SE402 Programming of CNC Machines
Syllabus | International University of Sarajevo - Last Update on Mar 03, 2026
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Software Engineering
Course Objectives
The aims of this course are to teach students the basics of CNC machines and fundamentals of CNC programming.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Edward Ford, Make: Getting Started with CNC; Peter Smid, CNC Programming Handbook, ISBN-13: 978-0831133474
Additional Literature
Teaching Methods
Class discussions with examples
Active laboratory sessions
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Blue print reading | |
| 2 | Fundamentals of G code | |
| 3 | Fundamentals of G code | |
| 4 | CNC milling machine basics (introduction to milling machine and its parts, different operations of milling machine) | |
| 5 | CNC milling machine basics (introduction to milling machine and its parts, different operations of milling machine). | |
| 6 | Overview of CAD/CAM programmes (AutoCAD, CATIA, APIRE, SolidWorks) Basics in the selected CAD/CAM programme: sketching points,lines, circles and arcs | |
| 7 | CAD/CAM: isometric views, splines and poly lines. | |
| 8 | MIDTERM preparation and MIDTERM | |
| 9 | CNC milling machine advanced. Practice CNC milling, excercises on machine by using different cycles | |
| 10 | Co2 laser advanced. Practice using Co2 lasers. Excercises using laser. | |
| 11 | Practice on CNC milling machine and Co2 lasers: excercises on machine and lasers. | |
| 12 | Practice on CNC milling machine and Co2 lasers: excercises on machine and lasers. | |
| 13 | Practice on CNC milling machine and Co2 lasers: excercises on machine and lasers. | |
| 14 | Project Presentations | |
| 15 | Review and final exam preparation |
Course Schedule (All Sections)
Office Hours & Room
Assessment Methods and Criteria
Assessment Components
Final Exam
AI: Not AllowedAlignment with Learning Outcomes :
Homework assignments
AI: Not AllowedAlignment with Learning Outcomes :
Project
AI: Not AllowedAlignment with Learning Outcomes :
In-term exam
AI: Not AllowedAlignment with Learning Outcomes :
IUS Grading System
| Grading Scale | IUS Grading System | IUS Coeff. | Letter (B&H) | Numerical (B&H) |
|---|---|---|---|---|
| 0 - 44 | F | 0 | F | 5 |
| 45 - 54 | E | 1 | ||
| 55 - 64 | C | 2 | E | 6 |
| 65 - 69 | C+ | 2.3 | D | 7 |
| 70 -74 | B- | 2.7 | ||
| 75 - 79 | B | 3 | C | 8 |
| 80 - 84 | B+ | 3.3 | ||
| 85 - 94 | A- | 3.7 | B | 9 |
| 95 - 100 | A | 4 | A | 10 |
Late Work Policy
Information about late submission policies will be shared during class and posted in this section. Please check back for official guidelines.
ECTS Credit Calculation
📚 Student Workload
This 6 ECTS credit course corresponds to 150 hours of total student workload, distributed as follows:
Lecture hours
42 hours ⏳ (14 week × 3 h)
In-term exam study
8 hours ⏳ (1 week × 8 h)
Active tutorials
28 hours ⏳ (14 week × 2 h)
Final exam study
10 hours ⏳ (1 week × 10 h)
Assignments
6 hours ⏳ (3 week × 2 h)
Term project/presentation
36 hours ⏳ (12 week × 3 h)
Home study
20 hours ⏳ (10 week × 2 h)
150 Total Workload Hours
6 ECTS Credits
Course Policies
Academic Integrity
All work submitted must be your own. Plagiarism, cheating, or any form of academic dishonesty will result in disciplinary action according to university policies. When in doubt about citation practices, consult the instructor.
Attendance Policy
Students are expected to adhere to the attendance requirements as outlined in the International University of Sarajevo Study Rules and Regulations. Excessive absences, whether excused or unexcused, may impact academic performance and eligibility for assessment. Mandatory sessions (e.g., labs, workshops) require attendance unless formally exempted. For detailed policies on absences, documentation, and penalties, please refer to the official university regulations.
Technology & AI Policy
Laptops/tablets may be used for note-taking only during lectures. Phones should be silenced and put away during all class sessions. Audio/video recording requires prior permission from the instructor.
