| Term |
Course Title and Course Number |
Insturctor |
Number of Units |
Textbook |
Note |
| Spring 2021 |
Math 202B: Introduction to Topology and Analysis (Second Course) |
Prof. Michael Christ |
4 |
- Gerald Folland, Real Analysis: Modern Techniques and Their Applications
|
Second course of Berkeley graduate sequence in analysis.
Mainly covers Lebesgue theory in n-dimensions and functional analysis. |
| Spring 2021 |
COMPSCI 189: Introduction to Machine Learning |
Prof. Jonathan Shewchuk |
4 |
- [JWHT] An Introduction to Statistical Learning
- [HTF] The Elements of Statistical Learning
|
Fundamental machine learning techniques: regression methods, GDA, decision trees
/ random forests,
(convolutional) neural networks, dimensionality reduction, clustering. |
| Spring 2021 |
DATA 100: Principles and Techniques of Data Science |
Prof. Joseph E. Gonzalez et al. |
4 |
|
Data cleaning, data visualization, introductory machine learning techniques. |
| Spring 2021 |
Math 185: Complex Analysis |
Prof. Di Fang |
4 |
- [BC] Complex Variables and Applications
|
Analytic functions of a complex variable. Cauchy's integral theorem, power series, Laurent series,
singularities of analytic functions, the residue theorem with application to definite integrals. Some
additional topics such as conformal mapping. |
| Fall 2020 |
Math 202A: Introduction to Topology and Analysis (First Course) |
Prof. Alan Hammond |
4 |
- Richard F. Bass, Real Analysis for Graduate Students
- Patrick Billingsley, Probability and measure
- Gerald Folland, Real Analysis: Modern Techniques and Their Applications
- Terrence Tao, An Introduction to Measure Theory
|
First course of Berkeley graduate sequence in analysis.
Mainly covers introductory measure theory. |
| Fall 2020 |
Math 222A: Partial Differential Equations (First Course) |
Prof. Daniel Tataru |
4 |
- Lawrence C. Evans, Partial differential equations
- [FJ], Introduction to the
Theory of Distributions
- Lars Hörmander, The Analysis of
Linear Partial Differential Operators
- Robert Strichartz, A Guide to Distribution
Theory and Fourier Transforms
|
First course of Berkeley graduate sequence in partial differential equations.
Mainly covers introductory theory of
distributions and functional analysis of PDEs. |
| Fall 2020 |
STAT 243: Introduction to Statistical Computing |
Chris Paciorek |
4 |
- [NR], Learning the bash Shell
- Joseph Adler, R in a Nutshell
- Hadley Wickham, Advanced R
- James E. Gentle, Computational Statistics
|
Concepts in statistical programming and statistical computation,
including programming principles, data and text manipulation, parallel processing,
Monte-Carlo simulation, numerical linear algebra, and optimization. |
| Spring 2020 |
EECS 126: Probability and Random Processes |
Prof. Kannan Ramchandran
|
4 |
- [BT], Introduction to Probability, 2nd Edition (2008)
- [W] Probability in Electrical Engineering and Computer Science:
An Application-Driven Course (2014)
|
This course covers the fundamentals of probability and random processes useful in fields such as
networks,
communication, signal processing, and control. Sample space, events, probability law.
Conditional probability. Independence. Random variables. Distribution, density functions.
Random vectors. Law of large numbers. Central limit theorem. Estimation and detection.
Markov chains. |
| Spring 2020 |
MATH 221: Advanced Matrix Computations |
Prof. James Demmel
|
4 ( view project ) |
- [J. Demmel], Applied Numerical Linear Algebra (1997)
|
Direct solution of linear systems, including
large sparse systems: error bounds, iteration methods,
least square approximation, eigenvalues and eigenvectors
of matrices, nonlinear equations, and minimization of functions. |
| Spring 2020 |
MATH 228B: Numerical Solution to Partial Differential Equations |
Prof. Sunčica Čanić
|
4 (A+) |
- [R. J. LeVeque], Finite Difference Methods for Ordinary
and Partial Differential Equations,
Steady State and Time Dependent Problems (2007)
- [R. J. LeVeque], Finite Volume Methods for Hyperbolic Problems (2002)
- [C. Johnson], Numerical Solution of Partial
Differential Equations by the Finite Element Method (2009)
|
Theory and practical methods for numerical solution of partial differential
equations. Finite difference methods for elliptic, parabolic
and hyperbolic equations, stability, accuracy and convergence,
von Neumann analysis and CFL conditions. Finite volume methods
for hyperbolic conservation laws, finite element methods for
elliptic and parabolic equations, discontinuous Galerkin methods
for conservation laws. Other topics include applications of the
techniques to a range of problems. |
| Fall 2019 |
COMPSCI 61B: Data Structures |
Prof. Paul Hilfinger
|
4 (A+) |
- [Paul N. Hilfinger], A Java Reference
- [Sierra & Bates], Head First Java
- [Paul N. Hilfinger], Data Structures (Into Java)
|
Fundamental dynamic data structures,
including linear lists, queues,
trees, and other linked structures;
arrays strings, and hash tables.
