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- First-Year Courses
- School of Science
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School of Environment and Society
- Department of Architecture and Building Engineering
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- Graduate major in Technology and Innovation Management
- Common courses
- Liberal arts and basic science courses
- Academic unit or major
- Undergraduate major in Mathematical and Computing Science
- Instructor(s)
- Cong Youyou Kashima Ryo
- Class Format
- Lecture / Exercise (Face-to-face)
- Media-enhanced courses
- Day/Period(Room No.)
- Mon7-8(W8E-307(W833)) Thr5-8(W8E-307(W833))
- Group
- -
- Course number
- MCS.T204
- Credits
- 3
- Academic year
- 2024
- Offered quarter
- 1Q
- Syllabus updated
- 2024/3/14
- Lecture notes updated
- -
- Language used
- Japanese
- Access Index
-
Course description and aims
This course consists of computer science lectures, programming lectures, and programming exercises. The computer science lectures cover topics related to computers and the theory of computation. The programming lectures and exercises introduce recipes for solving problems through programming in the Scala language. The last lecture discusses ethical issues in science. This course is the starting point of all studies in the Department of Mathematical and Computing Science.
Student learning outcomes
Students will acquire basic knowledge and skills in computer science and programming.
Keywords
computer science, programming, scientific ethics
Competencies that will be developed
| ✔ Specialist skills | Intercultural skills | Communication skills | Critical thinking skills | ✔ Practical and/or problem-solving skills |
Class flow
The course consists of lectures and programming exercises.
Course schedule/Required learning
| Course schedule | Required learning | |
|---|---|---|
| Class 1 | (Computer Science Lecture 1) History of computers & representation of data | Instructed in the class. |
| Class 2 | (Programming Lecture 1) Function definition | Instructed in the class. |
| Class 3 | (Programming Exercise 1) Function definition | Instructed in the class. |
| Class 4 | (Computer Science Lecture 2) Boolean algebra and logic circuits | Instructed in the class. |
| Class 5 | (Programming Lecture 2) Booleans and algebraic data types | Instructed in the class. |
| Class 6 | (Programming Exercise 2) Booleans and algebraic data types | Instructed in the class. |
| Class 7 | (Computer Science Lecture 3) Computability & computational complexity | Instructed in the class. |
| Class 8 | (Computer Science Lecture 4) How programs are executed | Instructed in the class. |
| Class 9 | (Programming Lecture 3) Complex data types | Instructed in the class. |
| Class 10 | (Programming Exercise 3) Complex data types | Instructed in the class. |
| Class 11 | (Computer Science Lecture 5) Lambda calculus | Instructed in the class. |
| Class 12 | (Programming Lecture 4) Lists, recursion, and higher-order functions | Instructed in the class. |
| Class 13 | (Programming Exercise 4) Lists, recursion, and higher-order functions | Instructed in the class. |
| Class 14 | (Computer Science Lecture 6) Logic and programming | Instructed in the class. |
| Class 15 | (Programming Lecture 5) Various recursive data types | Instructed in the class. |
| Class 16 | (Programming Exercise 5) Various recursive data types | Instructed in the class. |
| Class 17 | (Computer Science Lecture 7) Ethics of science | Instructed in the class. |
| Class 18 | (Programming Lecture 6) Advanced forms of recursion | Instructed in the class. |
| Class 19 | (Programming Exercise 6) Advanced forms of recursion | Instructed in the class. |
| Class 20 | (Programming Lecture 7) Wrap-up | Instructed in the class. |
| Class 21 | (Programming Exercise 7) Wrap-up | Instructed in the class. |
Out-of-Class Study Time (Preparation and Review)
To enhance effective learning, students are encouraged to spend approximately 100 minutes preparing for class and another 100 minutes reviewing class content afterwards (including assignments) for each class.
They should do so by referring to textbooks and other course material.
Textbook(s)
N/A
Reference books, course materials, etc.
M. Felleisen, R. Findler, M. Flatt, and S. Krishnamurthi. How to Design Programs, Second Edition. (https://htdp.org/)
Assessment criteria and methods
Evaluation is done based on the performance in paper-based quizzes (30%) and programming exercises (70%).
Note that earning credits requires gaining 60 points or more in both quizzes and exercises.
Related courses
- LAS.I111 ： Information Literacy I
- LAS.I112 ： Information Literacy II
- LAS.I121 ： Computer Science I
- LAS.I122 ： Computer Science II
Prerequisites (i.e., required knowledge, skills, courses, etc.)
Only students in Department of Mathematical and Computing Science may take this course.
Students must have successfully completed Information Literacy I and II (LAS.I111, LAS.I112) or have equivalent knowledge.
