| 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) |
Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledge in these areas in complex engineering problems. |
|
| 2) |
Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modelling methods for this purpose. |
|
| 3) |
Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose. |
|
| 4) |
Ability to devise, select, and use modern techniques and tools needed for analysing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively. |
|
| 5) |
Ability to design and conduct experiments, gather data, analyse and interpret results for investigating complex engineering problems or discipline specific research questions. |
|
| 6) |
Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually. |
|
| 7) |
Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions. |
|
| 8) |
Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself. |
|
| 9) |
Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice. |
|
| 10) |
Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development. |
|
| 11) |
Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions |
|
Istanbul Health and Technology University INFORMATION PACKAGE / COURSE CATALOGUE