ENS101 Introduction to Engineering
Syllabus | International University of Sarajevo - Last Update on Sep 09, 2025
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Electrical and Electronics Engineering
Tarik Namas
Course Lecturer
Course Objectives
The aims of this course are: - to introduce engineering students to methods of problem-solving. - to introduce engineering students to various skills related to communication and team work - to introduce general engineering computation software (SciLab, MATLAB, Excell) - to introduce engineering students to the importance of modeling and simulation in engineering work, and the tools to achieve that.
Learning Outcomes
After successful completion of the course, the student will be able to:
Course Materials
Required Textbook
Stephan, Park, Sill, Bowman & Ohland, “Thinking Like an Engineer”, 3rd edition, Pearson, 2015. Landis, R.B.,
Additional Literature
Studying Engineering: A Road Map to a Rewarding Career, 4th ed., ISBN-10: 0979348749 Moaveni, S. Engineering Fundamentals: An Introduction to Engineering, 5th ed. Cengage Learning, 2014 Palm, W. J. Introduction to MATLAB 7 for Engineers, 3rd ed. Mc-Graw Hill, 2011 Other notes and links, will be provided on MS teams. Foundations of Engineering, Mark Holtzapple and W. Reece, 3rd Edition, McGraw HillTeaching Methods
Student-engaged class discussions
Student presentations
Regular lab-book keeping
Teamwork
Continuous evaluation and feedback on progress
Weekly Topics
| Week | Topic | Readings / References |
|---|---|---|
| 1 | Introduction and course mechanics, Every day engineering | Ch01 |
| 2 | Ethics/ Introduction to Octave | Ch02/ Ch015 |
| 3 | Design, team work, project management / Algorithms, functions | Ch03/ Ch16 |
| 4 | Engineering communications/ Algorithms, functions | Ch04/ Ch16 |
| 5 | Estimation / Inputs-Outputs | Ch05/ Ch17 |
| 6 | Solving problems / Logic and Conditions | Ch06/ Ch18 |
| 7 | Abstractions and thinking in abstract way / Looping | class notes/ Ch19 |
| 8 | Midterm exam | class notes |
| 9 | Graphs / More on plotting and data visualization | Ch11 / class notes |
| 10 | Models and systems / Problems to be solved using Octave | Ch12 / class notes |
| 11 | Mathematical Models / Word processing, Latex | Ch13 / class notes |
| 12 | Statistics / Word processing, Latex / Project - poster presentation groups | Ch14 / class notes |
| 13 | Work on project and follow up | class notes |
| 14 | Work on project and follow up | class notes |
| 15 | Work on project and follow up - Presentation | class notes |
Course Schedule (All Sections)
| Section | Type | Day 1 | Venue 1 | Day 2 | Venue 2 |
|---|---|---|---|---|---|
| ENS101.1 | Course | Tuesday 15:00 - 16:50 | B F2.15 - Amphitheater II | - | - |
| ENS101.2 | Course | Monday 16:00 - 17:50 | B F2.15 - Amphitheater II | - | - |
| ENS101.4 | Tutorial | Wednesday 15:00 - 18:50 | B F2.17 | - | - |
| ENS101.2 | Tutorial | Tuesday 17:00 - 17:50 | B F2.15 - Amphitheater II | - | - |
| ENS101.3 | Tutorial | Thursday 17:00 - 18:50 | A F1.24 - Amphitheater I | - | - |
| ENS101.1 | Tutorial | Tuesday 14:00 - 14:50 | B F1.16 | Tuesday 15:00 - 15:50 | A F1.23 |
Office Hours & Room
| Day | Time | Office | Notes |
|---|---|---|---|
| Tuesday | 14:00 - 16:00 | B F3.15 | |
| Wednesday | 14:00 - 16:00 | B F3.15 | |
| Thursday | 15:00 - 16:00 | B F3.15 |
Assessment Methods and Criteria
Assessment Components
Final Exam
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
Midterm Exam
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 5
Tutorial
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
Project
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 5
Tests
AI: Not AllowedAlignment with Learning Outcomes : 1 2 3 4 5
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 3 ECTS credit course corresponds to 75 hours of total student workload, distributed as follows:
Lecture Hours
28 hours ⏳ (14 week × 2 h)
Home study
14 hours ⏳ (14 week × 1 h)
Midterm Exam Preparation
4 hours ⏳ (2 week × 2 h)
Final Exam Preparation
4 hours ⏳ (2 week × 2 h)
Project
5 hours ⏳ (5 week × 1 h)
Tutorials
