Computer Programming
Course Details
KTO KARATAY UNIVERSITY
Trade and Industry Vocational School
Programme of Computer Programming
Course Details
Trade and Industry Vocational School
Programme of Computer Programming
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 03841202 | Current Technologies In Informatics | 2025 | Spring | 4 | 2+2+0 | 5 | 5 |
| Course Type | Elective |
| Course Cycle | Associate (Short Cycle) (TQF-HE: Level 5 / QF-EHEA: Short Cycle / EQF-LLL: Level 5) |
| Course Language | Turkish |
| Methods and Techniques | 1. Theoretical Explanation: The topics are explained theoretically within the scope of the course. Students listen to topic explanations in order to understand the basic concepts of programming and the logic of algorithms. 2. Applied Studies: Students carry out studies with various examples under the mentorship of the course instructor in order to apply the topics explained theoretically. Gains are tried to be achieved. 3. Step-by-Step Solution: The encountered problems are solved step by step and how each step works is explained. With this method, students are provided with a better command of the topics. 4. Real Life Examples: Real life examples and problem scenarios are presented for a better understanding of the topics. In this way, students see how to use what they have learned in practice. 5. Laboratory Sheets and Quizzes: Students' progress is evaluated with weekly laboratory handouts and pre-exam quizzes, and whether the topics are understood is monitored. |
| Mode of Delivery | Face to Face |
| Prerequisites | There are no prerequisites for the course. All students receive instruction starting from the basic level. |
| Coordinator | - |
| Instructor(s) | Lect. Uğur POLAT |
| Instructor Assistant(s) | - |
Course Instructor(s)
| Name and Surname | Room | E-Mail Address | Internal | Meeting Hours |
|---|---|---|---|---|
| Lect. Uğur POLAT | C-129 | [email protected] | 7860 | Thursday 14.00-16.00 |
Course Content
Concepts of Digital Transformation, Industry 4.0 and Industry 5.0; Fundamentals of Artificial Intelligence, Machine Learning, and Generative AI models; Cloud Computing architectures and Edge Computing; Open-source vs. closed-source software ecosystems; Big Data analytics, data privacy, and security under GDPR/KVKK; Core principles of cybersecurity, attack, and defense strategies; Blockchain technology, smart contracts, and crypto assets; Internet of Things (IoT), sensor networks, and Smart City applications; 5G, 6G, and next-generation communication infrastructure; Metaverse, Augmented Reality (AR), and Virtual Reality (VR) technologies; Green IT, sustainability, and carbon footprint reduction; Future work models, remote work ecosystems, and digital nomadism; Ethical vision in information technology, legal regulations, and future technology trends.
Objectives of the Course
The objective of this course is to provide students with a holistic understanding of emerging technologies, digital transformation processes, and the modern IT ecosystem. The course aims to equip students with the skills to follow, evaluate, and adopt technological advancements by exploring the core principles, use cases, societal impacts, and ethical dimensions of key topics such as Digital Transformation (Industry 4.0/5.0), Artificial Intelligence & Generative AI, Cloud & Edge Computing, Big Data & Data Privacy, Cybersecurity, Blockchain, Internet of Things (IoT), Next-Gen Communication Technologies (5G/6G), Metaverse/AR/VR, Green IT, and Future Work Models.
Contribution of the Course to Field Teaching
| Basic Vocational Courses | |
| Specialization / Field Courses | X |
| Support Courses | |
| Transferable Skills Courses | X |
| Humanities, Communication and Management Skills Courses |
Relationships between Course Learning Outcomes and Program Outcomes
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Program Learning Outcomes | Level |
|---|---|---|
| P4 | Effectively uses information technologies (software, programs, animations, etc.) related to her/his profession. | 5 |
| P1 | He/she has basic, current and applied information about his/her profession. | 5 |
| P2 | Gains knowledge about occupational health and safety, environmental awareness and quality processes. | 3 |
| P3 | He/She follows current developments and practices in his profession and uses them effectively. | 5 |
| P5 | Has the ability to independently evaluate professional problems and issues with an analytical and critical approach and propose solutions. | 4 |
| P6 | Can present his/her thoughts effectively through written and verbal communication at the level of knowledge and skills and expresses them in an understandable manner. | 3 |
| P9 | It has social, scientific, cultural and ethical values in the stages of collecting data related to its field, applying it and announcing the results. | 3 |
| P11 | Creates algorithms and data structures and performs mathematical calculations. | 4 |
| P14 | Tests software and fixes bugs. | 5 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Knows how to develop algorithms and creates a data structure suitable for the algorithm. | P.4.1 | 1,7 |
| O2 | Ability to use artificial intelligence methods | P.4.4 | 1,7 |
| O3 | Have knowledge about current programming languages. | P.4.5 | 1,7 |
| O4 | Knows the basic elements of a computer. | P.1.1 | 1 |
| O5 | Knows how to use the internet and do research. | P.1.2 | 1 |
