宾夕法尼亚大学 UPenn数据科学硕士+ 查看更多
宾夕法尼亚大学 UPenn
数据科学硕士
+ 查看更多
- Penn 的数据科学工程理学硕士 (MSE) 为学生准备了广泛的以数据为中心的职业课程,这些课程将广泛应用在技术和工程、咨询、科学、政策制定,以及文学、艺术或通信领域
- 该计划通常可以在一年半到两年内完成。它融合了 机器学习、大数据分析和统计学等领域的前沿课程,与此同时学校开设各种选修课,并有机会将这些技术应用于所选的专业领域
- 该校的数据科学以其强大的跨学科授课传统为数据科学爱好者提供了完美的学习环境。学校与其他专业联合为学生提供了广泛的选修课,如:生物医学信息学、通信和公共政策、机器人技术、机器学习和人工智能以及数据隐私等
项目时长:1到1.5年全日制
项目授课地点:美国 宾夕法尼亚州 费城
申请要求
申请流程
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- 基础课程:
Programming Languages & Techniques (PL): Programming Languages & Techniques or Introduction to Software Development
Linear Algebra OR Computational Linear Algebra
If students have taken these courses as part of another program, the requirement may be waived.
For Accelerated Masters, the programming requirement can be waived with successful completion of a B+ or higher in CIS 1200. The linear algebra requirement can be waived with a B+ or higher in Math 3120. The Stats requirement can be waived with a B+ or higher in Stat 4310. A student may also waive Foundation requirements with any other relevant course after getting department approval.
- 核心课程
Statistics for Data Science
Big Data Analytics: Big Data Analytics
Mining and Learning: Intro to Machine Learning or Machine Learning or Modern Data Mining or Data-driven Modeling and Probabilistic Scientific Computingor Data Mining: Learning from Massive Datasets
- 技术和深度领域选修课(学生必须从下面列出的至少 3 个类别中选择课程 )
· TitleThesis/Practicum(二选一)
· Biomedicine
Brain-Computer Interfaces
Network Neuroscience
AI II: Introduction to Machine Learning and Health Language Processing
AI III: Advanced Methods and Health Applications in Machine Learning
Introduction to Computational Biology and Biological Modeling
Biomedical Image Analysis
Theoretical and Computational Neuroscience
· Social/Network Science
Ethical Algorithm Design
Econometrics I- Fundamentals
Econometrics III: Advanced Techniques of Cross-Section Econometrics
Econometrics IV: Advanced Techniques of Time-Series Econometrics
Applied Probability Models in Marketing
· Biomedicine
Brain-Computer Interfaces
Network Neuroscience
AI II: Introduction to Machine Learning and Health Language Processing
AI III: Advanced Methods and Health Applications in Machine Learning
Introduction to Computational Biology and Biological Modeling
Biomedical Image Analysis
Theoretical and Computational Neuroscience
· Social/Network Science
Ethical Algorithm Design
Econometrics I- Fundamentals
Econometrics III: Advanced Techniques of Cross-Section Econometrics
Econometrics IV: Advanced Techniques of Time-Series Econometrics
Applied Probability Models in Marketing
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