EE · Spring 2026 · Undergraduate
Computer Science and Coding
An introduction to computational thinking and practical programming through Python.
Course Overview
This course introduces computer programming as a way to formulate and solve problems. Students build programs in Python while learning core data types, control flow, functions, data structures, modules, file processing, exception handling, and object-oriented programming. Lectures are paired with guided practice so that each concept is applied in code.
- Instructor
- Prof. Nuri Kim
- Term
- Spring 2026
- Meetings
- Mon 11:00–12:30
Wed 11:00–11:50 - Classroom
- Engineering Building 1
Room 161
Logistics
Learning goals
- Translate a problem into a clear sequence of computational steps.
- Write, run, test, and debug Python programs.
- Select appropriate control structures and built-in data structures.
- Organize programs with functions, modules, files, and classes.
Course information
- Credits: 3.
- Format: Monday lecture and guided practice; Wednesday lab.
- Office hours: Monday, 13:00–14:00, Engineering Building No. 7, Room 326.
- Programming environment: Python 3 with IDLE, Visual Studio Code, or Jupyter Notebook.
Course communication: administrative questions may be sent by email. Questions about lectures, assignments, and course operation should be posted through the JBNU LMS.
Schedule
Programming Foundations
Data Structures & Review
Programs & Objects
This schedule records the Spring 2026 offering. Lecture materials, assignment files, and announcements remain available to enrolled students through the JBNU LMS.
Coursework & Assessment
Homework 1–3
Core Python
Practice conditionals, loops, functions, numeric problems, and structured input and output.
Homework 4–5
Data Structures
Work with lists, dictionaries, tuples, and sets to organize and process collections of data.
Homework 6–7
Modules & Files
Create reusable modules and build robust programs with exceptions and file input and output.
Homework 8–9
Object-Oriented Programming
Design classes and apply inheritance and class-based problem solving.
- Midterm Exam
- 30%
- Final Exam
- 40%
- Homework
- 10%
- Quizzes
- 10%
- Attendance
- 10%
Submission policy: homework is normally posted on Wednesday and due by Sunday at midnight. Late submissions are not accepted. Unauthorized generative AI use, plagiarism, or submitting techniques outside the permitted course scope receives no credit.
Resources
- Course platformJBNU LMS
- Programming languagePython 3
- Development toolsPython IDLE · Visual Studio Code · Jupyter Notebook
- InstructorProf. Nuri Kim
- Contactnuri.kim@jbnu.ac.kr