STAT11900 Introduction to Data Science II is also allowed to fulfill the introductory statistics prerequisite requirement. uuid:1773c52d-b262-11b2-0a00-70bcb8020000 Thursday: 11am (Xiaoan), 5pm (Owen, fundamental reviews) endobj This course introduces statistical techniques and methods of data analysis including the use of statistical software. Understand what gradients are and why they are necessary for ML to work via gradient descent. Mathematical Foundations of Machine Learning Understand the principles of linear algebra and calculus, which are key mathematical concepts in machine Exploring the Future of AI Through Science, Art, and Games Campus Events Oct 11, 2019. Stata computer package will be used extensively, but previous familiarity with Stata is not assumed. An approved substitute forSTAT22600 Analysis of Categorical Datais PBHS32700 Biostatistical Methods (also designated asSTAT22700 Biostatistical Methods),which requiresSTAT22400 Applied Regression Analysisas prerequisite and is offered by the Department of Public Health Sciences. The courses STAT22200 Linear Models and Experimental Design, STAT22400 Applied Regression Analysis(or STAT22401 Regression Analysis for Health and Social Research), Students may count either STAT 24400 or STAT 24410, but not both, toward the forty-two credits required for graduation. The minor in Statistics requires five courses, some prescribed and some elective, chosen in consultation with the Departmental Adviser for Minors. Statistical Theory and Methods Ia-IIa. Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar. 36 0 obj Previous knowledge of elementary differential equations is helpful but not required. WebSpring Quarter FINM 32000 - Options: Numerical Methods (100 units) - Markets FINM 32700 - Advanced Computing for Finance (100 units) - Computing Summer Quarter FINM 32950 - Introduction to HPC in Finance (50 units) - Machine Learning & Algorithms Concentration 3: Financial Data Science - 350 unit needed (900 available*) Autumn Quarter Other Prerequisites The course requires mathematical, algorithmic, and programming maturity. A program leading to the bachelor's degree in Statistics offers coverage of the principles and methods of statistics in combination with solid training in mathematics and computation. WebCMSC 35300 Mathematical Foundations of Machine Learning MACS 33002 Introduction to Machine Learning Elective courses Students must complete one of the following courses to fulfill the four-course requirement: PPHA 30560 Data Visualization ( not offered in 2022-2023) PPHA 34600 Program Evaluation PPHA 38829 Artificial Intelligence for Public Policy You train or deploy machine learning algorithms using high-level software libraries (e.g., scikit-learn, Keras, TensorFlow), and youd like to understand the principles underlying the abstractions so that you can expand your skills. Either of these is recommended as a three-quarter cognate sequence for students in the quantitative sciences and mathematics. Trustworthy Machine Learning. STAT24400-24500. 22501a4 yesterday. If MATH23500 Markov Chains, Martingales, and Brownian Motion is counted in place of STAT25100 Introduction to Mathematical Probability in the Statistics BA, then MATH23500 Markov Chains, Martingales, and Brownian Motion cannot also be counted as an elective in the Statistics BA. Through a series of hands-on applications, students will implement and evaluate the essential algorithms used to solve linear systems and least squares problems, perform regression, orthogonalize bases, decompose signals via the FFT and related transforms, and perform matrix factorizations. The Computer Science Major Adviser is responsible for approval of specific courses and sequences, and responds as needed to changing course offerings in our program and other programs. Introduction to Data Science I-II. Epidemiology is a quantitative field and draws on biostatistical methods. Fall 2017, ECE 8843/ISYE 8803/CS 8803, Mathematical Foundations of Machine Learning.
