A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | Refer to the Class Schedule for additional information. | ||||||||||||||||||||||||||
2 | Course Number | Semester | Course name | Course Instructor | In person or Online Lecture | Lecture Days and Times | Asynchronous or Synchronous | Time Conflicts Allowed with Lecture? | Time Conflicts Allowed with Labs? | Requisite Enforcement | Enrollment Appeal Form (if applicable) | Reserved Seating? | Additional Notes | ||||||||||||||
3 | 2 | Spring 2022 | Introduction to Statistics | TBD | Online | Asynchronous Lecture | Y (updated 11/1/21) | 10/18/21: UPDATED TIME enrollment will open = 2pm today. 10/15/21: The course proposal was approved! We will open Stat 2 enrollment on Monday, 10/18/21 at Noon. 10/11/21: Waiting for approval to offer Stat 2 online, so course is not on schedule right now. | |||||||||||||||||||
4 | C8 | Spring 2022 | Foundations of Data Science (DS Admin) | J. DeNero & S. Sahai | In person | MWF 10:00-11:00am | Administered by Data Science and all seats listed under Data C8. Email ds-enrollments@berkeley.edu for questions. See Data Science Enrollment FAQs and Data Science Spring 2022 Course Page. | ||||||||||||||||||||
5 | 20 Lec 001 | Spring 2022 | Introduction to Probability and Statistics | A. Bray | In person | MWF 11:00am-12:00pm | Synchronous | No | No | To compare Stat 20 Lectures see: https://docs.google.com/spreadsheets/d/1eCUfVanlLuH05VwoojOtTsQ42lN1fBLSUfqBdodzVjU/edit?usp=sharing | |||||||||||||||||
6 | 20 Lec 002 (class# 31141) | Spring 2022 | Introduction to Probability and Statistics | A. Bray | In person (simulcast) | MWF 11:00am-12:00pm | Synchronous | Yes | No | 11/18/21: Lec 2 and Lec 3 are available for enrollment. To compare Stat 20 Lectures see: https://docs.google.com/spreadsheets/d/1eCUfVanlLuH05VwoojOtTsQ42lN1fBLSUfqBdodzVjU/edit?usp=sharing 11/17/21: Lec 2 and Lec 3 will be open for enrollment 11/18/21 at 1:00pm. 11/16/21: Additional Stat 20 lectures and lab sections will be available for enrollment on Thursday, 11/18. More details will be available tomorrow. 11/15/21: The online lecture was approved by COCI but we are still in the process of setting up the course for enrollment with the instructor. 11/1/21: The proposal for an online lecture is still pending approval and will need to be re-evaluated at the next Academic Senate's COCI meeting. We hope to have another update by 11/15/21. 10/18/21: Waiting for approval to offer Stat 20 Lec 2 online, so the online lecture is not on the schedule right now. Students who want to take Stat 20 and enroll in the online lecture can add to the Lec 1 waitlist and we will notify the waitlist students when the online lecture is on the schedule. Alternatively, students can simply check updates to this spreadsheet on Oct. 30th. | |||||||||||||||||
7 | 20 Lec 003 (class# 32785) | Spring 2022 | Introduction to Probability and Statistics | A. Bray | Online | N/A (asynchronous) | Asynchronous Lecture | Yes | No | 11/18/21: Lec 2 and Lec 3 are available for enrollment. To compare Stat 20 Lectures see: https://docs.google.com/spreadsheets/d/1eCUfVanlLuH05VwoojOtTsQ42lN1fBLSUfqBdodzVjU/edit?usp=sharing 11/17/21: Lec 2 and Lec 3 will be open for enrollment 11/18/21 at 1:00pm. 11/16/21: Additional Stat 20 lectures and lab sections will be available for enrollment on Thursday, 11/18. More details will be available tomorrow. 11/15/21: The online lecture was approved by COCI but we are still in the process of setting up the course for enrollment with the instructor. 11/1/21: The proposal for an online lecture is still pending approval and will need to be re-evaluated at the next Academic Senate's COCI meeting. We hope to have another update by 11/15/21. 10/18/21: Waiting for approval to offer Stat 20 Lec 2 online, so the online lecture is not on the schedule right now. Students who want to take Stat 20 and enroll in the online lecture can add to the Lec 1 waitlist and we will notify the waitlist students when the online lecture is on the schedule. Alternatively, students can simply check updates to this spreadsheet on Oct. 30th. | |||||||||||||||||
