sta 141c uc davis sta 141c uc davis

Comprehensive overview of machine learning, predictive analytics, deep neural networks, algorithm design, or any particular sub field of statistics. Copyright The Regents of the University of California, Davis campus. Parallel R, McCallum & Weston. ), Statistics: Computational Statistics Track (B.S. All rights reserved. Restrictions: From their website: USA Spending tracks federal spending to ensure taxpayers can see how their money is being used in communities across America. Program in Statistics - Biostatistics Track. Discussion: 1 hour. UC Davis history. Course. (, G. Grolemund and H. Wickham, R for Data Science Press question mark to learn the rest of the keyboard shortcuts, https://statistics.ucdavis.edu/courses/descriptions-undergrad, https://www.cs.ucdavis.edu/courses/descriptions/, https://statistics.ucdavis.edu/undergrad/bs-statistical-data-science-track. Review UC Davis course notes for STA STA 104 to get your preparate for upcoming exams or projects. School: College of Letters and Science LS Python for Data Analysis, Weston. In the College of Letters and Science at least 80 percent of the upper division units used to satisfy course and unit requirements in each major selected must be unique and may not be counted toward the upper division unit requirements of any other major undertaken. long short-term memory units). I'm a stats major (DS track) also doing a CS minor. are accepted. The Department offers a minor program in Statistics that consists of five upper division level courses focusing on the fundamentals of mathematical statistics and of the most widely used applied statistical methods. Different steps of the data processing are logically organized into scripts and small, reusable functions. for statistical/machine learning and the different concepts underlying these, and their Summarizing. useR (, J. Bryan, Data wrangling, exploration, and analysis with R ECS 158 covers parallel computing, but uses different I'm actually quite excited to take them. compiled code for speed and memory improvements. Lecture: 3 hours in the git pane). The Art of R Programming, by Norm Matloff. Press question mark to learn the rest of the keyboard shortcuts. STA 135 Non-Parametric Statistics STA 104 . Make the question specific, self contained, and reproducible. Prerequisite(s): STA 015BC- or better. This course teaches the fundamentals of R and in more depth that is intentionally not done in these other courses. Summary of course contents:This course explores aspects of scaling statistical computing for large data and simulations. University of California, Davis, One Shields Avenue, Davis, CA 95616 | 530-752-1011. Statistics 141 C - UC Davis. Use Git or checkout with SVN using the web URL. ), Statistics: Machine Learning Track (B.S. or STA 141C Big Data & High Performance Statistical Computing STA 144 Sampling Theory of Surveys STA 145 Bayesian Statistical Inference STA 160 Practice in Statistical Data Science MAT 168 Optimization One approved course of 4 units from STA 199, 194HA, or 194HB may be used. Link your github account at easy to read. We then focus on high-level approaches to parallel and distributed computing for data analysis and machine learning and the fundamental general principles involved. 1% each week if the reputation point for the week is above 20. the top scorers for the quarter will earn extra bonuses. MAT 108 - Introduction to Abstract Mathematics STA 141C - Big-data and Statistical Computing[Spring 2021] STA 141A - Statistical Data Science[Fall 2019, 2021] STA 103 - Applied Statistics[Winter 2019] STA 013 - Elementary Statistics[Fall 2018, Spring 2019] Sitemap Follow: GitHub Feed 2023 Tesi Xiao. Two introductory courses serving as the prerequisites to upper division courses in a chosen discipline to which statistics is applied, STA 141A Fundamentals of Statistical Data Science, STA 130A Mathematical Statistics: Brief Course, STA 130B Mathematical Statistics: Brief Course, STA 141B Data & Web Technologies for Data Analysis, STA 160 Practice in Statistical Data Science. You'll learn about continuous and discrete probability distributions, CLM, expected values, and more. ), Statistics: Statistical Data Science Track (B.S. This course overlaps significantly with the existing course 141 course which this course will replace. This is to indicate what the most important aspects are, so that you spend your time on those that matter most. If there is any cheating, then we will have an in class exam. I'm taking it this quarter and I'm pretty stoked about it. the URL: You could make any changes to the repo as you wish. Potential Overlap:This course overlaps significantly with the existing course 141 course which this course will replace. STA 142A. Discussion: 1 hour. It discusses assumptions in indicate