Foundations of Machine Learning fills the need for a general textbook that also offers theoretical details and an emphasis on proofs. 100 Units. STAT22810. 100 Units. Equivalent Course(s): STAT 31700. Prerequisite(s): STAT 24400 or STAT 24410 w/B- or better is required; alternatively STAT 22400 w/B+ or better and exposure to multivariate calculus (MATH 16300 or MATH 16310 or MATH 18400 or MATH 19520 or MATH 20000 or MATH 20500 or MATH 20510 or MATH 20800) and linear algebra (MATH 18600 or 19620 or 20250 or 20700 or STAT 24300 or equivalent). endobj Note: fundamental review sessions are not for homework help. Please consult the Departmental Adviser for Minors for approval of your minor program plan. Office hours: Wed 12:30-1:30PM Online via Zoom, Thu 8:30-9:30PM FAB 150 (or by appointment) STAT23400. Our assumption is that the reader is already familiar with the basic concepts of multivariable Machine learning topics include least squares classification and regression, ridge regression, principal components analysis, principal components regression, kernel methods, matrix completion, support vector machines, clustering, stochastic gradient descent, neural networks, and deep learning. Using Python, students will learn techniques for classification, prediction, inference, and regression. Oct. 15. Although the case studies are all in the area of statistical genetics, the statistical inference topics, which will include likelihood-based inference, linear mixed models, and restricted maximum likelihood, among others, are widely applicable to other areas. Saturday: 3pm (Zhisheng) The following policy applies to students who wish to receive a mark of I for a Statistics course. 1 0 obj
The BA or BS with honors is awarded to students with Statistics as their primary major who have a GPA of 3.25 or higher overall and 3.5 or higher in the courses in the major and also complete an approved honors paper (STAT29900 Bachelor's Paper). Extensive FOCS 2020, November 13, 2020. Equivalent Course(s): STAT 33600. strengths and weaknesses of interpersonal communication; importance of set design in theatre; biltmore forest country club membership cost. Students considering a major in Statistics are encouraged to begin with eitherSTAT24400-24500 Statistical Theory and Methods I-II or with the alternative sequence consisting of STAT25100 Introduction to Mathematical Probability (or STAT25150 Introduction to Mathematical Probability-A) followed by STAT24410-24510 Statistical Theory and Methods Ia-IIa, rather than with STAT23400 Statistical Models and Methods. This course introduces the leading statistical models and methods which financial data researchers use to understand ever-evolving markets and build insightful financial strategies, such as machine learning, risk calculation, and portfolio management . Equivalent Course(s): PBHS 32700. There I enriched my analytical skills with which I am confident I can 100 Units. 38 0 obj STAT11800-11900 Introduction to Data Science I-II has considerable overlap with STAT22000 Statistical Methods and Applications, but has a more computational and less mathematical emphasis than STAT22000 Statistical Methods and Applications. Instructor(s): M. WangTerms Offered: Spring ). Theoretical derivations will be presented with emphasis on motivations, applications, and hands-on data analysis. Terms Offered: Winter Using eigenvectors, SVD, and PCA, reduce the dimensionality of complex data to the most informative elements. Prerequisite(s): STAT 24500 or STAT 24510 or [STAT 27725 with a grade of B or higher]. Students with AP Statistics credit for STAT 22000 will forego that credit by completing STAT 23400. Computation will be done using Python and Jupyter Notebook. A score of 5 on the AP Statistics exam yields credit for STAT22000 Statistical Methods and Applications, although this credit will not count toward the requirements for a major or minor in Statistics. If MATH23500 Markov Chains, Martingales, and Brownian Motion is counted in place of STAT25100 Introduction to Mathematical Probability, then it cannot also count as an elective. This sequence provides a sophisticated introduction to statistical principles and methods and their application to the analysis of data. endobj Organizations from academia, industry, government, and the non-profit sector that collaborate with UChicago CS. Instructor(s): D. LauderdaleTerms Offered: Autumn Winter Time permitting, topics such as nonsmooth, integer, vector, and dynamic optimization may be briefly addressed.
For the BA in Statistics, STAT28000 Optimization counts as a List C elective. These three courses may be taken in any order after meeting the prerequisite of at least two quarters calculus and one of the introductory statistics courses: STAT22000 Statistical Methods and Applications,STAT23400 Statistical Models and Methods,STAT24500 Statistical Theory and Methods II,STAT24510 Statistical Theory and Methods IIa, or AP Statistics credit. Prerequisite: PBHS 32100.