| O6 | Can perform basic mathematical analyses related to his/her profession. | P.1.3 | 1 |
| O7 | Has knowledge about Computer and Security. | P.1.4 | 1 |
| O8 | Evaluates environmental protection and sustainability principles | P.2.2 | 1 |
| O9 | Knows current techniques for data analysis. | P.3.1 | 1 |
| O10 | Must know and use current software development platforms. | P.3.2 | 1 |
| O11 | Analyzes complex problems and develops solution strategies | P.3.4 | 1 |
| O12 | Have basic analysis knowledge. | P.3.5 | 1 |
| O13 | Tests software and fixes bugs. | P.5.1 | 1 |
| O14 | Knows analytical, effective research and solution techniques to identify problems. | P.5.2 | 1 |
| O15 | Evaluates alternative solutions and selects the most appropriate one. | P.5.3 | 1 |
| O16 | Evaluate computer science topics and algorithms using critical thinking skills | P.5.4 | 1 |
| O17 | Makes decisions by taking into consideration social, scientific, cultural and ethical values. | P.9.1 | 1 |
| O18 | Follows ethical standards in data collection and analysis | P.9.2 | 1 |
| O19 | Knows and uses current Information Technology platforms. | P.11.2 | 1,7 |
| O20 | Has knowledge of current programming languages. | P.11.3 | 1 |
| O21 | He/she has knowledge about current technology topics such as Artificial Intelligence, Image Processing, Machine Learning. | P.11.6 | 1,7 |
| O22 | He has knowledge in embedded systems and basic electronics. | P.11.8 | 1 |
| ** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7 | |||
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | Digital Transformation and Industry 4.0 / 5.0 |
| 2 | Artificial Intelligence and Generative AI Models |
| 3 | Cloud Computing and Edge Computing |
| 4 | Open Source vs. Closed Source Software |
| 5 | Big Data and Data Privacy |
| 6 | Cybersecurity: Attack and Defense |
| 7 | Pre-Exam Quiz |
| 8 | Midterm exam |
| 9 | Blockchain and Crypto Assets |
| 10 | Internet of Things (IoT) and Smart Cities |
| 11 | 5G, 6G and Communication Technologies |
| 12 | Metaverse, AR (Augmented Reality) and VR (Virtual Reality) |
| 13 | Green IT and Sustainability |
| 14 | General Review and Ethical Vision |
| 15 | Pre-Exam Quiz, Course Review and Discussion |
| 16 | Final Exam |
Textbook or Material
| Resources | Stuart Russell ve Peter Norvig, "Artificial Intelligence: A Modern Approach" |
| Thomas Erl, Ricardo Puttini, Zaigham Mahmood, "Cloud Computing: Concepts, Technology & Architecture" |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | 1 | 20 (%) |
| Field Study | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Seminar | - | - |
| Quiz | 2 | 10 (%) |
| Listening | - | - |
| Midterms | 1 | 30 (%) |
| Final Exam | 1 | 40 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 4 | 56 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 3 | 42 |
| Midterms | 1 | 8 | 8 |
| Quiz | 2 | 5 | 10 |
| Homework | 0 | 0 | 0 |
| Practice | 14 | 1 | 14 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 1 | 6 | 6 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 14 | 14 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 150 | ||
| Total Work Load / 30 | 5 | ||
| Course ECTS Credits: | 5 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P1 | P2 | P3 | P4 | P5 | P9 | P11 |
|---|---|---|---|---|---|---|---|---|
| O1 | Knows the basic elements of a computer. | 4 | - | - | - | - | - | - |
| O2 | Knows how to use the internet and do research. | 4 | - | 3 | - | - | - | - |
| O3 | Can perform basic mathematical analyses related to his/her profession. | 4 | - | - | - | 3 | - | - |
| O4 | Has knowledge about Computer and Security. | 4 | - | - | - | - | - | - |
| O5 | Evaluates environmental protection and sustainability principles | - | 5 | - | - | - | - | - |
| O6 | Knows current techniques for data analysis. | - | - | 4 | - | - | - | - |
| O7 | Must know and use current software development platforms. | - | - | 5 | - | - | - | - |
| O8 | Analyzes complex problems and develops solution strategies | - | - | - | - | 4 | - | - |
| O9 | Have basic analysis knowledge. | - | - | 5 | - | 3 | - | - |
| O10 | Knows how to develop algorithms and creates a data structure suitable for the algorithm. | - | - | - | 5 | - | - | 4 |
| O11 | Ability to use artificial intelligence methods | - | - | - | 5 | - | - | 5 |
| O12 | Have knowledge about current programming languages. | - | - | - | 5 | - | - | 3 |
| O13 | Tests software and fixes bugs. | - | - | - | - | 5 | - | - |
| O14 | Knows analytical, effective research and solution techniques to identify problems. | - | - | - | - | 4 | - | - |
| O15 | Evaluates alternative solutions and selects the most appropriate one. | - | - | 3 | - | 5 | - | - |
| O16 | Evaluate computer science topics and algorithms using critical thinking skills | - | - | - | - | 5 | - | - |
| O17 | Makes decisions by taking into consideration social, scientific, cultural and ethical values. | - | - | - | - | - | 5 | - |
| O18 | Follows ethical standards in data collection and analysis | - | - | - | - | - | 5 | - |
| O19 | Knows and uses current Information Technology platforms. | - | - | 4 | - | - | - | - |
| O20 | Has knowledge of current programming languages. | - | - | 3 | 4 | - | - | - |
| O21 | He/she has knowledge about current technology topics such as Artificial Intelligence, Image Processing, Machine Learning. | - | - | 4 | - | - | - | 5 |
| O22 | He has knowledge in embedded systems and basic electronics. | - | - | 3 | - | - | - | - |