Here's some more detail regarding UCLA's Data Theory major

This was from Miles Chen a professor in the math department from around the middle part of 2019:

The major is jointly administered by the Math Department and Statistics Department. The goal is to provide a strong foundation for students who plan on pursuing graduate studies in fields related to Data Science.

Students will have to take statistics courses that cover data analysis (Stats 101A, 101C, 102A, 102B) as well as courses that cover more advanced proof-based math like Math 115A and Math 131A. Students will learn programming in C++ (Pic 10A), R (Stats 20), and Python (Stats 21 - new course). It is a capstone major, so students will take a capstone course with a data project in their final year. A few new courses are also being developed for the major. The full requirements for completing the major is expected to be published and made public by Fall 2019.

There’s a few reasons for the naming “Data Theory” rather than Data Science. Data Science rests on a foundation of math, statistics, and computer science (in addition to domain knowledge of the source of data). One could imagine another major with a stronger focus on software/computer engineering that is developed as a joint venture between Stats/CS or Math/CS departments. “Data Theory” highlights the more theoretical components of the major. That said, students in the data theory major will still get a lot of exposure to computer programming - but will probably learn less of the theoretical aspects of computer science (similar to the difference between PIC courses and CS courses.)

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And the language by the professor is standard at UCLA (as I copy and paste):

The University wants to convey that the major will set someone up for graduate studies if she/he desires, not that the main or only focus is to go for graduate studies.

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I just wanted to add that there’s also a Python class in the Program In Computing (“PIC”) courses 16, which has been there for awhile longer than the one Dr. Chen mentioned in his blurb, as well as Java courses in the three-course PIC 20 series.

Here’s a list of the PIC courses,

which can be attached to one’s degree as a Specialization in Computing, which just about any major can include, with exceptions being the Computer Science major, Statistics, and Data Theory, because, of course, most of their computer courses are self-contained.

There are computationally based majors for various disciplines: Computational and Systems Biology leading to an MS (Life Sciences Department), Linguistics and Computer Science (Linguistics Department), and Mathematics of Computation (Math Dept.).

And there are minors in Digital Humanities, available to a large cross-section of majors; Bioinformatics, for life-science majors, and GIS&T through Geography.

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Here’s the missing link (one that is extant) from my post above from which I took the information:

At some point, hopefully soon, I’ll parse the list for course 22 in my post labeled above as “List 2” and try to remove the courses that don’t belong – it appears that there are a few the University doesn’t offer anymore within the Stats department.

There are also a handful of courses that are not offered now because the first cohort for Data Theory (“DT”) having entered in 2019 as freshmen hasn’t reached the level to be able to take them. As far as transfers are concerned, I didn’t see any who were listed as DT majors for the cohort entering in 2019 – unless they were listed under Statistics majors, so it’ll be interesting to see (at least for me) what the numbers are for 2020. Perhaps the Math department is holding off until 2021 for transfers so those who entered as frosh in 2019 catch up with those who transfer in.

I redid the following schedule because the prior one was more jumbled and confusing.

UCLA Data Theory (“DT”) Major – Minimum Total of Units needed to complete DT major:
……GE Requirements…………………48
……Prep for Major………………38-39
……Major Requirements………51-60
……Total………………………137-147, with 33-43 min. additional units needed to be filled towards the 180 units needed to graduate. This can be accomplished by delving more into the DT major or by adding another major or minor. Unit caps are stated as 208-216, which might be enforced for Letters and Sciences, but not in engineering. I don’t know if there is a program for DT as in engineering (with a 3.5 min. gpa), whereby one can obtain a masters in DT by taking an additional year of courses.

GE Requirements, 48 units min., 10 Courses. Here are two Links:

Courses Needed :

Master List:

There are 25 courses needed to complete a degree in DT

Here’s a link to the DT major with requirements:

Here are the links related to these courses (lower division classes are numbered < 100, and upper is ≥ 100):

– Mathematics and Program In Computing Undergraduate Course Landing, the prerequisite courses and the links to each class which gives a sample syllabus, a very detailed course description, and when course is offered:

– Here are the Math Courses, Descriptions and Prerequisites (without having to go to an individual link provided for each class, with less detail in description):

– Here are the Statistics Course Descriptions and Prerequisites:

Here are the 25 requisite courses for the DT major:

1.) Math 31A - Differential & Integral Calculus, 4.0

2.) Math 31B - Integration & Infinite Series, 4.0

3.) Math 32A - Calculus of Several Variables, 4.0

4.) Math 32B - Calculus of Several Variables, 4.0

5.) Math 33A - Linear Algebra & Apps., 4.0

……Math 33B - Differential Equations, 4.0, Not Required

6.) Math 115A - Linear Algebra, 5.0 (Req. Math 33A)

7.) PIC 10A - Intro. Programming, 5.0 (If no programming experience, take PIC 1, not sure if they still offer this course)

8.) One from following:
……Stats 10 - Intro. Stats Reasoning, 5.0
……Stats 12 - Intro. Stats Methods for Geog. & Environ. Studies, 5.0
……Stats 13 - Intro. Stats Methods for Life Sciences, 5.0
……Stats 15 - Intro. Data Science, 5.0
……Stats 20 - Intro. Stats Programming with R, 4.0
……Stats 21 - Python & Other Technologies for Data Science, 4.0

9.) Math 42 - Intro. Data-driven Math Modeling: Life, Universe, Everything, 4.0 (Req. …Math 31A-33A; Stats 10, 12, or 13; PIC 10)

Major Requirements (See Course Description for additional prereqs), 51-60 Units:

10.) Math 118 – Math Methods of Data Theory, 4.0

11.) Math 131A – Analysis, 4.0

12.) Math 156 – Machine Learning, 4.0

13.) Stats 101A – Intro. Data Analysis & Regression, 4.0

14.) Stats 102A – Intro. Computational Statistics with R, 4.0

15.) Stats 102B – Intro. Comp. and Optim. for Statistics, 4.0 (Req. Stats 102A)

16.) Stats 101C – Intro. Stats Models & Data Mining, 4.0 (Req. Stats 101B, conflict?)

17.) Stats 147 – Data Technologies for Data Scientists, 2.0 (Req. Stats 101B, Math …170S, 101A, 101C or 156)

18.) Stats 184 – Societal Impacts of Data, 2.0 (Req. Stats 101B, Math 170S, 101A, …101C or 156)

19.) Math 170E – Intro. to Probability & Statistics 1, 4.0
19.) Math 100A – Intro. to Probability, 4.0

20.) Math 170S – Intro. to Probability & Statistics 2, 4.0
20.) Math 100B – Intro. to Math Statistics, 4.0

21.) Select 1:
………List 1
………Math 151A - Applied Numerical Methods, 4.0
………Math 151B - Applied Numerical Methods, 4.0
………Math 164 - Optimization, 4.0 (Req. Math 131A)
………Math 168 - Introduction to Networks, 4.0 (Req. Math 170E)
………Math 171 - Stochastic Processes, 4.0 (Req. Math 170E or 170A)
………Math 174E - Mathematics of Finance for Mathematics/Economics …Students, 4.0
………Math 178A - Foundations of Actuarial Mathematics: Life Insurance and …Annuities, 4.0
………Math 178B - Foundations of Actuarial Mathematics: Additional Topics in …Long-Term Actuarial Mathematics, 4.0
………Math 178C - Foundations of Actuarial Mathematics: Loss Models, 4.0
………Math 179 - Advanced Topic in Financial Mathematics, 4.0
………Math 182 - Algorithms, 4.0

22.) Select one:
………List 2:
………Stats 100C - Linear Models, 4.0
………Stats 101B - Introduction to Design and Analysis of Experiment, 4.0
………Stats 102C - Introduction to Monte Carlo Methods, 4.0
………Stats C151 - Experimental Design, 4.0
………Stats M154 - Measurement and Its Applications, 4.0
………Stats C155 - Applied Sampling, 4.0
………Stats 157 - Probability and Statistics Data Modeling and Analysis using …Statistics Online Computational Resource, 4.0
………Stats C161 - Introduction to Pattern Recognition and Machine Learning, …4.0
………Stats 170 - Introduction to Time-Series Analysis, 4.0
………Stats M171 - Introduction to Spatial Statistics, 4.0
………Stats C173 - Applied Geostatistics, 4.0
………Stats 175 - Statistics for Spatial Data, 4.0
………Stats C180 - Introduction to Bayesian Statistics, 4.0
………Stats C183 - Statistical Models in Finance, 4.0
………Stats 184 - Societal Impacts of Data, 2.0
………Stats 188SA - Individual Studies for USIE Facilitators, 1.0
………Stats 188SB - Individual Studies for USIE Facilitators, 1.0
………Stats 188SC - Individual Studies for USIE Facilitators, 2.0
………Stats 195 - Community or Corporate Internships in Statistics, 4.0
………Stats 199 - Directed Research in Statistics, 1.0 to 4.0