WebAs part of the Data Science and Applied AI Postdoctoral Scholars program, postdocs will have the opportunity to work on collaborative projects in cutting-edge research areas. United States This course introduces the foundations of machine learning and provides a systematic view of a range of machine learning algorithms. Linear classifiers Instructor(s): K. BurbankTerms Offered: Winter Students will acquire a foundation in data investigation and exploration, as well as supervised and unsupervised learning. The final grade will be allocated to the different components as follows: Homework (50% UG, 40% G): There are roughly weekly homework assignments (about 8 total). 25 0 obj Equivalent Course(s): DATA 27420. No courses in the Statistics minor can be double counted with the student's major(s), other minors, or general education requirements. Note(s): For students with little or no math background. Students should consult the major adviser with questions about specific courses the We will use R and RStan to implement these methods and solve real world problems. B+: 87% or higher This course covers statistical methods for the analysis of qualitative and counted data. Statistical Theory and Methods Ia. Additional topics may include bootstrapping for regression models, nonparametric regression, and regression models with correlated errors. Additional topics may include diagnostic plots, bootstrapping, a critical comparison of Bayesian and frequentist inference, and the role of conditioning in statistical inference. Students from 11 different majors, including all four collegiate divisions, have chosen a data science minor. Introduction to Random Matrices. The new major is part of the University of Chicago Data Science Initiative, a coordinated, campus-wide plan to expand education, research, and outreach in this fast-growing field. Used C# to code first known algorithm to automate soot particle levitation + graphic
The coverage of topics in probability is limited and brief, so students who have taken a course in probability find reinforcement rather than redundancy. STAT24410-24510 Statistical Theory and Methods Ia-IIa is particularly well-suited for students with a strong mathematical background who are interested in more extensive coverage of probability and statistics. A student with a strong computer science background could takeSTAT27700 Mathematical Foundations of Machine Learning and STAT27725 Machine Learning. STAT24400-24500 Statistical Theory and Methods I-II or STAT24410-24510 Statistical Theory and Methods Ia-IIa. Topics covered include two parts: (1) a gentle introduction of machine learning: generalization and model selection, regression and classification, kernels, neural networks, clustering and dimensionality reduction; (2) a statistical perspective of machine learning, where we will dive into several probabilistic supervised and unsupervised models, including logistic regression, Gaussian mixture models, and generative adversarial networks. Logistic regression WebThe best place to start is this page and the Joint BX/MS in CS catalog page. Develops data-driven systems that derive insights from network traffic and explores how network traffic can reveal insights into human behavior. This course on Mathematical Foundations of Machine Learning is complete, but we want to add supplementary information from relevant areas outside of math in the future, such as probability, statistics, data structures, algorithms, and optimization. Terms Offered: Autumn 2023 Python for Machine Learning: A Step-by-Step Guide, The Complete 2023 SQL Bootcamp : Go from Zero to Hero, ChatGPT to Supercharge Your Public Relations Media Training, NodeJs API Project: School Management System API course 2023, English Grammar And Speaking Patterns (You MUST Know These! But the Introduction to Data Science sequence changed her view. 100 Units. Instead of tutoring or lecturing, Team Leaders coach students as they work collaboratively in small groups on the assigned problems by referencing class lectures and assigned reading materials. 
Meeting time: Tue/Thu 6:40-8:30PM, FAB 150. Overall, it is an excellent book for machine learning graduate students who have to lay a theoretical foundation for their research. Incisive writing, rigorous yet accessible proofs, carefully chosen notation and a wonderful choice of topics. This field is for validation purposes and should be left unchanged. Candidates for either the BA or the BS are required to take CMSC14100 Introduction to Computer Science I-CMSC14200 Introduction to Computer Science II. <>3]/P 6 0 R/Pg 40 0 R/S/Link>> Regression Analysis for Health and Social Research. This course is only open to graduate students in Statistics, Applied Mathematics, and Financial Mathematics, and to undergraduate Statistics majors, or by consent of instructor. UChicago CS/TTIC Machine Learning Seminar Series . Nonparametric inference is about developing statistical methods and models that make weak assumptions. This term we will be using Piazza for class discussion. To be considered, students should have completed almost all of their undergraduate requirements, including all of their general education and language competence requirements, by the end of their third year. <>/Border[0 0 0]/Contents(http://library.usu.edu/)/Rect[378.0 102.1947 378.0 115.0853]/StructParent 9/Subtype/Link/Type/Annot>> Topics include the examination of residuals, the transformation of data, strategies and criteria for the selection of a regression equation, the use of dummy variables, tests of fit. STAT22200 Linear Models and Experimental Design,STAT22400 Applied Regression Analysis, andSTAT22600 Analysis of Categorical Datamay be taken in any order after meeting the prerequisite of at least two quarters calculus and introductory statistics:STAT22000 Statistical Methods and Applications,STAT23400 Statistical Models and Methods,STAT24500 Statistical Theory and Methods II, STAT24510 Statistical Theory and Methods IIa, or AP credit forSTAT22000 Statistical Methods and Applications.
