CS HA. Senior Honors Thesis Research. Catalog Description: Thesis work under the supervision of a faculty member. To obtain credit the student must, at the end of two semesters, submit a satisfactory thesis to the Electrical Engineering and Computer Science department archive. A Five-Year BS/MS. The Five-Year Bachelor/Master Program, called the 5th Year MS Program for short, offers qualified Berkeley EECS and L&S Computer Science undergraduate students a unique opportunity to begin graduate study immediately after graduation, thereby accelerating the master's degree by requiring only one additional year beyond the bachelor's degree Ryan Theisen (PhD student, UC Berkeley) Feynman Liang (PhD student, UC Berkeley) Amir Gholaminejad (postdoc, UC Berkeley, present, joint w. K. Keutzer) Former Students and Postdocs. Zhenyu Liao (postdoc, UC Berkeley, ; now faculty at Huazhong) Jianfei Chen (postdoc, UC Berkeley, , joint w. J. Gonzalez; now faculty at
CS Courses | EECS at UC Berkeley
Catalog Description: Foundations of data science from three perspectives: inferential thinking, computational thinking, and real-world relevance. Given data arising from some real-world phenomenon, how does one analyze that data so as to understand that phenomenon? The course teaches critical concepts and skills in computer programming and statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, document collections, geographical data, and social networks.
It delves into social and legal issues surrounding data analysis, including issues of privacy and data ownership. Units: 4. Emphasizes the use of computation to gain insight about quantitative problems with real data. Expressions, data types, collections, and tables in Python. Programming practices, abstraction, and iteration.
Visualizing univariate and bivariate data with bar charts, histograms, plots, and maps. Introduction to statistical concepts including averages and distributions, predicting one variable from another, berkeley eecs phd thesis, association and causality, probability and probabilistic simulation.
Relationship between numerical functions and graphs. Sampling and introduction to inference. Units: 3. Catalog Description: Introduction to the constructs in the Matlab programming language, aimed at students who already know how to program. Array and matrix operations, functions and function handles, control flow, plotting and image manipulation, berkeley eecs phd thesis, cell arrays and structures, and the Symbolic Mathematics toolbox.
Units: 2. Catalog Description: Self-paced course in the C programming language for students who already know how to program. Computation, input and output, flow of control, functions, arrays, berkeley eecs phd thesis, and pointers, linked structures, use of dynamic storage, and implementation of abstract data types.
Catalog Description: Self-paced course in functional programming, using the Scheme programming language, for students who already know how to program. Recursion; higher-order functions; list processing; implementation of rule-based querying.
Catalog Description: Use of UNIX utilities and scripting facilities for customizing the programming environment, organizing files possibly in more than one computer accountimplementing a personal database, reformatting text, and searching for online resources. Catalog Description: Self-paced course in Java for students who already know how to program. Applets; variables and computation; events and flow of control; classes and objects; inheritance; GUI elements; applications; arrays, strings, files, and linked structures; exceptions; threads.
Catalog Description: Introduction to the constructs provided in the Python programming language, aimed at students berkeley eecs phd thesis already know how to program. Flow of control; strings, tuples, lists, and dictionaries; CGI programming; file input and output; object-oriented programming; GUI elements. Catalog Description: An introductory course for students with minimal prior exposure to computer science.
Prepares students for future computer science courses and empowers them to utilize programming to solve problems in their field of study. Presents an overview of the history, great principles, and transformative applications of computer science, as well as a comprehensive introduction to programming.
Topics include abstraction, recursion, algorithmic complexity, higher-order functions, berkeley eecs phd thesis, concurrency, social implications of computing privacy, education, algorithmic biasand engaging research areas data science, AI, HCI, berkeley eecs phd thesis. Students will program in Snap! a friendly graphical language and Python, and will design and implement two projects of their choice.
Catalog Description: This course meets the programming prerequisite for 61A. An introduction to the beauty and joy of computing. The history, social implications, great principles, and future of computing.
Beautiful applications that have changed the world. How computing empowers discovery and progress in other fields. Relevance of computing to the student and society will be emphasized. Students will learn the joy of programming a computer using a friendly, graphical language, and will complete a substantial team programming project related to their interests. Catalog Description: The Freshman Seminar Program has been designed to provide new students with the opportunity to explore an intellectual topic with a faculty member berkeley eecs phd thesis a small-seminar setting.
Freshman seminars are offered in all campus departments, and topics vary from department to department and semester to semester. Enrollment limited to 15 freshmen. Units: 1. Catalog Description: Computer Science 36 is a seminar for CS Scholars who are concurrently taking CS61A: The Structure and Interpretation of Computer Programs. CS Scholars is a cohort-model program to provide support in exploring and potentially declaring a CS major for students with little to no computational background prior to coming to the university.