23.) One Course from List 1 or 2

24.) One Course from List 1 or 2

25.) Capstone Course: Math M148 – Experience of Data Science, 4.0
25.) Capstone Course: Stats M148 – Experience of Data Science, 4.0

Some additional notes:

I didn’t include the following classes from Math which don’t appear to be offered anymore:

……Math 172B: Actuarial Models I

……Math 172C: Actuarial Models II

……Math 173A: Casualty Models I

……Math 173B: Casualty Models II

……Math 175: Introduction to Financial Math (**Possibly still offered, because they offer a more advanced financial math class)

……Math 176: Speech Communications for Actuarial Students

I think this followed from a few years back when math deemphasized the Actuarial major, even though it still offers the Financial Actuarial Mathematics major. I didn’t see these in the class schedule for 2019-2020.

**- UCLA used to offer Stats from within the Math Department, but it broke off Stats into its own category. You’ll be taking Data Theory core classes from Math or Stats unless they break off Data Theory from these two. **

- Let’s see what Dr. Chen had to say again:

So you have Data Analysis Courses:

Stats 101A: Introduction to Data Analysis and Regression

Stats 101C: Introduction to Statistical Models and Data Mining

Stats 102A: Introduction to Computational Statistics with R

Stats 102B: Introduction to Computation and Optimization for Statistics

Then you have advanced-proof based math:

Math 115A: Linear Algebra – Techniques of proof, abstract vector spaces, linear transformations, and matrices; determinants; inner product spaces; eigenvector theory. P/NP or letter grading. (A lot of majors at UCLA require this course, even among computational and Economics-related majors.)

Math 131A: Analysis - Rigorous introduction to foundations of real analysis; real numbers, point set topology in Euclidean space, functions, continuity. P/NP or letter grading.

These courses might ensure that you wouldn’t have to take courses with undergrads if you entered an MS in Data Science program. I believe this is what Dr. Chen meant when he said the following:

Again, not that UCLA wouldn’t prepare a DT major for the workplace.

And you have the Programming Courses:

PIC 10A: Introduction to Programming, C++

Stats 20: Introduction to Statistical Programming with R

Stats 21: Python and Other Technologies for Data Science

Unless there’s a restriction on DT majors, you can probably take the Specialization in Computing coursework. Here’s the link to this program:

There’s a three-course PIC series involving Java, 20A, 20B, 20C. And as seen above, there are Math and Stats courses involving programming.

Major Cutoffs: 3.30 gpa in premajor gets one in automatically, but a 2.70 is the minimum. Those with between a 2.70 and 3.30 will be admitted “if space is available.” For transfers, it essentially looks like a 3.30 is needed.

There is a capstone within the DT major, a senior project, which more majors at UCLA are requiring.

Here’s what Math M148 states:

Students solve real data science problems for community- or campus-based clients. Students work in small groups with faculty member and client to frame client’s question in data science terms, create mathematical models, analyze data, and report results. Students may elect to undertake research on foundations of data science, studying advanced topics and writing senior thesis with discussion of findings or survey of literature on chosen foundational topic. Development of collaborative skills, communication principles, and discussion of ethical issues. Letter grading.

I hope this gives you at least a basis of what to expect from the DT major at UCLA. In any case your counselor/advisor or maybe your talks with your math professors would be best with whom to consult. Sounds like a great major.

Sorry I sloughed over the non-DT courses as I wanted to detail mainly the DT major. But for Letters and Science, there are also: the Writing, the Foreign Language, the Diversity, and the Quantitative Reasoning Requirements within L&S.

Writing Requirements, Letters and Science

If one doesn’t qualify for bypassing Writing I, the student will have to take English Composition 3, 5.0 units. Writing II encompasses a list of courses to take which are below. One can satisfy this requirement within the GEs by taking the Freshmen Clusters, but there are also some interesting courses for WII outside of the Clusters and GEs.