what the most important aspects are, so that you spend your Open RStudio -> New Project -> Version Control -> Git -> paste the URL: https://github.com/ucdavis-sta141b-2021-winter/sta141b-lectures.git Choose a directory to create the project You could make any changes to the repo as you wish. like. ), Statistics: Statistical Data Science Track (B.S. STA 141C Computer Graphics ECS 175 Computer Vision ECS 174 Computer and Information Security ECS 235A Deep Learning ECS 289G Distributed Database Systems ECS 265 Programming Languages and. explained in the body of the report, and not too large. Copyright The Regents of the University of California, Davis campus. Keep in mind these classes have their own prereqs which may include other ECS upper or lower divisions that I did not list. We then focus on high-level approaches to parallel and distributed computing for data analysis and machine learning and the fundamental general principles involved. A tag already exists with the provided branch name. The A.B. Hes also teaching STA 141B for Spring Quarter, so maybe Ill enjoy him then as well . Nonparametric methods; resampling techniques; missing data. Learn more. By accepting all cookies, you agree to our use of cookies to deliver and maintain our services and site, improve the quality of Reddit, personalize Reddit content and advertising, and measure the effectiveness of advertising. I expect you to ask lots of questions as you learn this material. Illustrative reading: solves all the questions contained in the prompt, makes conclusions that are supported by evidence in the data, discusses efficiency and limitations of the computation. Summary of Course Content: Different steps of the data Numbers are reported in human readable terms, i.e. ), Statistics: Applied Statistics Track (B.S. In class we'll mostly use the R programming language, but these concepts apply more or less to any language. STA 137 and 138 are good classes but are more specific, for example if you want to get into finance/FinTech, then STA 137 is a must-take. High-performance computing in high-level data analysis languages; different computational approaches and paradigms for efficient analysis of big data; interfaces to compiled languages; R and Python programming languages; high-level parallel computing; MapReduce; parallel algorithms and reasoning. It moves from identifying inefficiencies in code, to idioms for more efficient code, to interfacing to compiled code for speed and memory improvements. Lingqing Shen: Fall 2018 undergraduate exchange student at UC-Davis, from Nanjing University. Goals:Students learn to reason about computational efficiency in high-level languages. This course explores aspects of scaling statistical computing for large data and simulations. The classes are like, two years old so the professors do things differently. is a sub button Pull with rebase, only use it if you truly new message. STA 013. . This course explores aspects of scaling statistical computing for large data and simulations. ECS 145 covers Python, but from a more computer-science and software engineering perspective than a focus on data analysis. Writing is clear, correct English. To fetch updates go to the git pane in RStudio click the "Commit" button and check the files changed by you This individualized program can lead to graduate study in pure or applied mathematics, elementary or secondary level teaching, or to other professional goals. Copyright The Regents of the University of California, Davis campus. ), Statistics: General Statistics Track (B.S. The B.S. Replacement for course STA 141. 10 AM - 1 PM. Statistics: Applied Statistics Track (A.B. You can view a list ofpre-approved courseshere. View Notes - lecture12.pdf from STA 141C at University of California, Davis. Summary of course contents: We also explore different languages and frameworks for statistical/machine learning and the different concepts underlying these, and their advantages and disadvantages. assignments. We also explore different languages and frameworks Catalog Description:High-performance computing in high-level data analysis languages; different computational approaches and paradigms for efficient analysis of big data; interfaces to compiled languages; R and Python programming languages; high-level parallel computing; MapReduce; parallel algorithms and reasoning. STA 131B: Introduction to Mathematical Statistics (4) a 'C-' or better in STA 131A or MAT 135A; instructor consent STA 141B: Data & Web Technologies for Data Analysis (4) a 'C-' or better in STA 141A STA 141C: Big Data & High Performance Statistical Computing (4) a 'C-' or better in STA 141B, or a 'C-' or better in STA 141A and ECS 32A Please They learn how and why to simulate random processes, and are introduced to statistical methods they do not see in other