CS 36 provides an introduction to the CS curriculum at UC Berkeley, berkeley eecs phd thesis, and the overall CS landscape in both industry and academia—through the lens of accessibility and its relevance to diversity. Catalog Description: Freshman and sophomore seminars offer lower division students the opportunity to explore an intellectual topic with a faculty member and a group of peers in a berkeley eecs phd thesis setting.
These seminars are offered in all campus departments; topics vary from department to department and from semester to semester. Enrollment limits are set by the faculty, but the suggested limit is Catalog Description: Implementation of generic operations.
Streams and berkeley eecs phd thesis. Implementation techniques for supporting functional, object-oriented, and constraint-based programming in the Scheme programming language. Together with 9D, 47A constitutes an abbreviated, self-paced version of 61A for students who have already taken a course equivalent to 61B.
Catalog Description: Iterators. Hashing, applied to strings and multi-dimensional structures. Storage management. Design and implementation of a program containing hundreds of lines of code. Students who have completed a portion of the subject matter of COMPSCI 61B may, with consent of instructor, complete COMPSCI 61B in this self-paced course.
Please note that students in the College of Engineering are required to receive additional permission from the College as well as the EECS department for the course to count in place of COMPSCI 61B. Catalog Description: MIPS instruction set simulation. The assembly and linking process. Caches and virtual memory. Pipelined computer organization. Students with sufficient partial credit in 61C may, with consent of instructor, complete the credit in this self-paced course.
Catalog Description: An introduction to programming and computer science focused on abstraction techniques as means to manage program complexity.
Techniques include procedural abstraction; control abstraction using recursion, higher-order functions, generators, and streams; data abstraction using interfaces, objects, classes, and generic operators; and language abstraction using interpreters and macros.
The course exposes students to programming paradigms, including functional, object-oriented, and declarative approaches. It includes an introduction to asymptotic analysis of algorithms. There are several significant programming projects. Catalog Description: Introductory programming and computer science. Abstraction as means to control program complexity.
Control abstraction: recursion and higher order functions. Introduction to asymptotic analysis of algorithms. Data abstraction: abstract data types, type-tagged data, first class data types, sequences implemented as lists and as arrays, generic operators implemented with data-directed programming and with message passing.
Implementation of object-oriented programming with closures over dispatch procedures. Introduction to berkeley eecs phd thesis and compilers. Course may be completed in one or two semesters. Students must complete a mimimum of two units during their first semester of 61AS. Units: Catalog Description: Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables.
Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language. Catalog Description: The same material as in 61B, but in a laboratory-based format. Catalog Description: Identical to CS61B, but in an online format. Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables, berkeley eecs phd thesis.
Catalog Description: The internal organization and operation of digital computers. Elements of computer logic design. Tradeoffs involved in fundamental architectural design decisions.
Catalog Description: The same material as in 61C but in a lab-centric format. Catalog Description: Logic, infinity, and induction; applications include undecidability and stable marriage problem.
Modular arithmetic and GCDs; applications include primality testing and cryptography. Polynomials; examples include error correcting codes and interpolation. Probability including sample spaces, independence, random variables, berkeley eecs phd thesis, law of large numbers; examples include load balancing, existence arguments, Bayesian inference.
Catalog Description: Development of Computer Science topics appearing in Foundations of Data Science C8 ; expands computational concepts and techniques of abstraction. Understanding the structures that underlie the programs, algorithms, and languages used in data science and elsewhere, berkeley eecs phd thesis. Mastery of a particular programming language while studying general techniques for managing program berkeley eecs phd thesis, e.
Provides practical experience with composing larger systems through several significant programming projects. Catalog Description: Topics will vary semester to semester.
UC Berkeley EECS PhD留學心得分享會_上半場
, time: 36:29Electrical Engineering and Computer Sciences < University of California, Berkeley
Five-Year BS/MS. The Five-Year Bachelor/Master Program, called the 5th Year MS Program for short, offers qualified Berkeley EECS and L&S Computer Science undergraduate students a unique opportunity to begin graduate study immediately after graduation, thereby accelerating the master's degree by requiring only one additional year beyond the bachelor's degree However, terminal master’s students in the EECS Department must apply through regular admission should they also wish to receive PhD degree from the EECS Department. UC Berkeley graduate students who are not in the EECS Department, must apply through regular admission to add an MS or a PhD degree from the EECS Department Oct 22, · EECS alumna Melody Ivory (M.S. /Ph.D. , advisor: Marti Hearst), the first Black woman to earn a doctorate in Computer Science at UC Berkeley, has been chosen as the keynote speaker who will close the 5th Annual Women in Tech Symposium, hosted at Berkeley on March 12, This year's symposium has the theme "The New Era in Human
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