with Computer Science moving into applications in the real world and involving large quantities of data, uncertainty and random variations become increasingly important aspects to be considered when designing algorithms, addressing large scale problems, modeling processes, or evaluating data. To do this, probabilistic methods for data analysis and modeling become essential tools within every branch of Computer Science.
This course briefly covers basic statistics and probability concepts and introduces techniques to model and analyze probabilistic data. This includes basic representation such as Bayesian networks as well as hypothesis testing techniques for data analysis and interpretation. Further, it introduces modeling and analysis techniques for sequential processes, including Markov models, regression analysis, and basic queueing models. All of these techniques will be discussed in the context of common Computer Science problems from a wide range of fields, including Computer Networks, Artificial Intelligence, Machine Learning, Computer Vision, Data Mining, Bioinformatics, etc. In addition, the course will discus selected advanced topics and applications such as capacity planning and bottleneck analysis, clustering and classification
Students successfully completing this course will have gained a solid understanding of probabilistic data modeling, interpretation, and analysis an thus have formed an important basis for more advanced courses in Computer Science as well as for the handling and analysis of data used in real-life applications and research.
All students are expected to have a background in basic probability, Calculus, and Algebra before attending this course. In particular, students should have passed the courses Engineering Probability (IE 3301), Algorithms and Data Structures (CSE 2320), Calculus II (Math 2425), and Differential Equations & Linear Algebra (Math 3319) or an equivalent. In case of questions, students should seek the consent of the instructor to attend the course.
There are a wide range of books on this topic, all of which cover many of topics covered in the course and can be used as references for the course. However, none of them covers everything in the course. As a consequence the course does not follow any one specific textbook. However, book recommendations will be made throughout the course and corresponding books will be made available in the Engineering Library Reserve.
Additional course materials will be available electronically or through the reserve section in the Engineering Library. Also, changes, if any, will be announced by e-mail.
Homework assignments in the course will contain programming components. The choice of programming language is left to the student. However, in some assignments simulation and data generation components might be provided which will be implemented in C or C++. These components will not be provided in additional languages and thus interfacing with C or C++ (which is possible in most programming languages) might be necessary when a different programming language is used. In all cases, the following limitation will apply to the programming language chosen: All programs must compile and run on university machines (either university servers or the machines in the open OIT laboratories) and instructions regarding how to compile and run the code must be provided with the program submission. In case of doubts regarding the use of a particular programming language or software package, contact the instructor prior to its use.
There is a course web page at http://ranger.uta.edu/
huber/cse5301 . All
changes and supplementary course materials will be
available from this site. In addition, necessary
changes or important announcements will also be
distributed by e-mail. In order to receive
class-related messages you have to send an e-mail to
the instructor (huber@cse.uta.edu).
Office hours for the course will be held by the instructor in ERB 128 or ERB 522,
M 6:00 - 7:00, Tu 2:30 - 3:20, and Th 5:00-6:00pm. The first office hours will be held on Thursday, January 19. Times are subject to change and will be posted.
If for some reason you can not make it to any
of these office hours, please inform the
instructor.
e-mail: huber@cse.uta.edu