8 | 33A | Spring 2022 | Introduction to R | G. Sanchez | In person | Friday 9:00-10:00am | Asynchronous options | No | No | ||||||||||||||||||
9 | 33B | Spring 2022 | Introduction to Advanced R | G. Sanchez | In person | Wed 2:00-3:00pm | Asynchronous options | No | No | ||||||||||||||||||
10 | 88 | Spring 2022 | Probability and Mathematical Statistics in Data Science | S. Stoyanov | In person | TTh 6:30-8:00pm | Asynchronous options | No | No | Prerequisite: One semester of calculus: MATH 16A, MATH 10A, or MATH1A; Corequisite or Prerequisite: Foundations of Data Science: STAT/COMPSCI/DATA/INFO C8 | 1/14/22: Dis 101 and Dis 111 CANCELLED (enrolled students emailed). Students planning to take STAT/COMPSCI/DATA/INFO C8 concurrently with Stat 88 must first be fully enrolled before they can enroll in Stat 88. Prof Stoyanov will allow students who have taken Stat 20 instead of Data C8 to enroll in Stat 88, but need to be aware that Python will be used in Stat 88. Students can email stat-enrollments@berkeley.edu for a permission # to enroll in 88 if they've taken Stat 20 instead of Data C8 and satisfy the remaining prerequisites. | ||||||||||||||||
11 | C100 | Spring 2022 | Principles & Techniques of Data Science (DS Admin) | J. Hug & L. Yan | In person | TTh 3:30-5:00pm | Administered by Data Science and all seats listed under Data C100. Email ds-enrollments@berkeley.edu for questions. See Data Science Spring 2022 Course Page. | ||||||||||||||||||||
12 | C102 | Spring 2022 | Data, Inference, and Decisions (DS Admin) | N. Haghtalab & R. Sridharan | Online | TTh 9:30-11:00am | 30 seats for Senior Statisitcs majors | Administered by Data Science and all seats listed under Data C102. Email ds-enrollments@berkeley.edu for questions. See Data Science Spring 2022 Course Page. | |||||||||||||||||||
13 | C131A | Spring 2022 | Introduction to Probability and Statistics for Life Sciences | S. Stoyanov | In person | TTh 2:00-3:30pm | Asynchronous options | No | No | (Requisites enforced by the enrollment system) Prerequisites: STAT/COMPSCI/DATA/INFO C8 or STAT 20; and either MATH 1A, MATH 16A, MATH 10A, or MATH 10B. | https://forms.gle/RtoqAW8aXvrnqGxW6 | Cross-listed with DATA C131A but all seats are listed under Stat C131A. | |||||||||||||||
14 | 133 | Spring 2022 | Concepts in Computing with Data | G. Sanchez | In person | MWF 11:00am-12:00pm | Asynchronous options | No | No | ||||||||||||||||||
15 | 134 | Spring 2022 | Concepts of Probability | A. Lucas | In person | MWF 10:00- 11:00am | No | No | |||||||||||||||||||
16 | 135 | Spring 2022 | Concepts of Statistics | Rebecca Barter (updated 12/20/21) | In person | TTh 11:00am-12:30pm | Asynchronous options | No | No | 12/20/21: New Instructor added: Prof. Rebecca Barter. 11/1/21: Instructor removed. New instructor TBD. | |||||||||||||||||
17 | C140 | Spring 2022 | Probability for Data Science (DS admin) | A. Adhikari | In person | TTh 5:00-6:30pm | (Requisites enforced by the enrollment system) Prerequisites: STAT/COMPSCI/DATA/INFO C8, or STAT/COMPSCI/DATA C100, or both STAT 20 and COMPSCI 61A; and MATH 1B or higher. Corequisite: MATH 54, EL ENG/EECS 16A, STAT 89A, MATH 110 or equivalent linear algebra | Administered by Data Science and all seats listed under DATA C140. See Data Science Spring 2022 Course Page. Email ds-enrollments@berkeley.edu for questions. | |||||||||||||||||||
18 | 150 | Spring 2022 | Stochastic Processes | Visiting Professor - Benson Au | In person | MWF 1:00-2:00pm | Synchronous | N/A (no labs) | |||||||||||||||||||
19 | 152 | Spring 2022 | Sampling Surveys | TBD | In person | TTh 11:00am-12:30pm | 11/8/21: Unfortunately, Stat 152 will not be offered in SP22. Not yet open for enrollment since instructor is still being identified. | ||||||||||||||||||||
20 | 153 | Spring 2022 | Introduction to Time Series | Visiting Professor - Ruoqi Yu | In person | TTh 8:00-9:30am | Synchronous | No | No | ||||||||||||||||||