Here’s a link to an algorithm to see if one can bypass WI and the reqs:

Here’s a link for the WII courses, along with whether it would satisfy a GE:

If you wanted to step up your game by taking say a scientific or business writing class here’s a list of Composition classes, with upper division having some really specialized classes:

Diversity Requirement

There’s a Stats class, 112, 5.0 units – Windows to Underserved Diversity, that satisfies the requirement. Here’s the master list:

Language Requirements

Here is the master list of languages that fulfill UCLA’s L&S requirements in case not fulfilled in high school or by examination:

Quantitative Reasoning Requirement

Satisfied by majoring in DT.

Freshman Clusters

As stated above the Clusters will satisfy many of the GEs, possibly the Diversity requirement, and possibly the writing reqs.

Here’s an update Part I

Sorry about some of the links not working because I originally did this based off of the 2019-20 UCLA catalogue. UCLA has updated the requirements for Data Theory (DT), and there are 27 courses that are required for the major, not 25 as I showed above.

With that in mind, I wanted to see how a four-year Data Theory (DT) courseload would work out for a student who would need maxed out GEs and prereqs, because it’s not a short major, but it is in Letters & Science which requires a lot of GEs. I will refer to the student as “Z” (totally fictitious and won’t invoke gender references).

I. Here’s a general algorithm for determining GEs for one’s major.

….b** Determine if the GE Writing I requirement has been met. If not, take English Composition 3 in summer before or early in freshman year.

….b** From the three GE Foundation tracks, find the sub-foundational classes required for one’s primary area of study by the college/school in which the major is located. (Example for DT will follow.)

….b** Determine if the student will take a freshman-year cluster:

………b** If yes, then pick a three-term, freshman-year Subject Cluster, which will reduce GEs and remove the Writing II requirement which will be completed in the spring term.

………b** If no, then the three-sets of Foundation GEs and their sub-foundational subjects will be chosen from the following inclusive of an approved Writing II course (English Comp has some specialized lower- and upper-division writing courses, which may or may not satisfy the II requirement):

….b** If needed, choose approved courses that will fulfill the Language Requirement. (Links for these will follow so as not to clutter the writeup.)

….b** Choose a course that will fulfill the Diversity Requirement, which is required of all students.

….b** Choose a Quantitative Reasoning class if necessary. Some majors will satisfy this requirement, and some will score well enough on the Math to bypass this requirement.

….b** Here’s a worksheet for L&S GEs:

I. Here are the following assumptions about Student Z:

b** Z didn’t have any AP college credits for Mathematics and will take all 6 calculus courses, 31A-33B at UCLA, even if 33B isn’t required for DT; I’m guessing though that it could be recommended.

b** Z did not meet the Letters & Science Language requirement, so Z will take language classes at UCLA.

b** Z will take a Freshman Cluster.

b** Z is not in working to enter the College Honors program.

b** Z has not satisfied the Writing I requirement and will have to take English Composition 3.

III. Choosing specific coursework for DT

….b** Link to Foundation GE requirements by College:

….b** L&S in which DT is located, requires the following Foundations GEs and its sub-foundational courses:

……….FOUNDATIONS OF THE ARTS & HUMANITIES, 3 Courses 15 Total Units Minimum
……………Literary & Culture Analysis, 1 Course, 5 Units
……………Philosophic & Linguistic Analysis, 1 Course, 5 Units
……………Visual & Performance Arts Analysis & Practice, 1 Course, 5 Units

……….FOUNDATIONS OF SOCIETY & CULTURE, 3 Courses Total 15 Units Minimum
……………Historical Analysis, 1 or 2 Courses, 5 or 10 Units
……………Social Analysis, 2 or 1 Course, 10 or 5 Units

……….FOUNDATIONS OF SCIENTIFIC INQUIRY, 4 Courses Total 18 Units Minimum, 2 Labs
……………Life Sciences, 2 Courses, 1 with Lab, 9 Units
……………Physical Sciences, 2 Courses, 1 with Lab, 9 Units

….b** Here is a link for the freshman clusters for 2020-21:

………b** Student Z has chosen Cluster M1 – “Food: a Lens for Environment & Sustainability,” and satisfying this cluster will cover the following courses within the Foundational GEs:

………b** By completing the M1 Cluster, the following GEs will still need to be completed:

……….FOUNDATIONS OF THE ARTS & HUMANITIES, 3 Courses, 15 Total Units Minimum
……………Literary & Culture Analysis, 1 Course, 5 Units
……………Philosophic & Linguistic Analysis, 1 Course, 5 Units
……………Visual & Performance Arts Analysis & Practice, 1 Course, 5 Units

……….FOUNDATIONS OF SOCIETY & CULTURE, Total 2 Courses, 10 Units Minimum
……………Historical Analysis, 1 or 2 Courses, 5 or 10 Units
……………Social Analysis, 1 or 0 Courses, 4 or 0 Units

……….FOUNDATIONS OF SCIENTIFIC INQUIRY, Total 1 Courses, 4 Units Minimum
……………Physical Sciences, 1 Courses, 4 Units (No Lab)

………b** Student Z will fulfill the remainder Foundations classes from the following link:

……………Foundation of Arts & Humanities, Literary & Cultural Analysis: Italian 42A, “Italy through Ages in English: Saints and Sinners in Early Modern Italy”, 5.0 Units

……………Foundation of Arts & Humanities, Philosophic & Linguistic Analysis: Philosophy 9, “Principles of Critical Reasoning”, 5.0

……………Foundation of Arts & Humanities, Visual & Performance Arts & Practice; Musicology 7, “Film & Music”, 5.0

……………Foundation of Society & Culture, Historical Analysis, Scandinavian 138, “Vikings”, 5.0
………….Foundation of Society & Culture, Social Analysis, Comparative Literature 20, “Blockchain: Future of Absolutely Everything”, 5.0

………….Foundation of Scientific Inquiry, Physical Sciences, Geography 5, “People and Earth’s Ecosystems”, 5.0

….b** For GE Languages, Student Z wanted to take Sumerian, the oldest written language, or Akkadian, the second oldest, but the scheduling is inconsistent for both (Near Eastern Languages at UCLA is underappreciated and underenrolled) so Z chose Greek instead. Here’s a link for the approved language classes:

………b** Here’s Z’s schedule available in fall, winter, and spring:

……………Greek 1, 5.0 Units
……………Greek 2, 5.0
……………Greek 3, 5.0

….b** Here are the approved Diversity classes:

………b** Student Z will take Statistics 112, “Statistics: Window to Understand Diversity”, 5.0.

….b** The DT required courses have changed from earlier when I listed them. There are now 27 pre-major and major courses that are required for a degree in DT, rather than 25. Rather than duplicate-listing them, here’s the updated worksheet:

….Here are the courses chosen by Student X, again she will take Math 33B:

………b** Premajor 12 Courses, 51 Units

……………Math 31A, 4.0…….Math 42, 4.0
……………Math 31B, 4.0…….Math 115A, 5.0
……………Math 32A, 4.0…….PIC 10A, 5.0
……………Math 32B, 4.0…….Stats 20, 4.0
……………Math 33A, 4.0…….Stats 21, 4.0
……………Math 33B, 4.0…….Stats 10 (Elective), 5.0

………b** 17 Major courses, 65 Units:

………….Math 118, 4.0……… Stats 102B, 4.0………Math 182, 4.0
.…………Math 131A, 4.0…… Stats 147, 2.0……………Stats 102C, 4.0
……….…Math 156, 4.0………Stats 184, 2.0…………Stats 101B, 4.0
.…………Stats 101A, 4.0…….Stats 100A, 4.0………Stats C161, 4.0
.…………Stats 101C, 4.0…….Stats 100B, 4.0……. Stats M148 (Capstone), 4.0
………….Stats 102A, 4.0……Stats 112, 5.0 (Diversity)

….b** Here’s a couple links for Math and Statistics:

…………Undergraduate Course Landing Mathematics with Detailed Course Description when classes are offered for 20-21 (subject to change yearly):

…………Course Listings and Descriptions for Statistics (there’s no comprehensive course landing as in math):

Continued in the next post…

Update Part II

IV. Here’s a complete listing of courses for student Z, with approximate term when course is offered, possible year when they can be taken – perhaps “should” be taken, their units and what requirement they’ve satisfied, abbreviated as: Course and Number, “Title” / Term / Units / Requirement // Added Notes. There are a total of 42 classes with 184 Units:

  1. English Composition 3 / Sum, Y0; F, Y1 / 5.0 / Writing I
  2. Cluster M1A, “Food: A Lens for Environment & Sustainability” / F, Y1 / 6.0 / GE-Foundation
  3. Cluster M1B, “Food…” / W, Y1 / 6.0 / GE Foundation
  4. Cluster M1CW, “Food…” / S, Y1 / 6.0 / GE Foundation, Writing II
  5. Italian 42A, “Italy through Ages in English: Saints and Sinners in Early Modern Italy”/ W, Y1-Y4 / 5.0 / GE Foundation of Arts & Humanities, Literary & Cultural Analysis
  6. Philosophy 9, “Principles of Critical Reasoning”/ S, Y1-Y4 / 5.0 / GE Foundation of Arts & Humanities, Philosophic & Linguistic Analysis
  7. Musicology 7, “Film & Music”/ S, Y1-Y4 / 5.0 / GE Foundation of Arts & Humanities, Visual & Performance Arts & Practice
  8. Scandinavian 138, “Vikings” / W, Y1-Y4 / 5.0 / GE Foundation of Society & Culture, Historical Analysis
  9. Comparative Literature 20, “Blockchain: Future of Absolutely Everything” / ?, Y1-Y4 / 5.0 / GE Foundation of Society & Culture, Social Analysis
  10. Geography 5, “People and Earth’s Ecosystems” / F, W?, S?, Y1-Y4 / 5.0 / GE Foundation of Scientific Inquiry, Physical Sciences
  11. Geek 1, Elementary / F, Y1-Y4 / 5.0 / GE Language Requirement
  12. Greek 2, Elementary / W, Y1-Y4 / 5.0 / GE Language Requirement
  13. Greek 3, Elementary / S, Y1-Y4 / 5.0 / GE Language Requirement
  14. Math 31A, “Differential and Integral Calculus” / F, Y1 / 4.0 / DT Prerequisite
  15. Math 31B, “Integration and Infinite Series” / W, Y1 / 4.0 / DT Prerequisite
  16. Math 32A, “Calculus of Several Variables” / S, Y1 / 4.0 / DT Prerequisite
  17. Math 32B, “Calculus of Several Variables” / F, Y2 / 4.0 / DT Prerequisite
  18. Math 33A, “Linear Algebra and Applications” / W, Y2 / 4.0 / DT Prerequisite
  19. Math 33B, “Differential Equations” / S, Y2 / 4.0 / Not Required
  20. PIC 10A, “Introduction to Programming” / F or W, Y1 / 5.0 / DT Prerequisite
  21. Math 42, “Introduction to Data-Driven Mathematical Modeling: Life, The Universe, and Everything” / S, Y2 / 4.0 / DT Prerequisite // Lists Math 31A-33A, PIC 10A as Prerequisites
  22. Math 115A, “Linear Algebra” / S, Y2 / 5.0 / DT Prerequisite // Lists Math 33A as Prerequisite
  23. Stats 10, “Introduction to Statistical Reasoning” / F, Y2 / 5.0 / DT Prerequisite Elective // No Listed Prerequisites
  24. Stats 20, “Introduction to Statistical Programming with R” / W, Y2 / 4.0 / DT Prerequisite //Stats 10, 12, or 13 Listed as Prerequisite
  25. Stats 21, “Python and Other Technologies for Data Science” / S, Y2 / 4.0 / DT Prerequisite //Stats 20 Listed as Prerequisite
  26. Math 118, “Mathematical Methods of Data Theory” / F, W; Y3-Y4 / 4.0 / DT Major Requirement // Prerequisites Math 42 and Math 115A
  27. Math 131A, “Analysis” / F, W, S; Y3-Y4 / 4.0 / DT Major Requirement // Listed Prerequisites: Math 32B, M33B , 115A; Slight conflict because Math 33B is not required for DT major
  28. Math 156, “Machine Learning” / F, W; Y4 / 4.0 / DT Major Requirement // Listed Prerequisites: Math 115A, 164, Stats 100A, PIC 10A, Stats 21
  29. Math 182, “Algorithms” / F, W, S; Y3-Y4 / 4.0 / DT Major Elective // Listed Prerequisites: Math 32A and 61
  30. Stats 100A, “Introduction to Probability” / F, W, S; Y3-Y4 / 4.0 / DT Major Requirement, Choice Between This Class and Math 170E// Listed Prerequisites Math 32A
  31. Stats 100B, “Introduction to Mathematical Statistics” / F, W, S; Y3-Y4 / 4.0 / DT Major Requirement, Choice Between This Class and Math 170S // Listed Prerequisites Stats 100A
  32. Stats 101A, “Introduction to Data Analysis and Regression” / W, Y3-Y4 / 4.0 / DT Major Requirement // Listed Prerequisites Stats 10, 12, or 13; and 20
  33. Stats 101B, “Introduction to Design and Analysis of Experiment / S, Y3-Y4 / 4.0 / DT Major Elective // Listed Prerequisite Stats 101A
  34. Stats 101C, “Introduction to Statistical Models and Data Mining” / F, Y3-Y4 / 4.0 / DT Major Requirement // Listed Prerequisite Stats 101B
  35. Stats 102A, “Introduction to Computational Statistics with R” / W, Y3-Y4 / 4.0 / DT Major Requirement // Listed Prerequisites Stats 20, Math 33A
  36. Stats 102B, “Introduction to Computation and Optimization for Statistics” / S, Y3-Y4 / 4.0 / DT Major Requirement // Listed Prerequisites Stats 100B, 102A, Math 33A
  37. Stats 102C, “Introduction to Monte Carlo Methods” / F, Y4 / 4.0 / DT Major Elective // Listed Prerequisites Stats 100B, 102A
  38. Stats 112, “Statistics: Window to Understanding Diversity” / F, Y3-Y4 / 5.0 / Diversity Requirement // Listed Prerequisite Stats 10
  39. Stats 147, “Data Technologies for Data Scientists” / Not Offered Currently Because No DT Majors in Upper Division / 2.0 / DT Major Requirement // Listed Prerequisites Stats 100B, 101A, 101C
  40. Stats C161, “Introduction to Pattern Recognition and Machine Learning” / Not Offered Currently Because No DT Majors in Upper Division / 4.0 / DT Major Elective // Listed Prerequisites Stats 100B and Math 33A
  41. Stats 184, “Societal Impacts of Data” / Not Offered Currently Because No DT Majors in Upper Division / 2.0 / DT Major Requirement // Listed Prerequisites Stats 100B, 101A, or 101C
  42. Stats M148, “Experience of Data Science / Not Offered Currently Because No DT Majors in Upper Division / 4.0 / DT Major Capstone Project // Listed Prerequisites Stats 100B, 101A, or 101C

