Lecture: 3 hours course materials for UC Davis STA141C: Big Data & High Performance Statistical Computing. Feel free to use them on assignments, unless otherwise directed. 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. to use Codespaces. like. 2022-2023 General Catalog Introduction to computing for data analysis and visualization, and simulation, using a high-level language (e.g., R). 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. Nonparametric methods; resampling techniques; missing data. Plots include titles, axis labels, and legends or special annotations where appropriate. 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 Summary of course contents:This course explores aspects of scaling statistical computing for large data and simulations. STA 141A Fundamentals of Statistical Data Science. This is an experiential course. The report points out anomalies or notable aspects of the data discovered over the course of the analysis. ), Statistics: Statistical Data Science Track (B.S. ), Statistics: Statistical Data Science Track (B.S. Different steps of the data You signed in with another tab or window. The environmental one is ARE 175/ESP 175. compiled code for speed and memory improvements. Program in Statistics - Biostatistics Track. ECS145 involves R programming. Format: University of California, Davis, One Shields Avenue, Davis, CA 95616 | 530-752-1011. 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. ggplot2: Elegant Graphics for Data Analysis, Wickham. This is your opportunity to pursue a question that you are personally interested in as you create a public 'portfolio project' that shows off your big data processing skills to potential employers or admissions committees. Probability and Statistics by Mark J. Schervish, Morris H. DeGroot 4th Edition 2014, Pearson, University of California, Davis, One Shields Avenue, Davis, CA 95616 | 530-752-1011. When I took it, STA 141A was coding and data visualization in R, and doing analysis based on our code and visuals. Statistics: Applied Statistics Track (A.B. STA 131C Introduction to Mathematical Statistics. 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) ), Statistics: Computational Statistics Track (B.S. However, the focus of that course is very different, focusing on more fundamental computer science tasks and also comparing high-level scripting languages. STA 131A is considered the most important course in the Statistics major. is a sub button Pull with rebase, only use it if you truly Tables include only columns of interest, are clearly explained in the body of the report, and not too large. A list of pre-approved electives can be foundhere. You can view a list ofpre-approved courseshere. This feature takes advantage of unique UC Davis strengths, including . Work fast with our official CLI. The grading criteria are correctness, code quality, and communication. ), Statistics: Applied Statistics Track (B.S. This is the markdown for the code used in the first . Stat Learning II. We also explore different languages and frameworks for statistical/machine learning and the different concepts underlying these, and their advantages and disadvantages. to use Codespaces. 10 AM - 1 PM. Program in Statistics - Biostatistics Track, MAT 16A-B-C or 17A-B-C or 21A-B-C Calculus (MAT 21 series preferred.). View full document STA141C: Big Data & High Performance Statistical Computing Lecture 1: Python programming (1) Cho-Jui Hsieh UC Davis April 4, 2017 Highperformance computing in highlevel data analysis languages; different computational approaches and paradigms for efficient analysis of big data; interfaces to compiled languages; R and Python programming languages; highlevel parallel computing; MapReduce; parallel algorithms and reasoning. 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. 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. The report points out anomalies or notable aspects of the data This course teaches the fundamentals of R and in more depth that is intentionally not done in these other courses. 2022 - 2022. This course explores aspects of scaling statistical computing for large data and simulations. STA 135 Non-Parametric Statistics STA 104 . Use of statistical software. Check regularly the course github organization The course covers the same general topics as STA 141C, but at a more advanced level, and All rights reserved. If there were lines which are updated by both me and you, you ), Statistics: Machine Learning Track (B.S. ), Statistics: General Statistics Track (B.S. ECS 145 covers Python, Open RStudio -> New Project -> Version Control -> Git -> paste easy to read. Link your github account at ECS145 involves R programming. explained in the body of the report, and not too large. 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. experiences with git/GitHub). Oh yeah, since STA 141B is full for Winter Quarter, I'm going to take STA 141C instead since the prereqs are STA 141B or STA 141A and ECS 32A at the same time. Examples of such tools are Scikit-learn functions, as well as key elements of deep learning (such as convolutional neural networks, and long short-term memory units). The class will cover the following topics. Mon. Elementary Statistics. Preparing for STA 141C. Discussion: 1 hour. ), Statistics: Computational Statistics Track (B.S. Variable names are descriptive. Different steps of the data processing are logically organized into scripts and small, reusable functions. College students fill up the tables at nearby restaurants and coffee shops with their laptops, homework and friends. A.B. As for CS, I've heard that after you take ECS 36C, you theoretically know everything you need for a programming job. I recently graduated from UC Davis, majoring in Statistical Data Science and minoring in Mathematics. They develop ability to transform complex data as text into data structures amenable to analysis. School: UC Davis Course Title: STA 131 Type: Homework Help Professors: ztan, JIANG,J View Documents 4 pages STA131C_Assignment2_solution.pdf | Fall 2008 School: UC Davis Course Title: STA 131 Type: Homework Help Professors: ztan, JIANG,J View Documents 6 pages Worksheet_7.pdf | Spring 2010 School: UC Davis Branches Tags. If nothing happens, download GitHub Desktop and try again. ), Information for Prospective Transfer Students, Ph.D. ), Statistics: Statistical Data Science Track (B.S. Could not load branches. . We also take the opportunity to introduce statistical methods specifically designed for large data, e.g. 1. Title:Big Data & High Performance Statistical Computing Are you sure you want to create this branch? I downloaded the raw Postgres database. ECS 220: Theory of Computation. Community-run subreddit for the UC Davis Aggies! Adapted from Nick Ulle's Fall 2018 STA141A class. It moves from identifying inefficiencies in code, to idioms for more efficient code, to interfacing to compiled code for speed and memory improvements. This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. Prerequisite(s): STA 015BC- or better. They learn how and why to simulate random processes, and are introduced to statistical methods they do not see in other courses. 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. Programming takes a long time, and you may also have to wait a long time for your job submission to complete on the cluster. in Statistics-Applied Statistics Track emphasizes statistical applications. For the STA DS track, you pretty much need to take all of the important classes. These are comprehensive records of how the US government spends taxpayer money. 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 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. ), Statistics: General Statistics Track (B.S. Statistics 141 C - UC Davis. Career Alternatives They learn to map mathematical descriptions of statistical procedures to code, decompose a problem into sub-tasks, and to create reusable functions. We also explore different languages and frameworks STA141C: Big Data & High Performance Statistical Computing Lecture 5: Numerical Linear Algebra Cho-Jui Hsieh UC Davis April Potential Overlap:ECS 158 covers parallel computing, but uses different technologies and has a more technical, machine-level focus. Sampling Theory. ), Statistics: General Statistics Track (B.S. Testing theory, tools and applications from probability theory, Linear model theory, ANOVA, goodness-of-fit. My goal is to work in the field of data science, specifically machine learning. Replacement for course STA 141. STA 141C Big Data and High Performance Statistical Computing (4) Fall STA 145 Bayesian statistical inference (4) Fall STA 205 Statistical methods for research (4) . ECS classes: https://www.cs.ucdavis.edu/courses/descriptions/, Statistics (data science emphasis) major requirements: https://statistics.ucdavis.edu/undergrad/bs-statistical-data-science-track. Check that your question hasn't been asked. hushuli/STA-141C. 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