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Discipline ID
bf91b86a-62db-4996-b583-29c1ffe6e71e

COURSE DETAIL

PRINCIPLES AND PRACTICES OF SOFTWARE DEVELOPMENT
Country
Korea, South
Host Institution
Seoul National University
Program(s)
Seoul National University
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Computer Science
UCEAP Course Number
123
UCEAP Course Suffix
UCEAP Official Title
PRINCIPLES AND PRACTICES OF SOFTWARE DEVELOPMENT
UCEAP Transcript Title
SOFTWARE DEVELOPMNT
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description

This course teaches the principles of software development for medium to large software design and implementation. Students apply these principles to software systems in practice by working on group projects. Through this experience, students learn how to build correct and high-performance software.

Language(s) of Instruction
English
Host Institution Course Number
M1522.002400
Host Institution Course Title
PRINCIPLES AND PRACTICES OF SOFTWARE DEVELOPMENT
Host Institution Course Details
Host Institution Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
Computer Science and Engineering
Course Last Reviewed
2021-2022

COURSE DETAIL

INTRODUCTION TO ARTIFICIAL INTELLIGENCE
Country
Korea, South
Host Institution
Yonsei University
Program(s)
Yonsei University
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Computer Science
UCEAP Course Number
121
UCEAP Course Suffix
UCEAP Official Title
INTRODUCTION TO ARTIFICIAL INTELLIGENCE
UCEAP Transcript Title
ARTIFICIAL INTEL
UCEAP Quarter Units
4.50
UCEAP Semester Units
3.00
Course Description
Computational (data-driven) AI is one of the fastest-growing and most exciting fields lately, and machine learning represents its genuine bleeding edge. In this course, you'll develop a clear understanding of the motivation for machine learning, and design intelligent systems that learn from data. Emphasis is placed on the analysis of these models, on methods of training them and on their application to engineering problems in prediction, regression, and classification. Prerequisites: Calculus, Linear Algebra, Probability Theory and Random Variables, Matlab/Python/C/C++ (either one) Programming skill.
Language(s) of Instruction
English
Host Institution Course Number
EEE3314
Host Institution Course Title
INTRODUCTION ARTIFICIAL INTELLIGENCE
Host Institution Course Details
Host Institution Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
Electrical and Electronics Engineering
Course Last Reviewed

COURSE DETAIL

DEEP NEURAL NETWORKS
Country
Germany
Host Institution
Technical University Berlin
Program(s)
Technical University Berlin
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Computer Science
UCEAP Course Number
125
UCEAP Course Suffix
UCEAP Official Title
DEEP NEURAL NETWORKS
UCEAP Transcript Title
DEEP NEURAL NETWORK
UCEAP Quarter Units
3.00
UCEAP Semester Units
2.00
Course Description
This course examines deep neural networks (DNN) and covers the following topics: DNN basics, model complexity and model selection, optimization of DNNs, DNNs for images, DNNs for time series, explaining DNN decisions, DNNs beyond classification.
Language(s) of Instruction
English
Host Institution Course Number
Host Institution Course Title
DEEP NEURAL NETWORKS
Host Institution Course Details
Host Institution Campus
FAKULTÄT IV ELEKTROTECHNIK UND INFORMATIK
Host Institution Faculty
Host Institution Degree
Host Institution Department
Informatik
Course Last Reviewed

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HEALTH DATA SCIENCE AND DATA ANALYTICS IN HEALTHCARE (LEVEL 2)
Country
United Kingdom - England
Host Institution
University College London
Program(s)
Summer at University College London
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Health Sciences Computer Science
UCEAP Course Number
114
UCEAP Course Suffix
S
UCEAP Official Title
HEALTH DATA SCIENCE AND DATA ANALYTICS IN HEALTHCARE (LEVEL 2)
UCEAP Transcript Title
HEALTH DATA SCIENCE
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description

Health Data Science is an area that combines scientific inquiry, statistical knowledge, substantive expertise, and computer programming in the area of healthcare and biomedicine. Students are introduced to fundamental data analytic tools and techniques, and learn how to use specialized software to analyze real-world health data.

Language(s) of Instruction
English
Host Institution Course Number
ISSU0091
Host Institution Course Title
HEALTH DATA SCIENCE AND DATA ANALYTICS IN HEALTHCARE (LEVEL 2)
Host Institution Campus
Bloomsbury
Host Institution Faculty
Host Institution Degree
Bachelors
Host Institution Department
Institute of Health Informatic
Course Last Reviewed
2022-2023

COURSE DETAIL

ADVANCED TOPICS IN ARTIFICIAL INTELLIGENCE
Country
Singapore
Host Institution
National University of Singapore
Program(s)
National University of Singapore
UCEAP Course Level
Graduate
UCEAP Subject Area(s)
Computer Science
UCEAP Course Number
208
UCEAP Course Suffix
UCEAP Official Title
ADVANCED TOPICS IN ARTIFICIAL INTELLIGENCE
UCEAP Transcript Title
ADV TOPICS IN AI
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This course covers advanced topics in artificial intelligence that are of current research or application interests. A wide range of topics may be covered including soft computing (fuzzy logic, genetic algorithms, etc.), data mining, machine learning, image and video processing, artificial life, robotics, etc. The exact topics to be taught will depend on the lecturers teaching the module. Graduate Research Module, this semester with a focus on "Computer Vision for Self-Driving Cars". Paper presentations throughout the semester and a final capstone research project.
Language(s) of Instruction
English
Host Institution Course Number
CS6208
Host Institution Course Title
ADVANCED TOPICS IN AI
Host Institution Course Details
Host Institution Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
Computer Science
Course Last Reviewed

