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Computational, Mathematical, and Physical Sciences
Department of Statistics

New Course Changes for Fall 2022

In Fall 2022 there will be new changes to the requirements for the Data Science Emphasis and the Actuarial Emphasis. The changes are as follows.

Data Science Capstone Class (2-semester sequence).  

STAT 420 and 421 are now STAT 482 and 483, "Data Science Capstone 1 and 2". The two semester sequence is co-taught with the Computer Science Department and corresponds to CS 482 and 483. The main focus of the year-long class is the successful completion of a capstone project sponsored by professionals working in data science. Past sponsors of capstone projects have included Adobe, Mutual App, Qualtrics, BYU History Department, Overstock, Proctor and Gamble, Ancestry, Recursion Pharmaceuticals and many others. During Fall Semester, students form multidisciplinary groups and are matched with a project sponsor. Course lectures during Fall semester consist of a variety of data science and machine learning topics to prepare students for work on the capstone project. During Winter Semester, students continue working on the capstone project and meet regularly as a group and with their project sponsors. Lecture time during the Winter semester consists of group meetings with academic mentors and guest lectures from professionals working in the industry. The year-long class culminates in a final project presentation event for both students and sponsors.

STAT 482 is only available via add-code. If you are interested in taking STAT 482 this coming Fall, please complete this survey and watch for emails from the Statistics Department. Note that STAT 330, STAT 340, and STAT 125/126/226 (now STAT 286) are prerequisites. Students should also be aware that no credit will be given for the Fall Semester (STAT 482) if the Winter Semester (STAT 483) is not also successfully completed.

Tentative Schedule of Topics for FALL Semester (this is based on topics covered during Fall 2021 and is subject to change)
Week 1: Python review
Week 2: Spark
Week 3: Data concerns
Week 4: Linear and logistic regression
Week 5: Project matchup
Week 6-7: Classification
Week 8: Model Evaluation
Week 9-10: Ensemble learning
Week 11: Clustering
Week 12-13: Deep learning
Week 14-15: Natural language processing

Here's what former students have to say about the class:

"I have really enjoyed this [winter] semester in stat 421 [483] because we get to hear from an all-star cast of guest lecturers that have been really cool and informative."

"Great class. Exposed me to opportunities to gain data science experience that I couldn’t get in my other coursework."

I enjoyed the fact that we got to do something that our sponsors actually need and will be using. That was a very unique experience, and really useful. We got to collaborate with the CEO every week, which was in itself a great experience.

New Data Science Process and Machine Learning Classes

STAT 426 (formly "Data Science Methods and Applications in Statistics") is now STAT 386, "Data Science Process" and STAT 486, "Machine Learning". STAT 386 will cover the first half of the former STAT 426 and STAT 486 will cover the second half of the former STAT 426. This split will help students cover topics such as data wrangling, version control, visualization, data storytelling, data ethics, supervised & unsupervised learning, deep learning, and the basics of natural language process in more depth than was previously possible. One former student put it this way:

"I think splitting the class would be an awesome idea! I for one really enjoyed the Machine Learning half of the class and feel like it was very beneficial for me. I wish we could have gone deeper into it so I could feel more comfortable with different models.  The first half of the class was also very useful because it provided a good foundation for further work, and I always feel a strong base is the right way to go." 

STAT 386 will be offered Fall 2022. The current plan is for both STAT 386 and 486 to be offered in Winter 2023. Please note that STAT 486 will not be offered Fall 2022. Students should also be aware that the prerequisites for STAT 386 are STAT 286, CS 110, or CS 111. Since all the prerequisites are brand new courses, students will need an add-code in order to register for STAT 386. Students who have completed the STAT 125/126/226 courses qualify as having completed the prerequisite. Note that STAT 386 is currently for statistics or actuarial science majors only.

STAT 386 has the following tentative schedule:
Week 1-2: Basic Python, numpy and pandas
Week 3: Git and GitHub
Week 4-5: Importing Data, Web scraping, Using APIs to get data
Week 6-7: Data wrangling
Week 8-10: Data Visualization, data storytelling, dashboards
Week 11-12: Data biases, ethics, and privacy
Week 13-15: Introduction to machine learning and case studies

The prerequisites for STAT 486 are STAT 330, 340 and 386. STAT 486 has the following tentative schedule:
Weeks 1-2: Machine Learning Basics
Weeks 3-6: Supervised Learning
Weeks 7-9: Neural Networks and Deep Learning
Weeks 10-12: Unsupervised Learning
Weeks 13-15: Extended Case study with Natural Language Processing

Here's what former (STAT 426) students had to say about the class

"It was a well structured class that acted as a crash course in data science. I liked using Python. I thought the content was engaging and useful for my career path."