courses. Mon. Acknowledge where it came from in a comment or in the assignment. You can walk or bike from the main campus to the main street in a few blocks. Students will learn how to work with big data by actually working with big data. R is used in many courses across campus. Any violations of the UC Davis code of student conduct. . Twenty-one members of the Laurasian group of Therevinae (Diptera: Therevidae) are compared using 65 adult morphological characters. Learn more. This is to Variable names are descriptive. STA 141C was in R, and we focused on managing very big data and how to do stuff with it, as well as some parallel computing stuff and some theory behind it. Lecture: 3 hours All rights reserved. ECS 201B: High-Performance Uniprocessing. I took it with David Lang and loved it. It can also reflect a special interest such as computational and applied mathematics, computer science, or statistics, or may be combined with a major in some other field. For those that have already taken STA 141C, how was the class and what should I expect (I have Professor Lai for next quarter)? to use Codespaces. The prereqs for 142A are STA 141A and 131A/130A/MAT 135 while the prereqs for 142B are 142A and 131B/130B. Assignments must be turned in by the due date. Courses at UC Davis. If there were lines which are updated by both me and you, you The course covers the same general topics as STA 141C, but at a more advanced level, and includes additional topics on research-level tools. ), Statistics: Statistical Data Science Track (B.S. The report points out anomalies or notable aspects of the data Stack Overflow offers some sound advice on how to ask questions. STA 010. https://signin-apd27wnqlq-uw.a.run.app/sta141c/. type a short message about the changes and hit Commit, After committing the message, hit the Pull button (PS: there Hadoop: The Definitive Guide, White.Potential Course Overlap: STA 141B was in Python, where we learned web scraping, text mining, more visualization stuff, and a little bit of SQL at the end. Open the files and edit the conflicts, usually a conflict looks functions, as well as key elements of deep learning (such as convolutional neural networks, and Discussion: 1 hour, Catalog Description: This means you likely won't be able to take these classes till your senior year as 141A always fills up incredibly fast. The following describes what an excellent homework solution should look You signed in with another tab or window. J. Bryan, the STAT 545 TAs, J. Hester, Happy Git and GitHub for the Units: 4.0 We then focus on high-level approaches All STA courses at the University of California, Davis (UC Davis) in Davis, California. ), Statistics: Machine Learning Track (B.S. Former courses ECS 10 or 30 or 40 may also be used. Could not load tags. Program in Statistics - Biostatistics Track, Linear model theory (10-12 lect) (a) LS-estimation; (b) Simple linear regression (normal model): (i) MLEs / LSEs: unbiasedness; joint distribution of MLE's; (ii) prediction; (iii) confidence intervals (iv) testing hypothesis about regression coefficients (c) General (normal) linear model (MLEs; hypothesis testing (d) ANOVA, Goodness-of-fit (3 lect) (a) chi^2 test (b) Kolmogorov-Smirnov test (c) Wilcoxon test. I would take MAT 108 and MAT 127A for sure though if I knew I was trying to do a MSS or MSDS. Davis, California 10 reviews . Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Several new electives -- including multiple EEC classes and STA 131B,STA 141B and STA 141C -- have been added t Create an account to follow your favorite communities and start taking part in conversations. the bag of little bootstraps. ), Information for Prospective Transfer Students, Ph.D. Computing, https://rmarkdown.rstudio.com/lesson-1.html, https://github.com/ucdavis-sta141c-2021-winter/sta141c-lectures.git, https://signin-apd27wnqlq-uw.a.run.app/sta141c/, https://github.com/ucdavis-sta141c-2021-winter. As the century evolved, our mission expanded beyond agriculture to match a larger understanding of how we should be serving the public. Are you sure you want to create this branch? STA 141B: Data & Web Technologies for Data Analysis (4) a 'C-' or better in STA 141A STA 141C: Big Data & High Performance Statistical Computing (4) a 'C-' or better in STA 141B, or a 'C-' or better in STA 141A and ECS 32A Any MAT course numbered between 100-189, excluding MAT 111* (3-4) varies; see university catalog California'scollege town. I downloaded the raw Postgres database. Copyright The Regents of the University of California, Davis campus. ), Statistics: Applied Statistics Track (B.S. Learn low level concepts that distributed applications build on, such as network sockets, MPI, etc. The report points out anomalies or notable aspects of the data discovered over the course of the analysis. A tag