21 | 154 | Spring 2022 | Modern Statistical Prediction and Machine Learning | TBD | In person | TTh 5:00-6:30pm | (Requisites enforced by the enrollment system) Prerequisites: MATH 53; and MATH 54; and STAT 135. | forthcoming | 35 out of 70 seats reserved for Statistics majors through end of Phase 1 | ||||||||||||||||||
22 | 155 | Spring 2022 | Game Theory | A. Lucas | In person | MWF 9:00-10:00am | Synchronous | No | N/A (no labs) | 50 out of 70 seats reserved for Statistics majors through end of Phase 1 | 11/5/21: Enrollment limit increased to 100. | ||||||||||||||||
23 | 157 | Spring 2022 | Seminar on Topics in Probability & Statistics | J. Steinhardt | In person | MWF 11:00am-12:00pm | Synchronous | No | N/A (no labs) | 20 out of 35 seats reserved for Statistics majors through end of Phase 1 | Forecasting has been used to predict elections, climate change, and the spread of COVID-19. Poor forecasts led to the 2008 financial crisis. In our daily lives, good forecasting ability can help us plan our work, be on time to events, and make informed career decisions. This practically-oriented class will provide you with tools to make good forecasts, including Fermi estimates, calibration training, base rates, scope sensitivity, and power laws. We'll discuss several historical instances of successful and unsuccessful forecasts, and practice making forecasts about our own lives, about current events, and about scientific progress. Prerequisite: Stat 134 | ||||||||||||||||
24 | 159 | Spring 2022 | Reproducible and Collaborative Statistical Data Science | F. Perez | In person | Wed 2:00-5:00pm | Synchronous | No | No | Prep: Python programming at the level of Data 100. | |||||||||||||||||
25 | C200C | Spring 2022 | Principles & Techniques of Data Science (DS Admin) | J. Hug & L. Yan | In person | TTh 3:30-5:00pm | Administered by Data Science and all seats listed under DATA C100. See Data Science Spring 2022 Course Page. Email ds-enrollments@berkeley.edu for questions. | ||||||||||||||||||||
26 | C205B | Spring 2022 | Probability Theory | S. Evans | In person | TTh 2:00-3:30pm | Synchronous | No | No | ||||||||||||||||||
27 | C206B | Spring 2022 | Stochastic Processes: Static and dynamical aspects of random surface models | S. Ganguly | In person | TTh 3:30-5:00pm | 1/6/22: Topic title and description added to class listing. | ||||||||||||||||||||
28 | 210B | Spring 2022 | Theoretical Statistics | S. Mei | In person | TTh 9:30-11:00am | 15 seats reserved for Statistics PhD students | ||||||||||||||||||||
29 | 215B | Spring 2022 | Statistical Models: Theory and Application | E. Purdom | In person | TTh 12:30-2:00pm | 15 seats reserved for Statistics PhD students | ||||||||||||||||||||
30 | 222 | Spring 2022 | Masters of Statistics Capstone Project | T. Bengstron, L. Pospisil | In Person | Tues 5:00 pm - 7:59pm | All seats reserved for Statistics MA students | ||||||||||||||||||||
31 | 230A | Spring 2022 | Linear Models | P. Deng | In person | TTh 2:00-3:30pm | Synchronous | No | No | All seats reserved for Statistics MA students | Not accepting undergraduates at this time. | ||||||||||||||||
32 | 232 | Spring 2022 | Experimental Design | S. Pimentel | In person | TTh 3:30-5:00pm | Synchronous | No | Yes (update 1/10/22) No | Randomization, blocking, factorial design, confounding, heterogeneous effects, interference, generalizability, sequential experiments. | |||||||||||||||||
33 | C241B | Spring 2022 | Advanced Topics in Learning and Decision Making: "Approximate Dynamic Programming and Reinforcement Learning" | M. Wainwright | In person | TTh 5:00-6:30pm | Permission Number required | https://forms.gle/mVSaNMcWFYgfxejYA | By Instructor Permission Only. Restricted to PhD students. | 11/22/21: ADDED TO SCHEDULE. Enrollment by Permission Only. This class is a limited enrollment PhD level class focused on theory/algorithms for approximate dynamic programming and reinforcement learning. Only PhD students will be considered, with priority given to students in Statistics, EECS, and Math before considering other departments. All students should have strong backgrounds in linear algebra, real analysis, probability, and statistics; in addition, they should have taken STAT 210A, and have had exposure to optimization/algorithms at the level of EECS 227A/C or equivalent. Strong performance in other graduate courses, among them STAT C205A, STAT 210B, EECS 226A, and EECS 229A, will increase likelihood of enrollment. To request instructor permission to enroll, complete this form: https://forms.gle/mVSaNMcWFYgfxejYA | |||||||||||||||||
