SECTION I: GENERAL INFORMATION ABOUT THE COURSE |
Course Code | Course Name | Year | Semester | Theoretical | Practical | Credit | ECTS |
70619MEEOS-CME0132 | Machine Learning | 0 | Fall |
3 | 0 | 3 | 6 |
Course Type : | Non-Departmental Elective |
Cycle: | Master TQF-HE:7. Master`s Degree QF-EHEA:Second Cycle EQF-LLL:7. Master`s Degree |
Language of Instruction: | English |
Prerequisities and Co-requisities: | N/A |
Mode of Delivery: | |
Name of Coordinator: | Instructor EMRAH SEZER |
Dersin Öğretim Eleman(lar)ı: | |
Dersin Kategorisi: |
SECTION II: INTRODUCTION TO THE COURSE |
Course Objectives: | The aim of this course is to introduce machine learning topics such as regression, clustering and classification. In this course, a machine learning project will be developed using the Python programming language. |
Course Content: | The course is a major component of the Project-Based Learning (PBL) curriculum. Students do projects in certain areas using a Python programming language. It is at same time tool-based in the sense that students the necessary tools for the course such as the programming language, the project management tool, etc. The course is self-learning based, meaning that the student learns the tool to be used, explores the project, develops the project deliverables herself. The project development methodology is deliverable-driven, meaning that the student produces certain deliverables along the timeline of the project. Deliverables are reviwed at each step and the review forms the basis of the work to be done by the student at the next step. |
The evolutionary development approach will be used in the projects, and the project will be conducted in a step by step manner. Particular deliverables will be produced and will be submitted by the students at certain steps. Deliverables will be reviewed by the project manager or by a jury, depending on the particular deliverable. |
Knowledge (Described as Theoritical and/or Factual Knowledge.) | ||
Skills (Describe as Cognitive and/or Practical Skills.) | ||
Competences (Described as "Ability of the learner to apply knowledge and skills autonomously with responsibility", "Learning to learn"," Communication and social" and "Field specific" competences.) |
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Course Notes / Textbooks: | ONLINEBEYKOZ is the online learning platform for the course. It is a repository for the course, including learning material such as reading materials, lectures notes in scorm format, web resources, ppt presentations, videos, etc., on topical areas of the projects offered (such AI, machine learning, deep learning, data science, neural networks, IoT, statistical reasoning, etc), on tools, and on project specific application areas (such as medical diagnosis, risk analysis, natural language processing, image processing, etc). Onlinebeykoz also offers facilities such as forum discussion, wiki, question banks, exams, announcements, etc. It is at the same time an electronic communication medium for the course for exchanging material between the instructor and the students. |
References: |
SECTION III: RELATIONSHIP BETWEEN COURSE UNIT AND COURSE LEARNING OUTCOMES (CLOs) |
CLOs/PLOs |
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No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Programme Learning Outcomes | Contribution Level (from 1 to 5) |
SECTION IV: TEACHING-LEARNING & ASSESMENT-EVALUATION METHODS OF THE COURSE |
Lectures | |
Discussion | |
Case Study | |
Problem Solving | |
Demonstration | |
Views | |
Laboratory | |
Reading | |
Homework | |
Project Preparation | |
Thesis Preparation | |
Peer Education | |
Seminar | |
Technical Visit | |
Course Conference | |
Brain Storming | |
Questions Answers | |
Individual and Group Work | |
Role Playing-Animation-Improvisation | |
Active Participation in Class |
Midterm | |
Presentation | |
Final Exam | |
Quiz | |
Report Evaluation | |
Homework Evaluation | |
Oral Exam | |
Thesis Defense | |
Jury Evaluation | |
Practice Exam | |
Evaluation of Implementation Training in the Workplace | |
Active Participation in Class | |
Participation in Discussions |
LEARNING & TEACHING METHODS | ASSESMENT & EVALUATION METHODS | ||||||||||||||||||||
-Lectures | -Midterm | ||||||||||||||||||||
-Discussion | -Presentation | ||||||||||||||||||||
-Case Study | -Final Exam | ||||||||||||||||||||
-Problem Solving | -Quiz | ||||||||||||||||||||
-Demonstration | -Report Evaluation | ||||||||||||||||||||
-Views | -Homework Evaluation | ||||||||||||||||||||
-Laboratory | -Oral Exam | ||||||||||||||||||||
-Reading | -Thesis Defense | ||||||||||||||||||||
-Homework | -Jury Evaluation | ||||||||||||||||||||
-Project Preparation | -Practice Exam | ||||||||||||||||||||
-Thesis Preparation | -Evaluation of Implementation Training in the Workplace | ||||||||||||||||||||
-Peer Education | -Active Participation in Class | ||||||||||||||||||||
-Seminar | - Participation in Discussions | ||||||||||||||||||||
-Technical Visit | |||||||||||||||||||||
-Course Conference | |||||||||||||||||||||
-Brain Storming | |||||||||||||||||||||
-Questions Answers | |||||||||||||||||||||
-Individual and Group Work | |||||||||||||||||||||
-Role Playing-Animation-Improvisation | |||||||||||||||||||||
-Active Participation in Class |
Measurement and Evaluation Methods | # of practice per semester | Level of Contribution |
Project | 2 | % 34.00 |
Midterms | 1 | % 16.00 |
Semester Final Exam | 1 | % 50.00 |
Total | % 100 | |
PERCENTAGE OF SEMESTER WORK | % 50 | |
PERCENTAGE OF FINAL WORK | % 50 | |
Total | % 100 |
SECTION V: WORKLOAD & ECTS CREDITS ALLOCATED FOR THE COURSE |
WORKLOAD OF TEACHING & LEARNING ACTIVITIES | |||
Teaching & Learning Activities | # of Activities per semester | Duration (hour) | Total Workload |
Course | 12 | 3 | 36 |
Laboratory | 0 | 0 | 0 |
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 | 1 | 2 | 2 |
Homework Assignments | 2 | 2 | 4 |
Total Workload of Teaching & Learning Activities | - | - | 42 |
WORKLOAD OF ASSESMENT & EVALUATION ACTIVITIES | |||
Assesment & Evaluation Activities | # of Activities per semester | Duration (hour) | Total Workload |
Quizzes | 0 | 0 | 0 |
Midterms | 1 | 2 | 2 |
Semester Final Exam | 1 | 2 | 2 |
Total Workload of Assesment & Evaluation Activities | - | - | 4 |
TOTAL WORKLOAD (Teaching & Learning + Assesment & Evaluation Activities) | 46 | ||
ECTS CREDITS OF THE COURSE (Total Workload/25.5 h) | 6 |