20 hours ⏳ (10 week × 2 h)
75 Total Workload Hours
3 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 [ENS101] 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 Sep 09, 2025 | International University of Sarajevo
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Referencing Curricula Print this page
| Course Code | Course Title | Weekly Hours* | ECTS | Weekly Class Schedule | ||||||
| T | P | |||||||||
| ENS101 | Introduction to Engineering | 2 | 2 | 3 | ||||||
| Prerequisite | None | It is a prerequisite to | - | |||||||
| Lecturer | Tarik Namas | Office Hours / Room / Phone | Tuesday: 14:00-16:00 Wednesday: 14:00-16:00 Thursday: 15:00-16:00 |
|||||||
| tnamas@ius.edu.ba | ||||||||||
| Assistant | Mr. Anes Hadziomerovic for robotic part, TAs for tutorial. Reach Prof. directly. | Assistant E-mail | ahadziomerovic@ius.edu.ba | |||||||
| Course Objectives | The aims of this course are: - to introduce engineering students to methods of problem-solving. - to introduce engineering students to various skills related to communication and team work - to introduce general engineering computation software (SciLab, MATLAB, Excell) - to introduce engineering students to the importance of modeling and simulation in engineering work, and the tools to achieve that. |
|||||||||
| Textbook | Stephan, Park, Sill, Bowman & Ohland, “Thinking Like an Engineer”, 3rd edition, Pearson, 2015. Landis, R.B., | |||||||||
| Additional Literature |
|
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| Learning Outcomes | After successful completion of the course, the student will be able to: | |||||||||
|
||||||||||
| Teaching Methods | Student-engaged class discussions. Student presentations. Regular lab-book keeping. Teamwork. Continuous evaluation and feedback on progress. | |||||||||
| Teaching Method Delivery | Face-to-face | Teaching Method Delivery Notes | ||||||||
| WEEK | TOPIC | REFERENCE | ||||||||
| Week 1 | Introduction and course mechanics, Every day engineering | Ch01 | ||||||||
| Week 2 | Ethics/ Introduction to Octave | Ch02/ Ch015 | ||||||||
| Week 3 | Design, team work, project management / Algorithms, functions | Ch03/ Ch16 | ||||||||
| Week 4 | Engineering communications/ Algorithms, functions | Ch04/ Ch16 | ||||||||
| Week 5 | Estimation / Inputs-Outputs | Ch05/ Ch17 | ||||||||
| Week 6 | Solving problems / Logic and Conditions | Ch06/ Ch18 | ||||||||
| Week 7 | Abstractions and thinking in abstract way / Looping | class notes/ Ch19 | ||||||||
| Week 8 | Midterm exam | class notes | ||||||||
| Week 9 | Graphs / More on plotting and data visualization | Ch11 / class notes | ||||||||
| Week 10 | Models and systems / Problems to be solved using Octave | Ch12 / class notes | ||||||||
| Week 11 | Mathematical Models / Word processing, Latex | Ch13 / class notes | ||||||||
| Week 12 | Statistics / Word processing, Latex / Project - poster presentation groups | Ch14 / class notes | ||||||||
| Week 13 | Work on project and follow up | class notes | ||||||||
| Week 14 | Work on project and follow up | class notes | ||||||||
| Week 15 | Work on project and follow up - Presentation | class notes | ||||||||
| Assessment Methods and Criteria | Evaluation Tool | Quantity | Weight | Alignment with LOs | AI Usage |
| Final Exam | 1 | 40 | 1,2,3,4,5 | Not Allowed | |
| Semester Evaluation Components | |||||
| Midterm Exam | 1 | 20 | 1,2,3,5 | Not Allowed | |
| Tutorial | 10 | 10 | 1,2,3,4,5 | Not Allowed | |
| Project | 1 | 20 | 1,2,3,5 | Not Allowed | |
| Tests | 10 | 10 | 1,2,3,4,5 | Not Allowed | |
| *** ECTS Credit Calculation *** | |||||
| Activity | Hours | Weeks | Student Workload Hours | Activity | Hours | Weeks | Student Workload Hours | |||
| Lecture Hours | 2 | 14 | 28 | Home study | 1 | 14 | 14 | |||
| Midterm Exam Preparation | 2 | 2 | 4 | Final Exam Preparation | 2 | 2 | 4 | |||
| Project | 1 | 5 | 5 | Tutorials | 2 | 10 | 20 | |||
| Total Workload Hours = | 75 | |||||||||
| *T= Teaching, P= Practice | ECTS Credit = | 3 | ||||||||
| Course Academic Quality Assurance: Semester Student Survey | Last Update Date: 19/09/2025 | |||||||||