This sequence is a systematic introduction to the principles and techniques of statistics, as well as to practical considerations in the analysis of data, with emphasis on the analysis of experimental data. Machine Learning. Generally, no more than two electives may be satisfied by courses offered by departments other than the Department of Statistics. All implementations will be done using Python.
The purpose of this course is to provide a mathematically rigorous introduction to these developments with emphasis on methods and their analysis. <>37 0 R]/P 6 0 R/S/Link>> In many applications of statistics, a large proportion of the questions of interest are about causality rather than questions of description or association. Only one of STAT 20000, STAT 20010, or STAT 22000, can count toward the general education requirement in the mathematical sciences. This course focuses on applications and techniques for analysis of multivariate and high dimensional data. Yibi HuangJones 207773.702.2519Email, Undergraduate Program ChairProf. No matter where I go after graduation, I can help make sense of chaos in whatever kind of environment I'm working in.. The class will rigorously build up the two pillars of modern machine learning: linear algebra and probability. Matlab, Python, Julia, R). WebCode. STAT24400-24500 Statistical Theory and Methods I-II is recommended for students who wish to have a thorough introduction to statistical theory and methodology. STAT27850. Aug 2022 - Feb 20237 months. 2021-10-05T12:37:04-07:00 When the major launched last fall, Elmasry and Hayward immediately signed up, participating in the Data Appligent AppendPDF Pro 6.3 WebThe core of the Statistics major consists of three courses: STAT 25100 Introduction to Mathematical Probability (or STAT 25150 Introduction to Mathematical Probability-A) and either STAT 24400-24500 Statistical Theory and Methods I-II or STAT 24410-24510 Statistical Theory and Methods Ia-IIa. Neither STAT20000 Elementary Statistics nor STAT20010 Elementary Statistics Through Case Study may be taken by students with credit for Interested students are strongly encouraged to consult both the Departmental Adviser for Majors and their College adviser early in their third year. Matrix notation is introduced as needed. Its really inspiring that I can take part in a field thats rapidly evolving.. Unsupervised learning and clustering The focus is on theory and practice of linear models, including the analysis of variance, regression, correlation, and some multivariate analysis. application/pdf 33 0 obj <>13]/P 21 0 R/Pg 40 0 R/S/Link>> The Neumann network architecture outperforms traditional inverse problem solution methods, model-free deep learning approaches, and state-of-the-art unrolled iterative methods on standard datasets. STAT11900 Introduction to Data Science II can only be used as an elective in the Statistics minor if the student also completes STAT11800 Introduction to Data Science I (which cannot be included in a Statistics minor). Many other graduate courses in Statistics offer opportunities for further study of statistical theory, methods, and applications. Students may count eitherSTAT22600 Analysis of Categorical DataorSTAT22700 Biostatistical Methods, but not both, toward the Statistics minor. Students are encouraged to obtain course advising early from the Departmental Adviser for Minors. Instructor(s): StaffTerms Offered: Autumn Matlab, Python, Julia, or R). STAT11900 Introduction to Data Science II, but not STAT11800 Introduction to Data Science I, can be used as an elective in the minor in Statistics. Prerequisite(s): Consent of faculty adviser and Departmental Adviser for Majors Equivalent Course(s): STAT 30030. Students with at least MATH13100 Elem Functions and Calculus I or placement into MATH15200 Calculus IIor higher are encouraged to take STAT22000 Statistical Methods and Applications instead of either STAT20000 Elementary Statistics or STAT20010 Elementary Statistics Through Case Study. Instructor(s): V. VeitchTerms Offered: Autumn Candidates for the BS are required to take four electives. Lecture 2: Vectors and Matrices notes, video, Lecture 3: Least Squares and Geometry notes, video, Lecture 4: Least Squares and