already exists with the provided branch name. High-performance computing in high-level data analysis languages; different computational approaches and paradigms for efficient analysis of big data; interfaces to compiled languages; R and Python programming languages; high-level parallel computing; MapReduce; parallel algorithms and reasoning. Format: Graduate. Check regularly the course github organization Powered by Jekyll& AcademicPages, a fork of Minimal Mistakes. Potential Overlap:ECS 158 covers parallel computing, but uses different technologies and has a more technical, machine-level focus. Advanced R, Wickham. The town of Davis helps our students thrive. STA 141C - Big Data & High Performance Statistical ComputingSTA 144 - Sampling Theory of SurveysSTA 145 - Bayesian Statistical Inference STA 160 - Practice in Statistical Data Science STA 162 - Surveillance Technologies and Social Media STA 190X - Seminar sign in STA 141C Computational Cognitive Neuroscience . Coursicle. Subscribe today to keep up with the latest ITS news and happenings. For the STA DS track, you pretty much need to take all of the important classes. Prerequisite: STA 108 C- or better or STA 106 C- or better. UC Davis Veteran Success Center . They learn to map mathematical descriptions of statistical procedures to code, decompose a problem into sub-tasks, and to create reusable functions. Not open for credit to students who have taken STA 141 or STA 242. Check the homework submission page on Canvas to see what the point values are for each assignment. Work fast with our official CLI. STA 142 series is being offered for the first time this coming year. STA 141C. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. STA 013Y. Variable names are descriptive. No late assignments To make a request, send me a Canvas message with Stat Learning I. STA 142B. Format: Homework must be turned in by the due date. the bag of little bootstraps. Summary of course contents: If nothing happens, download Xcode and try again. The grading criteria are correctness, code quality, and communication. When I took it, STA 141A was coding and data visualization in R, and doing analysis based on our code and visuals. All rights reserved. But sadly it's taught in R. Class was pretty easy. A list of pre-approved electives can be foundhere. The ones I think that are helpful are: ECS 122A (possibly B), 130, 145, 158, 163, 165A (possibly B), 170, 171, 173, and 174. Nice! Nothing to show ), Statistics: Applied Statistics Track (B.S. If you receive a Bachelor of Science intheCollege of Letters and Science you have an areabreadth requirement. They will be able to use different approaches, technologies and languages to deal with large volumes of data and computationally intensive methods. ECS 221: Computational Methods in Systems & Synthetic Biology. View Notes - lecture9.pdf from STA 141C at University of California, Davis. The following describes what an excellent homework solution should look like: The attached code runs without modification. mid quarter evaluation, bash pipes and filters, students practice SLURM, review course suggestions, bash coding style guidelines, Python Iterators, generators, integration with shell pipeleines, bootstrap, data flow, intermediate variables, performance monitoring, chunked streaming computation, Develop skills and confidence to analyze data larger than memory, Identify when and where programs are slow, and what options are available to speed them up, Critically evaluate new data technologies, and understand them in the context of existing technologies and concepts. STA 141B: Data & Web Technologies for Data Analysis (4) a 'C-' or better in STA 141A STA 141C: Big Data & High Performance Statistical Computing (4) a 'C-' or better in STA 141B, or a 'C-' or better in STA 141A and ECS 32A Any MAT course numbered between 100-189, excluding MAT 111* (3-4) varies; see university catalog The lowest assignment score will be dropped. STA 141A Fundamentals of Statistical Data Science; prereq STA 108 with C- or better or 106 with C- or better. Additionally, some statistical methods not taught in other courses are introduced in this course. University of California, Davis Non-Degree UC & NUS Reciprocal Exchange Program Computer Science and Engineering. They will be able to use different approaches, technologies and languages to deal with large volumes of data and computationally intensive methods. At least three of them should cover the quantitative aspects of the discipline. advantages and disadvantages. Here is where you can do this: For private or sensitive questions you can do private posts on Piazza or email the instructor or TA. The course covers the same general topics as STA 141C, but at a more advanced level, and Feel free to use them on assignments, unless otherwise directed. If nothing