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THIRD CYCLE - DOCTORATE DEGREE
THE GRADUATE SCHOOL OF SOCIAL SCIENCES
INTERNATIONAL TRADE AND FINANCE DEPARTMENT
2205 INTERNATIONAL TRADE AND FINANCE
Course Information
Course Learning Outcomes
Course's Contribution To Program
ECTS Workload
Course Details
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COURSE INFORMATION
Course Code
Course Title
L+P Hour
Semester
ECTS
UTFB 522
BIG DATA AND MACHINE LEARNING
3 + 0
2nd Semester
7,5
COURSE DESCRIPTION
Course Level
Doctorate Degree
Course Type
Elective
Course Objective
The aim of the course is to learn the concepts of artificial intelligence, big data and machine learning by applying problems.
Course Content
The content of the course includes the concept of data manipulation, big data analytics, classification, prediction and regression analysis methods.
Prerequisites
No the prerequisite of lesson.
Corequisite
No the corequisite of lesson.
Mode of Delivery
Face to Face
COURSE LEARNING OUTCOMES
1
Understanding of data manipulation, big data analytics, classification, prediction and regression analysis
COURSE'S CONTRIBUTION TO PROGRAM
PO 01
PO 02
PO 03
LO 001
5
3
3
Sub Total
5
3
3
Contribution
5
3
3
ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
Activities
Quantity
Duration (Hour)
Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)
14
3
42
Hours for off-the-classroom study (Pre-study, practice)
14
8
112
Mid-terms
1
11
11
Final examination
1
30
30
Total Work Load
ECTS Credit of the Course
195
7,5
COURSE DETAILS
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All Years
2020-2021 Spring
This course is not available in selected semester.
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L+P:
Lecture and Practice
PQ:
Program Learning Outcomes
LO:
Course Learning Outcomes
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Home Page
About University
Name And Address
Acedemic Authorities
General Discription
Academic Calendar
General Admission Requirements
Recognition of Prior Learning
General Registration Procedures
ECTS Credit Allocation
Academic Guidance
Information For Students
Cost Of Living
Accommodation
Meals
Medical Facilities
Facilities for Special Needs Students
Insurance
Financial Support for Students
Student Affairs
Learning Facilities
International Programs
Language Courses
Internships
Sports Facilities and Leisure Activities
Student Associations
Practical Information for Mobile Students
Degree Programmes