34 | 248 | Spring 2022 | Time Series | A. Guntuboyina | In person | TTh 11:00am-12:30pm | 10 seats reserved for Statistics PhDs | 11/19/21: Enrollment expanded. Additional Lab 102 Opened. | |||||||||||||||||||
35 | 259 | Spring 2022 | Reproducible and Collaborative Statistical Data Science | F. Perez | In person | Wed 2:00-5:00pm | Synchronous | No | No | Prep: Python programming at the level of Data 100. | |||||||||||||||||
36 | 260 | Spring 2022 | Topics in Probability & Statistics | J. Steinhardt | In person | MWF 11:00am-12:00pm | Forecasting has been used to predict elections, climate change, and the spread of COVID-19. Poor forecasts led to the 2008 financial crisis. In our daily lives, good forecasting ability can help us plan our work, be on time to events, and make informed career decisions. This practically-oriented class will provide you with tools to make good forecasts, including Fermi estimates, calibration training, base rates, scope sensitivity, and power laws. We'll discuss several historical instances of successful and unsuccessful forecasts, and practice making forecasts about our own lives, about current events, and about scientific progress. | ||||||||||||||||||||
37 | 272 | Spring 2022 | Statistical Consulting | J. Mcauliffe | In person | Mondays 2:00-4:00pm | Advanced PhDs | ||||||||||||||||||||
38 | 375 | Spring 2022 | Professional Preparation: Teaching of Probability and Statistics | A. Bray | In person | Mon 2-4pm (updated 1/10/21) Wed 3:00-5:00pm | All seats require Permission Number | New Stat GSIs/UGSIs | |||||||||||||||||||
39 | |||||||||||||||||||||||||||
40 | |||||||||||||||||||||||||||
41 | |||||||||||||||||||||||||||
42 | |||||||||||||||||||||||||||
43 | |||||||||||||||||||||||||||
44 | |||||||||||||||||||||||||||
45 | |||||||||||||||||||||||||||
46 | |||||||||||||||||||||||||||
47 | |||||||||||||||||||||||||||
48 | |||||||||||||||||||||||||||
49 | |||||||||||||||||||||||||||
50 | |||||||||||||||||||||||||||
51 | |||||||||||||||||||||||||||
52 | |||||||||||||||||||||||||||
53 | |||||||||||||||||||||||||||
54 | |||||||||||||||||||||||||||
55 | |||||||||||||||||||||||||||
56 | |||||||||||||||||||||||||||
57 | |||||||||||||||||||||||||||
58 | |||||||||||||||||||||||||||
59 | |||||||||||||||||||||||||||
60 | |||||||||||||||||||||||||||
61 | |||||||||||||||||||||||||||
62 | |||||||||||||||||||||||||||
63 | |||||||||||||||||||||||||||
64 | |||||||||||||||||||||||||||
65 | |||||||||||||||||||||||||||
66 | |||||||||||||||||||||||||||
67 | |||||||||||||||||||||||||||
68 | |||||||||||||||||||||||||||
69 | |||||||||||||||||||||||||||
70 | |||||||||||||||||||||||||||
71 | |||||||||||||||||||||||||||
72 | |||||||||||||||||||||||||||
73 | |||||||||||||||||||||||||||
74 | |||||||||||||||||||||||||||
75 | |||||||||||||||||||||||||||
76 | |||||||||||||||||||||||||||
77 | |||||||||||||||||||||||||||
78 | |||||||||||||||||||||||||||
79 | |||||||||||||||||||||||||||
80 | |||||||||||||||||||||||||||
81 | |||||||||||||||||||||||||||
82 | |||||||||||||||||||||||||||
83 | |||||||||||||||||||||||||||
84 | |||||||||||||||||||||||||||
85 | |||||||||||||||||||||||||||
86 | |||||||||||||||||||||||||||
87 | |||||||||||||||||||||||||||
88 | |||||||||||||||||||||||||||
89 | |||||||||||||||||||||||||||
90 | |||||||||||||||||||||||||||
91 | |||||||||||||||||||||||||||
92 | |||||||||||||||||||||||||||
93 | |||||||||||||||||||||||||||
94 | |||||||||||||||||||||||||||
95 | |||||||||||||||||||||||||||
96 | |||||||||||||||||||||||||||
97 | |||||||||||||||||||||||||||
98 | |||||||||||||||||||||||||||
99 | |||||||||||||||||||||||||||
100 |