"The first half was a good intro to Python. Second half was good to learn basic ML in Python, more practice in both areas would be good.

"Overall, the class was very useful for someone who is planning to go get a job in data science, so if students plan on working as a data scientist, I would recommend taking the class because it will actually give them a number of applicable skills and experience."

Which option is right for you?  

While we'd love to give everyone the chance to take all the classes, because of demand, we only give credit for one of the options, either STAT 482 & 483 OR STAT 386 & 486. So how do you know which option is right for you? Before answering that question, you should know that the Statistics Department believes that you can't go wrong with either option. Both paths will give you experience in data science and machine learning. Both paths will help you develop marketable skills for your future employment. However, depending on your learning style and your expectations, there might be a path that you enjoy more. Here are two things that you should consider when deciding your own course.

1. Flexibility. While STAT 486 is not being offered in Fall 2022, the plan is to start offering it in the Fall of 2023. Students could then take STAT 386 during Winter Semester and STAT 486 the following Fall in order to graduate in December. STAT 482 and 483 must always be taken together in the same school year (Fall then Winter), so April graduations are the only option when taking these classes as a senior.

2. Teaching Style & Culture. STAT 482 & 483 are co-taught with the computer science department and CS faculty will teach some of the lectures. Some students have found the mix of discipline cultures to be valuable to the learning process while others have found it harder to make connections. The first semester (STAT 482) also goes extremely fast and a broad range of topics are presented in lectures. Some former students loved this format, while others did not. To illustrate the variety of opinions about the first semester in the capstone sequence, read the comments below that were left as part of the exit survey for Stat 421 (now 483):

I really liked the first semester as you focused on Data Science methods which helped us a ton while completing our projects this semester.

The first semester was a bit messy. The lectures were too specific, and too loaded with information, the range of topics was too broad, and their usefulness was not apparent.

I liked that we did a sample of different model building approaches the first semester and then a deep dive the second semester.

We didn't have time to go in depth on certain topics during class, but I understand that going quickly over stuff was just the nature of the class.

I loved the crash course in the first semester. I learned so much, so quickly, and I'm extremely grateful to have had access to the very applicable teaching provided.

One student that was able to take both STAT 420/421 and 426 described the two options as follows:

Stat 426 is very focused on developing your skills needed for data science, as well as building your own portfolio.  It had a great course layout that covered useful tools every class period.   Stat 420/421 feels a little more like a class out of a grad program.  Much less structure with an emphasis on professional exposure.  If you haven't done any relative internships, it has a draw because you are guaranteed a chance to collaborate with a real business. 

Please don't hesitate to reach out if you have any questions. Good luck and we look forward to seeing you in the Fall!

Actuarial Science

Discontinued Courses

  • Stat 377
  • Stat 475
  • Stat 477

New Courses

  • Stat 344 - Long-term Actuarial Math (once a year starting Fall 2022)
    • Prerequisites: 240, 274
  • Stat 346 - Short-term Actuarial Math (once a year starting in Winter 2023)
    • Prerequisites: 274, 340
  • Stat 348 - Predictive Analytics (once a year starting in Fall 2022)
    • Prerequisites: 240, 330
  • Stat 444 - Advanced Long-term Actuarial Math (once a year starting in Winter 2023)
    • Prerequisites: 340, 344
  • Stat 446 - Advanced Short-term Actuarial Math (once a year starting Fall 2025)
    • Prerequisites: 346

Major Requirements

  • Current - 2 of 377, 475, 477
  • New - 344, 346, 348, and one of 444, 446

Eventual Full Program

  • Fall: 274, 344, 348, 446
  • Winter: 274, 346, 444

Joint Exam Coverage

  • FM - 274
  • P - 240 and 340

SOA Exam Coverage

  • FAM - 344 and 346
  • ALTAM - 444
  • ASTAM - 446
  • SRM/PA - 330 and 348
  • ATPA - 251 and 451

CAS Exam Coverage

  • MAS-I -348
  • MAS-II - 251, 348, 451
  • 5 - Some in 346 and 446