计算机科学先修课要求

由于计算机科学的热度居高不下，很多专业的申请者会考虑转专业申请。尽管计算机科学项目欢迎工科等不同背景的申请者，建议申请者尽可能多修相关课程，以提高自己的竞争优势。

结合以下院校对先修课的要求，计算机科学的先修课可以概括为以下几类：

数学

Linear Algebra

Calculus I, II

Probability and Statistics

Linear Differential Equations

Numerical Analysis

Fourier Analysis

Discrete Mathematics

计算机

Introduction to Programming

Problem Solving & Programming

Computer Architecture

Data Structures (Arrays, Lists, Pointers)

Principles of Computer Systems或者Operating Systems

Algorithms

Introduction to Discrete Structures

Machine Structures

Programming Language: JAVA, Matlab, Python, C/C++Introduction to Computation

Software

Windows, MacOS, Linux

具体院校选修课要求——卡耐基梅隆大学

Master of Science in Computer Vision

Mathematics

Linear Algebra (Inversion, Eigen Decomposition, Null Space)

Linear Differential Equations (Matrix Algebra, Matrix manipulation)

Calculus (Derivatives, Gradients, Chain Rule)

Probability and Statistics

Numerical Integration

Fourier Analysis

Optimization (convex optimization, Levenberg-Marquardt, sparse optimization)

Programming knowledge

Data structures

C/C++, JAVA, Matlab, Python

OpenCV, VLfeat, Matlab Image processing toolbox

GPU (CUDA, OpenCL)

Software

Productivity software (MS office, iWork, OpenOffice)

Windows, MacOS, Linux

LaTeX

Photoshop (or equivalent)

Master of Science in Robotics

Prerequisites

It is each student’s personal responsibility to arrive with, or to acquire rapidly thereafter, basic understanding (at the level of an introductory undergraduate course) in the following areas:

·Mathematics: calculus, linear algebra, numerical analysis, probability and statistics

·Computer Science: programming, data structures, algorithms

·Physics and Engineering: mechanics, dynamics, electricity and magnetism, optics

Master of Science in Machine Learning

Incoming students must have a strong background in computer science, including a solid understanding of complexity theory and good programming skills, as well as a good background in mathematics. Specifically, the first-year courses assume at least one year of college-level probability and statistics, as well as matrix algebra and multivariate calculus.

For our introductory ML course, there's a self-assessment test [PDF]http://liuxue.xdf.cn/which will give you some idea about the background we expect students to have (for the MS you're looking at the "modest requirements"). Generally, you need to have some reasonable programming skills, with experience inMatlab/R/scipy-numpyespecially helpful, andJavaandPythonbeing more useful than C, and a solid math background, especially inprobability/statistics, linear algebra, and matrix and tensor calculus.

Master of Science in Computer Science

We cater to students withbasic analytic skillsanda strong aptitude for mathematics, programming, and logical reasoning.  You don’t need a bachelor’s degree in computer science specifically for the program, but a technical undergraduate background will set you up for success.

Master of Science in Robotic Systems Development

Recommended Skills for MRSD

PROGRAMMING

Matlab

Familiarity with command-line and external functions using MATLAB library; Import/export of data; graphing/plotting functions & data; rudimentary animation

Python

And / or C / C++ familiarity

ROS

Robot Operating System (ROS) - Optional (Good to know)

Program Constructs

Sequencing, Selection, Iteration & Recursion

Data Organization

Arrays, Lists, Pointers

COMPUTERS

Tools

Productivity SW (MS Office - Excel / Word / PowerPoint / Project)

Operating Systems

Windows or Apple-OS - use of personal laptop computer Linux or Ubuntu

MATHEMATICS

Linear Algebra

Inversion, Eigenvalues, Null-Space

Linear Differential Eq.

Matrix-Algebra & -Manipulation

Basic Calculus

Derivatives, Gradients, Chain Rule

Numerical Integration

Basic Computational Implementation, e.g. Runge-Kutta 4

Fourier Analysis

NOT how to calculate the coefficients, but the notion that any complicated fct. can be represented as a composite of simpler ones

CMU Math Fundamentals Course

16-811: Math Fundamentals for Robotics

PHYSICS

Newtonian Physics

Newton-Euler Mechanics (Forces, torques, mass / inertia, Equations of motion)

System State

Degrees of Freedom & Constraints to fully describe a system’s behavior mathematically

CONTROLS

Control Systems

Controls Fundamentals (transfer functions; bode plots; stability-margin; time-response of LTI systems; PID compensators)

OTHER

Electronics

Basic experience with practical circuits (elements, interactions, PCBs)

Mechanisms

Some design and fabrication experience (Concept -> CAD -> Fabrication)

Documentation

Basic skills in document structuring and technical writing

REFERENCES

Courses - College-Level

CMU: CS Courses 15-110 and / or 15-112 OR equivalentHIGHLY recommend being comfortable with material in 16-811

Courses - Online

Stanford - CS-101MIT - Code AcademyCourseraUdacity - . . . choose cs101 or cs373

Books

Linear Algebra: A Modern Introduction - David PoolePhysics - Jay OrearControl Systems Engineering - Norman NiseThe C Programming Language - Kernighan & RitchieThe C Programmers Handbook - Thom HoganProgramming in C - S. Kochan

Online Tutorials and Learning Resources

MATLABPythonLynda - assorted trainings - available with CMU ID