happens, download GitHub Desktop and try again. As mentioned by another user, STA 142AB are two new courses based on statistical learning (machine learning) and would be great classes to take as well. We first opened our doors in 1908 as the University Farm, the research and science-based instruction extension of UC Berkeley. Game Details Date 3/1/2023 Start 6:00 Time 1:53 Attendance 78 Site Stanford, Calif. (Smith Family Stadium) Introduction to computing for data analysis and visualization, and simulation, using a high-level language (e.g., R). in Statistics-Applied Statistics Track emphasizes statistical applications. University of California, Davis, One Shields Avenue, Davis, CA 95616 | 530-752-1011. It enables students, often with little or no background in computer programming, to work with raw data and introduces them to computational reasoning and problem solving for data analysis and statistics. Program in Statistics - Biostatistics Track. I'm trying to get into ECS 171 this fall but everyone else has the same idea. ), Information for Prospective Transfer Students, Ph.D. If nothing happens, download GitHub Desktop and try again. ), Statistics: Machine Learning Track (B.S. technologies and has a more technical focus on machine-level details. ), Statistics: Statistical Data Science Track (B.S. Statistics drop-in takes place in the lower level of Shields Library. Lai's awesome. experiences with git/GitHub). Work fast with our official CLI. Applications of (II) (6 lect): (i) consistency of estimators; (ii) variance stabilizing transformations; (iii) asymptotic normality (and efficiency) of MLE; Statistics: Applied Statistics Track (A.B. ECS145 involves R programming. includes additional topics on research-level tools. Preparing for STA 141C. ECS 201C: Parallel Architectures. https://github.com/ucdavis-sta141c-2021-winter for any newly posted Prerequisite:STA 141B C- or better or (STA 141A C- or better, (ECS 010 C- or better or ECS 032A C- or better)). No more than one course applied to the satisfaction of requirements in the major program shall be accepted in satisfaction of the requirements of a minor. Career Alternatives ECS 145 covers Python, It's forms the core of statistical knowledge. clear, correct English. As for CS, I've heard that after you take ECS 36C, you theoretically know everything you need for a programming job. Choose one; not counted toward total units: Additional preparatory courses will be needed based on the course prerequisites listed in the catalog; e.g., Calculus at the level of, and Mathematical Statistics: Brief Course, and Introduction to Mathematical Statistics, Toggle Academic Advising & Student Services, Toggle Student Resource & Information Centers, Toggle Academic Information, Policies, & Regulations, Toggle African American & African Studies, Toggle Agricultural & Environmental Chemistry (Graduate Group), Toggle Agricultural & Resource Economics, Toggle Applied Mathematics (Graduate Group), Toggle Atmospheric Science (Graduate Group), Toggle Biochemistry, Molecular, Cellular & Developmental Biology (Graduate Group), Toggle Biological & Agricultural Engineering, Toggle Biomedical Engineering (Graduate Group), Toggle Child Development (Graduate Group), Toggle Civil & Environmental Engineering, Toggle Clinical Research (Graduate Group), Toggle Electrical & Computer Engineering, Toggle Environmental Policy & Management (Graduate Group), Toggle Gender, Sexuality, & Women's Studies, Toggle Health Informatics (Graduate Group), Toggle Hemispheric Institute of the Americas, Toggle Horticulture & Agronomy (Graduate Group), Toggle Human Development (Graduate Group), Toggle Hydrologic Sciences (Graduate Group), Toggle Integrative Genetics & Genomics (Graduate Group), Toggle Integrative Pathobiology (Graduate Group), Toggle International Agricultural Development (Graduate Group), Toggle Mechanical & Aerospace Engineering, Toggle Microbiology & Molecular Genetics, Toggle Molecular, Cellular, & Integrative Physiology (Graduate Group), Toggle Neurobiology, Physiology, & Behavior, Toggle Nursing Science & Health-Care Leadership, Toggle Nutritional Biology (Graduate Group), Toggle Performance Studies (Graduate Group), Toggle Pharmacology & Toxicology (Graduate Group), Toggle Population Biology (Graduate Group), Toggle Preventive Veterinary Medicine (Graduate Group), Toggle Soils & Biogeochemistry (Graduate Group), Toggle Transportation Technology & Policy (Graduate Group), Toggle Viticulture & Enology (Graduate Group), Toggle Wildlife, Fish, & Conservation Biology, Toggle Additional Education Opportunities, Administrative Offices & U.C. Canvas to see what the point values are for each assignment. The PDF will include all information unique to this page. STA 141C - Big Data & High Performance Statistical Computing Four of the electives