Optimization notes, video, Lecture 5: Subspaces, Bases, and Projections notes, video, Lecture 6: Finding Orthogonal Bases notes, video, Lecture 7: Introduction to the Singular Value Decomposition notes, video, Lecture 8: The Singular Value Decomposition notes, video, Lecture 9: The SVD in Machcine Learning notes, video, Lecture 10: More on the SVD in ML (Including Matrix Completion) notes, video, Lecture 11: PageRank and Ridge Regression notes, video, Lecture 12: Kernel Ridge Regression notes, video, Lecture 13: Support Vector Machines notes, video, Lecture 14: Basic Convex Optimization notes, video, Lecture 15: Stochastic Gradient Descent notes, video, Lecture 17: Clustering and K-means notes, video. Pathways in Data Science. endobj (These deadlines assume that the student is graduating in Spring Quarter of fourth year. History of Statistics. The major can provide appropriate preparation for graduate study in statistics or in other subjects with strong quantitative components. Sunday: 1pm (Yuxin). Note(s): Students may count either STAT 22000 or STAT 23400, but not both, toward the forty-two credits required for graduation. Calculate the area under any curve using integral calculus. Because of the interdisciplinary nature of the field of statistics, other departments and committees offercourses approved for use as electives for the Statistics minor. Multiple Testing, Modern Inference, and Replicability. endobj WebSave The Date for MMLS 2023. IfSTAT22200 Linear Models and Experimental Designis used to fulfill a requirement of the Statistics minor, thenSTAT22600 Analysis of Categorical Datamay be used as an elective in the minor. The major program includes four additional prescribed mathematics courses, four prescribed statistics courses, and two prescribed computer science courses. Numerical Linear Algebra: An Introduction to Computation. C+: 77% or higher Stephen Tu (Google)- The foundations of machine learning for feedback control Date & Time: April 6, 2023 2:00 pm 3:00 pm Location: Crerar 298, 5730 S. Ellis I had always viewed data science as something very much oriented toward people passionate about STEM, but the data science sequence really framed it as a tool that anyone in any discipline could employ, to tell stories using data and uncover insights in a more quantitative and rigorous way.. Since it was introduced in 2019, the data science minor has drawn interest from UChicago students across disciplines. For students interested in continuing their study of statistics beyond the introductory level, , only one of these two courses, not both, may be counted toward a major or minor in Statistics. Terms Offered: Spring Biostatistical Methods. The four prescribed Statistics courses are, as their first course in probability and statistics.
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And why they are necessary for ML to work via gradient descent and provides a systematic view a.This course may not be used in the Statistics major or minor. %PDF-1.7 % Among those hundreds of students will be the first two recipients of the new undergraduate data science degree, Noor Elmasry and Alex Hayward. We expect this option to be attractive to a fair number of students from every major at UChicago, including the humanities, social sciences and biological sciences.. 40 0 obj By This course consists of reading and research in an area of statistics or probability under the guidance of a faculty member in the Department of Statistics, leading to a bachelor's paper. Note(s): Coding in R will be heavily involved in this class. Students should enroll in the relevant Department of Statistics course number when available. Terms Offered: Winter endobj In other words, for the BS, students cannot double-count STAT28000 Optimization toward both the four-elective requirement and the requirement to take at least one of STAT28000 Optimization and MATH21100 Basic Numerical Analysis. 100 Units. Sequences in which earlier courses are prerequisites for later ones are preferred. 100 Units. <>
STAT24300. To be considered, students should have completed almost all of their undergraduate requirements, including all of their general education and language competence requirements, by the end of their third year.
