STATISTICAL MACHINE LEARNING
- Course
- DASC311 - STATISTICAL MACHINE LEARNING
- Department
- Data Science - English - Undergraduate
- Course Type
- Course
- Status
- Required
- Language
- English
- Credit
- 3
- ECTS
- 6
- T+P+L
- 3 + 0 + 0
- Course Coordinator(s)
- Asst. Prof. Dr. Yasemin BAY
- Prerequisite
- -
Course Description
In this course, statistical machine learning which has roots in computer science, artificial intelligence and statistics is covered and a broad understanding of algorithms that allow computers to improve their performance through the process of ‘learning’ and enable them to make decisions and predictions is provided. Fundamental methods are taught and applied to real data. The term statistical in title emphasizes the statistical techniques, which form dominant approaches to machine learning. The course integrates methodology with theoretical underpinnings, computational elements, and statistical theory issues. By completion of this course, students are expected to learn about supervised and unsupervised learning approaches to speech recognition, internet search, bioinformatics, image and audio signal analysis, data mining and exploratory data analysis.
STATISTICAL MACHINE LEARNING
Evaluation Tools (Active Term)
| Item | Type | Weight (%) |
|---|---|---|
| Midterm | Midterm | 30 |
| Final | Final | 40 |
| Project | Project | 20 |
| Assignment | Assignment | 10 |
| Total | 100 | |
Course outcomes
No course outcomes have been defined yet.
Course Syllabus
No weekly content has been defined yet.
Reference Books & Course Materials
No reference books have been listed.
Learning Outcomes
No learning outcomes have been defined.
Program Outcomes
- P01 Be able to understand and apply security protocol and tools to security challenges faced in organizations
- P02 Be able to design security software to combat security issues
- P03 Be able to identify, categorize, and develop security solutions for computer orientated challenges.
- P04 Be able to demonstrate autonomy and responsibility in managing computer security projects
- P05 Be able to follow the state of the arts concepts in computer technology security
- P06 Be able to design, implement, and evaluate a computational system to meet desired security needs within realistic constraints
- P07 Be able to use appropriate security techniques, protocols, skills, and tools necessary for securing computer systems
- P08 Be able to apply effective communication skills consistent with the professional environment
- P09 Be able to apply effective collaboration skills in teamwork consistent with the professional environment
- P10 Be able to apply appropriate security technology and techniques to facilitate a safe operation in an organization
Po-Lo Matrix
The PO-LO matrix has not been populated yet.