| Week |
Subject |
Related Preparation |
| 1) |
Introduction to Machine Learning |
- |
| 2) |
Dataset preparation, Feature extraction, Evaluation and Comparing |
Reference Book |
| 3) |
Classification methods - K-NN |
" |
| 4) |
Classification methods - Naive Bayes Classificaion, Bayesian networks |
" |
| 5) |
Classification methods - Linear regression |
" |
| 6) |
Classification methods - Decision trees |
" |
| 6) |
Classification methods - Decision trees |
" |
| 7) |
Classification methods - Support Vector Machines |
" |
| 8) |
Midterm |
Lecture notes, reference books |
| 9) |
Clusturing Methods - K-means |
" |
| 10) |
Clusturing Methods - Hierarchical Clustering |
" |
| 11) |
Feature Selection Methods |
" |
| 12) |
Dimension reduction methods |
" |
| 13) |
Neural Networks |
" |
| 14) |
Project Presentation |
- |
| 15) |
Final Exam |
Lecture notes, books, exercises |
| |
Program Outcomes |
Level of Contribution |
| 1) |
Sufficient knowledge in mathematics, science and software engineering discipline-specific topics; the theoretical and practical knowledge in these areas, the ability to use in complex engineering problems. |
|
| 2) |
The ability to identify, formulate, and solve complex engineering problems; selecting and applying appropriate analysis and modelling methods for this purpose. |
|
| 3) |
The ability to design a complex system, process, device or product under realistic constraints and conditions to meet specific requirements; the ability to apply modern design methods for this purpose. |
|
| 4) |
Ability to develop, select and use modern techniques and tools necessary for analysis and solution of complex problems in engineering applications; ability to use information technologies effectively. |
|
| 5) |
Ability to design experiments, conduct experiments, collect data, analyse and interpret the results of complex engineering problems or discipline-specific research topics. |
|
| 6) |
Disiplin içi ve çok disiplinli takımlarda etkin biçimde çalışabilme becerisi; bireysel çalışma becerisi. |
|
| 7) |
Awareness of the need for lifelong learning; access to knowledge, ability to follow developments in science and technology, and constant self-renewal. |
|
| 8) |
Effective communication skills in Turkish oral and written communication; at least one foreign language knowledge; ability to write effective reports and understand written reports, to prepare design and production reports, to make effective presentations, to give clear and understandable instructions and to receive. |
|
| 9) |
Conformity to ethical principles, professional and ethical responsibility; Information on standards used in engineering applications. |
|
| 10) |
Information on practices in business, such as project management, risk management and change management; awareness about entrepreneurship, innovation; information on sustainable development. |
|
| 11) |
Information on the effects of engineering applications on health, environment, and safety in universal and social dimensions, and on the problems of the modern age in engineering; awareness of the legal consequences of engineering solutions. |
|
| 12) |
Adequate skills in the analysis, design, verification, evaluation, implementation, implementation, and maintenance of software systems |
|
Istanbul Health and Technology University INFORMATION PACKAGE / COURSE CATALOGUE