3. 강의목표
Continuous computations, which involve continuous data and operations, are fundamental to diverse areas of computer science, including machine learning and scientific computing. Examples include evaluating continuous functions (e.g., numpy.exp(x)) and computing derivatives (e.g., jax.grad(f)). This course introduces the foundations and principles of continuous computations. In essence, this course serves as a *computational* counterpart to a traditional calculus course, and a *continuous* counterpart to traditional CS courses on discrete computations. Lectures will start from first principles, and emphasize both mathematical theory and relevant computational methods.
4. 강의선수/수강필수사항
Students should have a basic knowledge of calculus, probability, and algorithms. As this course is math-intensive, students should be comfortable with understanding and doing rigorous mathematical proofs. The following courses are relevant but not required: Automata & Formal Languages (CSED341), Programming Languages (CSED321), and Analysis I (MATH311). Students are welcome to audit this course, subject to seat availability.
5. 성적평가
https://tinyurl.com/contcomp25
7. 참고문헌 및 자료
https://tinyurl.com/contcomp25
8. 강의진도계획
https://tinyurl.com/contcomp25
11. 장애학생에 대한 학습지원 사항
- 수강 관련: 문자 통역(청각), 교과목 보조(발달), 노트필기(전 유형) 등
- 시험 관련: 시험시간 연장(필요시 전 유형), 시험지 확대 복사(시각) 등
- 기타 추가 요청사항 발생 시 장애학생지원센터(279-2434)로 요청