| ARTIFICIAL INTELLIGENCE ENGINEERING | |||||
| Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 | ||
| Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
| AIN1001 | Computer Programming I (Python) | Fall | 2 | 2 | 3 | 5 |
| The course opens with the approval of the Department at the beginning of each semester |
| Language of instruction: | En |
| Type of course: | Must Course |
| Course Level: | Bachelor |
| Mode of Delivery: | Hybrid |
| Course Coordinator : | Instructor MUSTAFA ÜMİT ÖNER |
| Course Objectives: | This course introduces the Python programming language with an object-oriented approach. Students will be able to acquire basic programming skills using Python language and develop applications to solve engineering problems in an integrated development environment (IDE). |
|
The students who have succeeded in this course; Within completing this course, the student will be able to: 1. Define the basic concepts in Python programming language. 2. Develop, test, and run programs in order to solve a specific software problem. 3. Define the basic data types. 4. Define arithmetic, logical expressions, type conversations, assignment expressions, selection, and iteration controls. 5. Demonstrate the ability to create and use functions. 6. Demonstrate the ability to use logical control expressions. 7. Define the datasets. 8. Demonstrate the ability to use libraries prepared for Python when developing applications. |
| Introduction to Computers and Programming Algorithms, Flowcharts, Pseudocodes Data Types and Expressions Decision Structures Functions Strings Loops Functions Arrays & Lists Files Exception Handling |
| Week | Subject | Related Preparation | |
| 1) | Orientation | -Course Schedule -Expectations | |
| 2) | Introduction to Computers and Programming Algorithms, Flowcharts, Pseudocodes | -Set up your environment -Read Chapters 1 & 2 | |
| 3) | Data Types and Expressions | Chapter 1 & 2 | |
| 4) | Decision Structures | Chapter 3 | |
| 5) | Loops | Chapter 4 | |
| 6) | Functions | Chapter 5 | |
| 7) | Functions | Chapter 5 | |
| 8) | MIDTERM & Lab Exam #1 | ||
| 9) | Arrays & Lists | Chapter 7 | |
| 10) | Strings | Chapter 8 | |
| 11) | Files | Chapter 6 | |
| 12) | Exception Handling & Lab Exam #2 | Chapter 6 | |
| 13) | Case Study I – Shopping Cart | ||
| 14) | Case Study II – Gas Prices | ||
| Course Notes: | Recommended Textbook: Tony Gaddis, "Starting out With Python", 4th edition, Pearson |
| References: |
| Semester Requirements | Number of Activities | Level of Contribution |
| Attendance | % 0 | |
| Laboratory | 2 | % 30 |
| Application | % 0 | |
| Field Work | % 0 | |
| Special Course Internship (Work Placement) | % 0 | |
| Quizzes | % 0 | |
| Homework Assignments | % 0 | |
| Presentation | % 0 | |
| Project | % 0 | |
| Seminar | % 0 | |
| Midterms | 1 | % 30 |
| Preliminary Jury | % 0 | |
| Final | 1 | % 40 |
| Paper Submission | % 0 | |
| Jury | % 0 | |
| Bütünleme | % 0 | |
| Total | % 100 | |
| PERCENTAGE OF SEMESTER WORK | % 60 | |
| PERCENTAGE OF FINAL WORK | % 40 | |
| Total | % 100 | |
| Activities | Number of Activities | Duration (Hours) | Workload |
| Course Hours | 14 | 2 | 28 |
| Laboratory | 14 | 2 | 28 |
| Application | 0 | 0 | 0 |
| Special Course Internship (Work Placement) | 0 | 0 | 0 |
| Field Work | 0 | 0 | 0 |
| Study Hours Out of Class | 0 | 0 | 0 |
| Presentations / Seminar | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Homework Assignments | 0 | 0 | 0 |
| Quizzes | 2 | 6 | 12 |
| Preliminary Jury | 0 | 0 | 0 |
| Midterms | 1 | 20 | 20 |
| Paper Submission | 0 | 0 | 0 |
| Jury | 0 | 0 | 0 |
| Final | 1 | 28 | 28 |
| Total Workload | 116 | ||
| No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
| Program Outcomes | Level of Contribution | |
| 1) | Have sufficient background in mathematics, science and artificial intelligence engineering. | 5 |
| 2) | Use theoretical and applied knowledge in the fields of mathematics, science and artificial intelligence engineering together for engineering solutions. | 5 |
| 3) | Identify, define, formulate and solve engineering problems, select and apply appropriate analytical methods and modeling techniques for this purpose. | 3 |
| 4) | Analyse a system, system component or process and design it under realistic constraints to meet desired requirements; apply modern design methods in this direction. | 3 |
| 5) | Select and use modern techniques and tools necessary for engineering applications. | 4 |
| 6) | Design and conduct experiments, collect data, and analyse and interpret results. | 4 |
| 7) | Work effectively both as an individual and as a multi-disciplinary team member. | 4 |
| 8) | Access information via conducting literature research, using databases and other resources | |
| 9) | Follow the developments in science and technology and constantly update themself with an awareness of the necessity of lifelong learning. | |
| 10) | Use information and communication technologies together with computer software with at least the European Computer License Advanced Level required by their field. | 5 |
| 11) | Communicate effectively, both verbal and written; know a foreign language at least at the European Language Portfolio B1 General Level. | |
| 12) | Have an awareness of the universal and social impacts of engineering solutions and applications; know about entrepreneurship and innovation; and have an awareness of the problems of the age. | |
| 13) | Have a sense of professional and ethical responsibility. | |
| 14) | Have an awareness of project management, workplace practices, employee health, environment and work safety; know the legal consequences of engineering practices. |