Spring 2024
Web Programming (웹프로그래밍)
Instructor: Dr. Muhammad Syafrudin
Course information
Do you want to learn how to develop a web application (WebApp) using several existing technologies? Do you want to learn how to implement a machine learning model in a WebApp? Or do you want to learn how to develop a WebApp using APIs? Then this course is for you! In this course, you will:
- Learn web programming technologies such as HTML, CSS, and both front-end (MDB) and back-end (Python, Flask, etc.) frameworks.
- Gain hands-on experience with a WebApp project.
- Have the opportunity to form a group project (with a maximum of three students per group) to propose an idea or case study and develop a WebApp to solve it.
Lecture
Tue, Thu at 10:30‐12:00 am KST at 센B202
Office hours
Appointment by email (Office at AI Center 502호)
Prerequisites
Having Python or any programming experience will be advantageous but not required.
Notes
Course material can be downloaded in ecampus and please be aware,
that we will not publicly release the homework assignments this year.
Please note that:
-All lectures are in English.
-Weekly lecture topics may be adjusted or changed without prior notice depending
on the understanding level during the class.
-All lectures will be conducted offline or online depending on the university regulations.
-We will notify you via ecampus/email if there is an update from the university regarding the class.
Please contact me or stop by my office if you have any issues with the course.
Schedule
| 주차(Week) | 강의내용(Class Topic & Contents) | 강의활동유형(Class Type) |
|---|---|---|
| 1 | Course overview and intro to web programming | 강의 (Lecture) |
| 2 | Introduction to HyperText Markup Language (HTML) | 강의+실습 (Lecture + Practice) |
| 3 | Introduction to Cascading Style Sheets (CSS) | 강의+실습 (Lecture + Practice) |
| 4 | Introduction to Material Design for Bootstrap (MDB), an open source front-end web user interface (UI) framework. | 강의+실습 (Lecture + Practice) |
| 5 | Introduction to Python | 강의+실습 (Lecture + Practice) |
| 6 | Introduction to Flask, an open-source backend framework based on the Python programming | 강의+실습 (Lecture + Practice) |
| 7 | Web programming with Flask I | 강의+실습 (Lecture + Practice) |
| 8 | Mid exam | 시험 (Exam) |
| 9 | Integration with Database (MongoDB) | 강의+실습 (Lecture + Practice) |
| 10 | Web programming with Flask II | 강의+실습 (Lecture + Practice) |
| 11 | Web programming with Flask III | 강의+실습 (Lecture + Practice) |
| 12 | Project example I (WebApp for prediction or classification) | 강의+실습 (Lecture + Practice) |
| 13 | Project example II (WebApp using Application Programming Interface (API)) | 강의+실습 (Lecture + Practice) |
| 14 | Group project discussion and development | 강의+실습 (Lecture + Practice) |
| 15 | Group project discussion and development | 강의+실습 (Lecture + Practice) |
| 16 | Final group project presentation (ppt, codes, and project report final submission) | Evaluation |
Grading
The final grade will be calculated using the following weights:
| # | Final Grade Weight |
|---|---|
| Attendance | 10% |
| Assignment(quiz/homework/weekly assignment) | 20% |
| Mid exam | 30% |
| Final group project | 40% |
| Total | 100% |
Assignment
There might be 3-5 assignments, which will be released at the end of each lecture.
Submitting an assignment
Instructions for turning in assignments will be posted when the semester starts (in ecampus).
Getting help
For questions about homework, course content, installation, and after you have tried to troubleshoot yourselves, the process to get help is: Post the question in ecampus/group chat and hopefully your peers will answer. Note that in ecampus questions are visible to everyone. For private matters send an email to helpline: udin [at] sju [dot] ac [dot] kr.
Course Policies
Collaboration policy
We encourage you to talk and discuss the assignments with your fellow students (and on ecampus), but you are not allowed to look at any other students assignment or code outside of your pair. Discussion is encouraged, copying is not allowed.
Late day policy
Homework is due before each class. Late submission are not allowed.
Communication to students
Class announcements will be through ecampus. All homework and quizzes will be posted in ecampus. Also all feedback forms. Important note: make sure you have your settings set so you can receive emails from ecampus.
Academic honesty
We give a strong emphasis to Academic Honesty. As a student your best guidelines are to be reasonable and fair. We encourage teamwork for problem sets, but you should not split the homework and you should work on all the problems together.