The aim of this course is to introduce and teach the fundamentals of Artificial Intelligence applications.
Course Content
This course contains; Introduction to Artificial Intelligence,Philosophy and History of Artificial Intelligence,Basic Concepts,Problem Solving with Artificial Intelligence,Machine Learning,Unsupervised, Supervised and Reinforcement Learning,Big Data and Computing Technology,Intelligent Agents,Deep Learning,Neural Networks,Natural Language Processing,Computer Vision,Predictive models and sample applications,The Future of Artificial Intelligence.
Dersin Öğrenme Kazanımları
Teaching Methods
Assessment Methods
Knows the concepts of Artificial Intelligence.
10, 16, 9
A, E, H
Knows the types of machine learning.
10, 16, 9
A, E
Knows the application areas of machine learning.
10, 16, 9
A, E, F
Knows the concepts of big data and computing technology.
16, 23, 9
A, E, F, G
Conducts current research in the field of artificial intelligence
A: Traditional Written Exam, E: Homework, F: Project Task, G: Quiz, H: Performance Task
Course Outline
Order
Subjects
Preliminary Work
1
Introduction to Artificial Intelligence
2
Philosophy and History of Artificial Intelligence
3
Basic Concepts
4
Problem Solving with Artificial Intelligence
5
Machine Learning
6
Unsupervised, Supervised and Reinforcement Learning
7
Big Data and Computing Technology
8
Intelligent Agents
9
Deep Learning
10
Neural Networks
11
Natural Language Processing
12
Computer Vision
13
Predictive models and sample applications
14
The Future of Artificial Intelligence
Resources
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
Has the background in algorithms, programming, and application development in software engineering projects; and has the ability to use them together in business.
X
2
Chooses and uses the proper solution methods and special techniques for programming purpose.
X
3
Uses modern techniques and tools for programming applications.
X
4
Works effectively individually and in teams.
X
5
Implements and follows test cases of developed software and applications.
X
6
Has the awareness in workplace practices, worker health, environmental and workplace safety, professional and ethical responsibility, and legal issues about programming practices.
X
7
Reaches information, and surveys resources for this purpose.
X
8
Aware of the necessity of life-long learning; follows technological advances and renews him/herself.
X
9
Communicates, oral and written, effectively using modern tools.
X
10
Aware of universal and social effects of software solutions and practices; develops new software tools for solving universal problems and social advance.
X
11
Keeps attention in clean and readable code design.
X
12
Considers and follows user centered design principles.
X
Assessment Methods
Contribution Level
Absolute Evaluation
Rate of Midterm Exam to Success
40
Rate of Final Exam to Success
60
Total
100
ECTS / Workload Table
Activities
Number of
Duration(Hour)
Total Workload(Hour)
Course Hours
0
0
0
Guided Problem Solving
0
0
0
Resolution of Homework Problems and Submission as a Report
0
0
0
Term Project
0
0
0
Presentation of Project / Seminar
0
0
0
Quiz
0
0
0
Midterm Exam
0
0
0
General Exam
0
0
0
Performance Task, Maintenance Plan
0
0
0
Total Workload(Hour)
0
Dersin AKTS Kredisi = Toplam İş Yükü (Saat)/30*=(0/30)
0
ECTS of the course: 30 hours of work is counted as 1 ECTS credit.
Detail Informations of the Course
Course Description
Course
Code
Semester
T+P (Hour)
Credit
ECTS
ARTIFICIAL INTELLIGENCE
BPR2214994
Spring Semester
3+0
3
5
Course Program
Prerequisites Courses
Recommended Elective Courses
Language of Course
Turkish
Course Level
Short Cycle (Associate's Degree)
Course Type
Elective
Course Coordinator
Lect. Beyza KOYULMUŞ
Name of Lecturer(s)
Lect. Beyza KOYULMUŞ
Assistant(s)
Aim
The aim of this course is to introduce and teach the fundamentals of Artificial Intelligence applications.
Course Content
This course contains; Introduction to Artificial Intelligence,Philosophy and History of Artificial Intelligence,Basic Concepts,Problem Solving with Artificial Intelligence,Machine Learning,Unsupervised, Supervised and Reinforcement Learning,Big Data and Computing Technology,Intelligent Agents,Deep Learning,Neural Networks,Natural Language Processing,Computer Vision,Predictive models and sample applications,The Future of Artificial Intelligence.
Dersin Öğrenme Kazanımları
Teaching Methods
Assessment Methods
Knows the concepts of Artificial Intelligence.
10, 16, 9
A, E, H
Knows the types of machine learning.
10, 16, 9
A, E
Knows the application areas of machine learning.
10, 16, 9
A, E, F
Knows the concepts of big data and computing technology.
16, 23, 9
A, E, F, G
Conducts current research in the field of artificial intelligence
A: Traditional Written Exam, E: Homework, F: Project Task, G: Quiz, H: Performance Task
Course Outline
Order
Subjects
Preliminary Work
1
Introduction to Artificial Intelligence
2
Philosophy and History of Artificial Intelligence
3
Basic Concepts
4
Problem Solving with Artificial Intelligence
5
Machine Learning
6
Unsupervised, Supervised and Reinforcement Learning
7
Big Data and Computing Technology
8
Intelligent Agents
9
Deep Learning
10
Neural Networks
11
Natural Language Processing
12
Computer Vision
13
Predictive models and sample applications
14
The Future of Artificial Intelligence
Resources
Course Contribution to Program Qualifications
Course Contribution to Program Qualifications
No
Program Qualification
Contribution Level
1
2
3
4
5
1
Has the background in algorithms, programming, and application development in software engineering projects; and has the ability to use them together in business.
X
2
Chooses and uses the proper solution methods and special techniques for programming purpose.
X
3
Uses modern techniques and tools for programming applications.
X
4
Works effectively individually and in teams.
X
5
Implements and follows test cases of developed software and applications.
X
6
Has the awareness in workplace practices, worker health, environmental and workplace safety, professional and ethical responsibility, and legal issues about programming practices.
X
7
Reaches information, and surveys resources for this purpose.
X
8
Aware of the necessity of life-long learning; follows technological advances and renews him/herself.
X
9
Communicates, oral and written, effectively using modern tools.
X
10
Aware of universal and social effects of software solutions and practices; develops new software tools for solving universal problems and social advance.
X
11
Keeps attention in clean and readable code design.
X
12
Considers and follows user centered design principles.