have to be ECS : ECS courses numbered 120 to 189 inclusive and not used for core requirements (Refer below for student comments) ECS 193AB (Counts as one) - Two quarters of Senior Design Project (Winter/Spring) Course 242 is a more advanced statistical computing course that covers more material. ), Statistics: Computational Statistics Track (B.S. View full document STA141C: Big Data & High Performance Statistical Computing Lecture 1: Python programming (1) Cho-Jui Hsieh UC Davis April 4, 2017 STA 141B C- or better or (STA 141A C- or better, (ECS 010 C- or better or ECS 032A C- or better)). STA141C: Big Data & High Performance Statistical Computing Lecture 12: Parallel Computing Cho-Jui Hsieh UC Davis June 8, Oh yeah, since STA 141B is full for Winter Quarter, Im going to take STA 141C instead since the prereqs are STA 141B or STA 141A and ECS 32A at the same time. to use Codespaces. STA 141C Big Data & High Performance Statistical Computing Class Q & A Piazza Canvas Class Data Office Hours: Clark Fitzgerald ( rcfitzgerald@ucdavis.edu) Monday 1-2pm, Thursday 2-3pm both in MSB 4208 (conference room in the corner of the 4th floor of math building) The course will teach students to be able to map an overall statistical task into computer code and be able to conduct basic data analyses. 10 AM - 1 PM. moves from identifying inefficiencies in code, to idioms for more efficient code, to interfacing to ), Statistics: Computational Statistics Track (B.S. Computational reasoning, computationally intensive statistical methods, reading tabular and non-standard data. Using short snippets of code (5 lines or so) from lecture, Piazza, or other sources. STA 141C (Spring 2019, 2021) Big data and Statistical Computing - STA 221 (Spring 2020) Department seminar series (STA 2 9 0) organizer for Winter 2020 STA 141A Fundamentals of Statistical Data Science. ggplot2: Elegant Graphics for Data Analysis, Wickham. No description, website, or topics provided. Pass One & Pass Two: open to Statistics Majors, Biostatistics & Statistics graduate students; registration open to all students during schedule adjustment. I would pick the classes that either have the most application to what you want to do/field you want to end up in, or that you're interested in. Regrade requests must be made within one week of the return of the Information on UC Davis and Davis, CA. Currently ACO PhD student at Tepper School of Business, CMU. Statistical Thinking. Goals: All rights reserved. Minor Advisors For a current list of faculty and staff advisors, see Undergraduate Advising. STA 144. Parallel R, McCallum & Weston. STA 131A is considered the most important course in the Statistics major. analysis.Final Exam: STA 141A Fundamentals of Statistical Data Science. There was a problem preparing your codespace, please try again. ECS 222A: Design & Analysis of Algorithms. We'll use the raw data behind usaspending.gov as the primary example dataset for this class. You may find these books useful, but they aren't necessary for the course. No late homework accepted. . You signed in with another tab or window. Elementary Statistics. One approved course of 4 units from STA 199, 194HA, or 194HB may be used. Prerequisite:STA 108 C- or better or STA 106 C- or better. First offered Fall 2016. You're welcome to opt in or out of Piazza's Network service, which lets employers find you. The largest tables are around 200 GB and have 100's of millions of rows. These requirements were put into effect Fall 2019. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Course 242 is a more advanced statistical computing course that covers more material. Personally I'm doing a BS in stats and will likely go for a MSCS over a MSS (MS in Stats) and a MSDS. STA 141B was in Python, where we learned web scraping, text mining, more visualization stuff, and a little bit of SQL at the end. Program in Statistics - Biostatistics Track, MAT 16A-B-C or 17A-B-C or 21A-B-C Calculus (MAT 21 series preferred.). ), Information for Prospective Transfer Students, Ph.D. Go in depth into the latest and greatest packages for manipulating data. View Notes - lecture5.pdf from STA 141C at University of California, Davis. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. Stats classes: https://statistics.ucdavis.edu/courses/descriptions-undergrad. This is an experiential course. 2022 - 2022. Programming takes a long time, and you may also have to wait a long time for your job submission to complete on the cluster. STA 141C: Big Data & High Performance Statistical Computing (4) a 'C-' or better in STA 141B, or a 'C-' or better in STA 141A and ECS 32A Complete at least ONE of the following computational biology and bioinformatics courses: BIT 150: Applied Bioinformatics (4)* BIS 101; ECS 10 or ECS 15 or PLS 21; PLS 120 or STA 13 or STA 13Y or STA 100