Storage management. Elementary
principles of software engineering.
Abstract data types. Algorithms for
sorting and searching. Introduction
to the Java programming language. |
| Fall 2019 |
MATH 104: Introduction to Mathematical Analysis |
Prof. Rui Wang
|
4 |
- [Rudin], Principles of mathematical analysis
|
The real number system. Sequences, limits,
and continuous functions in R and R.
The concept of a metric space. Uniform
convergence, interchange of limit operations.
Infinite series. Mean value theorem and applications.
The Riemann integral. |
| Fall 2019 |
MATH 228A: Numerical Solution to Ordinary Differential Equations |
Prof. Lin Lin |
4 |
- [R.J. LeVeque] Finite Difference Methods
for Ordinary and Partial Differential
Equations: Steady-State and Time-dependent Problems
- [R.J. LeVeque] A First Course in
the Numerical Analysis of Differential Equations
- [Syvert Paul Nørsett,
Gerhard Wanner, Ernst Hairer] Solving
Ordinary Differential Equations I: Nonstiff Problems
|
Ordinary differential equations: Runge-Kutta
and predictor-corrector methods; stability
theory, Richardson extrapolation, stiff equations,
boundary value problems. Partial differential
equations: stability, accuracy and convergence,
Von Neumann and CFL conditions, finite difference
solutions of hyperbolic and parabolic equations.
Finite differences and finite element solution
of elliptic equations. |
| Spring 2019 |
COMPSCI 61A: Struture and Interpretation of Computer Programs |
Prof. Daniel Garcia
|
4 |
|
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. |
| Spring 2019 |
MATH 113: Abstract Algebra |
Prof. Sylvie Corteel
|
4 |
- [John B. Fraleigh] A First Course in Abstract Algebra
|
Sets and relations. The integers, congruences, and the Fundamental Theorem of Arithmetic. Groups and
their factor groups. Commutative rings, ideals, and quotient fields. The theory of polynomials:
Euclidean algorithm and unique factorizations. The Fundamental Theorem of Algebra. Fields and field
extensions. |
| Spring 2019 |
MATH 128A: Numerical Analysis |
Prof. John Strain
|
4 |
- [Richard L. Burden, J. Douglas Faires] Numerical Analysis
|
MATLAB programming for numerical calculations, round-off error, approximation and interpolation,
numerical quadrature, and solution of ordinary differential equations. |
| Spring 2019 |
UGBA 103: Introduction to Corporate Finance |
Prof. Christine A. Parlour, Matteo Benetton
|
4 (A+) |
- [Jonathan B. Berk, Peter DeMarzo] Corporate Finance
|
Analysis and management of the flow of funds through an enterprise. Cash management, source and
application of funds, term loans, types and sources of long-term capital. Capital budgeting, cost of
capital, and financial structure. Introduction to capital markets. |
| Fall 2018 |
MATH 110: Linear Algebra |
Prof. Sug Woo Shin
|
4 |
- [Arnold J. Insel, et al.] Linear Algebra
|
Matrices, vector spaces, linear transformations, inner products, determinants. Eigenvectors. QR
factorization. Quadratic forms and Rayleigh's principle. Jordan canonical form, applications. Linear
functionals. |
| Fall 2018 |
History 124A: The Recent United States:
The United States from the Late 19th Century
to the Eve of World War II |
Prof. Brendan A. Shanahan
|
4 |
|
During the first half-century before World War II, the United States became an industrialized, urban society with national markets and communication media. This class will explore in depth some of the most important changes and how they were connected. We will also examine what did not change, and how state and local priorities persisted in many arenas. Among the topics addressed: population movements and efforts to control immigration; the growth of corporations and trade unions; the campaign for women's suffrage; Prohibition; an end to child labor; the institution of the Jim Crow system; and the reshaping of higher education.
|