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BIG DATA AND ARTIFICIAL INTELLIGENCE
Country
Spain
Host Institution
Pompeu Fabra University
Program(s)
21st Century Barcelona
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Computer Science
UCEAP Course Number
119
UCEAP Course Suffix
UCEAP Official Title
BIG DATA AND ARTIFICIAL INTELLIGENCE
UCEAP Transcript Title
BIG DATA & AI
UCEAP Quarter Units
1.50
UCEAP Semester Units
1.00
Course Description
This course offers an introduction to the concept of Big Data and how to manage large volumes of data using machine learning. It applies Big Data to various areas including education, health, finance, and social media. This course also discusses the challenges of Big Data including data bias, transparency and accountability of the algorithms, the loss of privacy and the new ethical dilemmas these algorithms generate.
Language(s) of Instruction
English
Host Institution Course Number
59029
Host Institution Course Title
BIG DATA AND ARTIFICIAL INTELLIGENCE
Host Institution Course Details
Host Institution Campus
Ciutadella Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
UPF Education Abroad Program
Course Last Reviewed

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ARTIFICIAL INTELLIGENCE FOR GAME PROGRAMMING 2
Country
Sweden
Host Institution
Uppsala University
Program(s)
Uppsala University
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Computer Science
UCEAP Course Number
118
UCEAP Course Suffix
UCEAP Official Title
ARTIFICIAL INTELLIGENCE FOR GAME PROGRAMMING 2
UCEAP Transcript Title
AI/GAME PROGRAMMG 2
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description

This course focuses on the development of software for Artificial Intelligence (AI) for computer games, primarily regarding strategic games. The course covers the development of AI for games with perfect information (e.g., chess, Othello, and AlphaGo), and games without perfect information (e.g. card and dice games), including simultaneous games and classical concepts within game theory, such as the Nash equilibrium. The programming language used is C++. 

Language(s) of Instruction
English
Host Institution Course Number
5SD810
Host Institution Course Title
ARTIFICIAL INTELLIGENCE FOR GAME PROGRAMMING 2
Host Institution Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
Computer Science
Course Last Reviewed
2021-2022

COURSE DETAIL

Digital Image Processing
Country
Germany
Host Institution
Technical University Berlin
Program(s)
Technical University Berlin
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Computer Science
UCEAP Course Number
108
UCEAP Course Suffix
UCEAP Official Title
Digital Image Processing
UCEAP Transcript Title
DIG IMAGE PROCESSNG
UCEAP Quarter Units
5.50
UCEAP Semester Units
3.70
Course Description

This course covers image representation in frequency domain, Fourier transform, sampling theorem, Filtering, Wiener Filter, image enhancement, edge detection, Hough transform, segmentation, interest operators, mathematical morphology, vectorization, texture, sceletonization, medical axis and distance transform, contour/line tracing and -smoothing, Gestalt psychology, and grouping.

Language(s) of Instruction
English
Host Institution Course Number
0433 L110
Host Institution Course Title
Digital Image Processing
Host Institution Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
Institut für Technische Informatik und Mikroelektronik
Course Last Reviewed
2021-2022

COURSE DETAIL

FUNCTIONAL PROGRAMMING
Country
United Kingdom - England
Host Institution
University College London
Program(s)
University College London
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Computer Science
UCEAP Course Number
118
UCEAP Course Suffix
UCEAP Official Title
FUNCTIONAL PROGRAMMING
UCEAP Transcript Title
FUNCTNL PROGRAMMING
UCEAP Quarter Units
6.00
UCEAP Semester Units
4.00
Course Description
This course provides an overview of functional programming, including both the functional programming language Miranda and functional language implementation techniques such as graph reduction and garbage collection. The course is suitable for advanced undergraduates and conversion MSc students; no prior experience of functional programming is assumed, but students must have prior programming experience in a general purpose programming language.
Language(s) of Instruction
English
Host Institution Course Number
COMP0020
Host Institution Course Title
FUNCTIONAL PROGRAMMING
Host Institution Campus
University College London
Host Institution Faculty
Host Institution Degree
Host Institution Department
Computer Science
Course Last Reviewed
2019-2020

COURSE DETAIL

COMPUTER PROGRAMMING IN PYTHON
Country
Taiwan
Host Institution
National Taiwan University
Program(s)
National Taiwan University
UCEAP Course Level
Upper Division
UCEAP Subject Area(s)
Computer Science
UCEAP Course Number
107
UCEAP Course Suffix
UCEAP Official Title
COMPUTER PROGRAMMING IN PYTHON
UCEAP Transcript Title
PYTHON PROGRAM
UCEAP Quarter Units
4.50
UCEAP Semester Units
3.00
Course Description

The course begins by writing a Python environment build while teaching the structure and use of various syntaxes. The course introduces various basic knowledge in Python one by one, arranging exercises in various situations at the same time so that students can accumulate the syntax and skills of writing Python programs while solving imaginary problems. The course content is introduced in the following order: 1. Python and authoring tools/platforms; 2. Python basic variable types, grammatical structure and package usage, and 3. Some of the most popular packages in Python. At the end of the course, students will choose a topic for a final project report (individual or group); students will be expected to introduce the problems they encountered and want to solve; how to solve these problems through Python, and present the results in visual ways.

Language(s) of Instruction
Chinese
Host Institution Course Number
Data5006
Host Institution Course Title
COMPUTER PROGRAMMING IN PYTHON
Host Institution Campus
Host Institution Faculty
Host Institution Degree
Host Institution Department
Course Last Reviewed
2022-2023
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