加州大学伯克利分校计算机科学硕士+ 查看更多
加州大学伯克利分校
计算机科学硕士
+ 查看更多
- 该课程是是一个职业学位课程,学校聘请了推动计算机科学发展的教授,涵盖了目前最前沿的计算机科学技术,通过向这样的老师学习,可以加速学生的职业发展
- 该项目需要完成32个小时的研究生课程,全部授课制,不带研究论文
项目时长:1年全日制项目
项目授课地点:美国 加州 旧金山
申请要求
学术 | 学术背景:
有足够的本科培训,以便在所选领域从事研究生工作 要求最低平均成绩(GPA)为3.0
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TOEFL | 总分:90 |
GRE | 选择性递交 |
IELTS | 总分:7.0+ |
其他要求 |
申请流程
第1步:准备好申请文件 |
·推荐信 三封推荐信,尽可能递交学术推荐信。推荐信内容包括有关申请人的学习目标、研究成就、技术和领导能力、学术工作等的详细信息。 ·SOP Why are you applying for this program? What are your research goals and interests? What do you hope to accomplish in this degree program? What do you want to do after and how will this help you? ·Personal History Statement What from your past made you decide to go into this field? And how will your personal history help you succeed in this program and your future goals? ·CV List any education, work, research, volunteer experience, awards, or future coursework |
第2步:需要的其他文件 |
|
第3步:在线填表申请 |
第4步:递交申请费 |
Foundations of Data Science
The Beauty and Joy of Computing
Designing Information Devices and Systems
The Coevolution of Humans and Machines
The Structure and Interpretation of Computer Programs
Data Structures
Machine Structures
Discrete Mathematics and Probability Theory
Computational Structures in Data Science
Principles & Techniques of Data Science
Introduction to Robotics
Probability and Random Processes
Optimization Models in Engineering
Introduction to Embedded Systems
Introduction to Digital Design and Integrated Circuits
Introduction to Digital Design and Integrated Circuits Lab
Operating Systems and System Programming
Programming Languages and Compilers
Introduction to the Internet: Architecture and Protocols
Introduction to Software Engineering
Efficient Algorithms and Intractable Problems
Computability and Complexity
Algorithms for Computational Biology
Designing, Visualizing and Understanding Deep Neural Networks
Introduction to Database Systems
Introduction to Artificial Intelligence
Introduction to Machine Learning
Intro to Computer Vision and Computational Photography
Special Topics on Decentralized Finance
Entrepreneurship in Web3
Social Implications of Computer Technology
Introduction to Robotics
Digital Image Processing
Optimization Models in Engineering
Introduction to Embedded Systems
Introduction to Digital Design and Integrated Circuits
Introduction to Digital Design and Integrated Circuits Lab
Advanced Topics in Computer SystemsJohn Kubiatowicz
Randomness and Computation
Designing, Visualizing and Understanding Deep Neural Networks
Deep Reinforcement Learning, Decision Making, and Control
Introduction to Machine Learning
Intro to Computer Vision and Computational Photography
Experimental Design for Machine Learning on Multimedia Data
Immersive Computing and Virtual Reality
Building Systems with Decentralized Trust
Special Topics on Decentralized Finance
Efficient Algorithms and Computational Intractability in Statistics
Entrepreneurship in Web3
Advances in Error-Correcting Codes
Quantum Complexity Theory
Polarization and Social Media
Recent Topics on Program Synthesis, Compilation, and Debugging
Field Studies in Computer Science
Group Studies Seminars, or Group Research
Individual ResearchMichael Mahoney
Adaptive Instruction Methods in Computer Science
Teaching Techniques for Computer Science
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