the actual discussions happen outside of CalCentral. Instructors will provide more information during the first lecture. show less
*This course will allow time conflicts with the lecture, but students are expected to attend their in-person lab and discussion.
*There is no final exam, so final exam conflicts are allowed.
*This course will have two Out-of-Class midterm times on February 24 from 7-9pm and April 14 from 7-9pm.
*Prerequisites for this course are ENFORCED.
*If you have satisfied one or more of the prerequisites for Data C102 outside of UC Berkeley OR you are a graduating senior in Spring 2022 who will be declared in Data Science and you have not yet satisfied the Modeling, Learning & Decision Making requirement, please submit an enrollment request for Data C102 at:
https://forms.gle/Y6UN9vNLoijKqnJ68
*This class uses 999 and 999L sections. In addition to the lecture, you must enroll in the DIS 999 and LAB 999L to enroll in the course. Selection and assignment into the actual discussions 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