Artificial Intelligence (AI) Usage: The use of AI tools (e.g., ChatGPT, Copilot, Gemini) varies by assessment component. Please refer to the AI usage indicator next to each assessment item in the Assessment Methods and Criteria section above. Submitting AI-generated content as your own work, where AI is not explicitly allowed, constitutes an academic integrity violation.
Communication Policy
All course-related communication should occur through official university channels (institutional email or SIS). Emails should include [SE402] in the subject line.
Academic Quality Assurance Policy
Course Academic Quality Assurance is achieved through Semester Student Survey. At the end of each academic year, the institution of higher education is obliged to evaluate work of the academic staff, or the success of realization of the curricula.
Learning Tips
Be prepared to contribute thoughtfully during class discussions, labs, or collaborative work. Active participation deepens understanding and encourages critical thinking.
Complete assigned readings or prep materials before class. Take notes, highlight key ideas, and jot down questions. Aim to grasp core concepts and their applications—not just facts.
Use course frameworks or methodologies to analyze problems, case studies, or projects. Begin early to allow time for reflection and refinement. Seek feedback to improve your work.
Don’t hesitate to reach out when something is unclear. Use office hours, discussion boards, or peer networks to clarify concepts and stay on track.
Syllabus Last Updated on Mar 03, 2026 | International University of Sarajevo
Print Syllabus
Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| SE402 | Programming of CNC Machines | 3 | 2 | 6 | ||||||
| Prerequisite | CS105 | It is a prerequisite to | - | |||||||
| Lecturer | Office Hours / Room / Phone | Currently not available |
||||||||
| Assistant | Assistant E-mail | |||||||||
| Course Objectives | The aims of this course are to teach students the basics of CNC machines and fundamentals of CNC programming. |
|||||||||
| Textbook | Edward Ford, Make: Getting Started with CNC; Peter Smid, CNC Programming Handbook, ISBN-13: 978-0831133474 | |||||||||
| Additional Literature | ||||||||||
| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | Class discussions with examples. Active laboratory sessions. | |||||||||
| Teaching Method Delivery | Teaching Method Delivery Notes | |||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Blue print reading | |||||||||
| Week 2 | Fundamentals of G code | |||||||||
| Week 3 | Fundamentals of G code | |||||||||
| Week 4 | CNC milling machine basics (introduction to milling machine and its parts, different operations of milling machine) | |||||||||
| Week 5 | CNC milling machine basics (introduction to milling machine and its parts, different operations of milling machine). | |||||||||
| Week 6 | Overview of CAD/CAM programmes (AutoCAD, CATIA, APIRE, SolidWorks) Basics in the selected CAD/CAM programme: sketching points,lines, circles and arcs | |||||||||
| Week 7 | CAD/CAM: isometric views, splines and poly lines. | |||||||||
| Week 8 | MIDTERM preparation and MIDTERM | |||||||||
| Week 9 | CNC milling machine advanced. Practice CNC milling, excercises on machine by using different cycles | |||||||||
| Week 10 | Co2 laser advanced. Practice using Co2 lasers. Excercises using laser. | |||||||||
| Week 11 | Practice on CNC milling machine and Co2 lasers: excercises on machine and lasers. | |||||||||
| Week 12 | Practice on CNC milling machine and Co2 lasers: excercises on machine and lasers. | |||||||||
| Week 13 | Practice on CNC milling machine and Co2 lasers: excercises on machine and lasers. | |||||||||
| Week 14 | Project Presentations | |||||||||
| Week 15 | Review and final exam preparation | |||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam | 1 | 30 | Not Allowed | ||
| Semester Evaluation Components | |||||
| Homework assignments | 2 | 10 | Not Allowed | ||
| Project | 1 | 40 | Not Allowed | ||
| In-term exam | 1 | 20 | Not Allowed | ||
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lecture hours | 3 | 14 | 42 | In-term exam study | 8 | 1 | 8 | |||
| Active tutorials | 2 | 14 | 28 | Final exam study | 10 | 1 | 10 | |||
| Assignments | 2 | 3 | 6 | Term project/presentation | 3 | 12 | 36 | |||
| Home study | 2 | 10 | 20 | 0 | ||||||
| Total Workload Hours = | 150 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 6 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 27/03/2026 | |||||||||