Some notes:

– So it is feasible to have effectively no APs or other things to opt out of courses and still be pretty close to 180 units. But those who do have them, can get credit and simultaneously up the 180 minimum cap and add AP credits generated and do what they want with the other credits, double major, delve deeper into the major, etc. Or they can use them to graduate earlier.

– There are four upper-division DT classes that have not been offered yet, Stats 147, M148, C161, and 184, because the first cohort of prospective DT majors entered in 2019 as freshmen and obviously aren’t upperclassmen. There were as far as I could see none that entered that year from community college either. I don’t foresee any transfers being admitted this year also, because the 2020-21 schedule doesn’t appear to include these classes.

– I originally wanted to put together an individual 12-quarter schedule/planner but that’s a little hard to do with a new major. I believe, though, that students should try to attempt to do this within a spreadsheet to keep track of their classes and keep detailed track of specific GE, pre-major and major requirements with cumulative units completed and yet to be taken. Things won’t go perfectly, because any preplanned course schedule will run into time and day conflicts, etc, and some will change their majors, but I think it would be a good exercise.

When I get a chance, I’ll try to do a comparison between Stats and Data Theory, perhaps in a different thread. And I might do course listings for other majors.

The main thing is that Stats is a shorter major with 20 lower and upper division classes required, with the key courses being the 9 Stats classes 100A-100C, 101A-C, and 102A-C being the chief foundation classes.

Because it’s a shorter major, students often combine Stats with Applied Math, and I believe perhaps Econ or Bus Econ, or something remotely relatable. Some students are stepping into a grad Stats program for an MS right away. We’ll have to see what DT majors do.

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