Pamukkale University
University is the guide to life
Welcome to PAU;
Prospective Student
Our Students
Our Staff
TR
Information Package & Course Catalogue
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
THIRD CYCLE - DOCTORATE DEGREE
THE GRADUATE SCHOOL OF SOCIAL SCIENCES
MANAGEMENT INFORMATION SYSTEMS DEPARTMENT
2315 MANAGEMENT INFORMATION SYSTEMS
Course Information
Course Learning Outcomes
Course's Contribution To Program
ECTS Workload
Course Details
Print
COURSE INFORMATION
Course Code
Course Title
L+P Hour
Semester
ECTS
YOBS 538
INTRODUCTION TO DATA SCIENCE
3 + 1
2nd Semester
7,5
COURSE DESCRIPTION
Course Level
Doctorate Degree
Course Type
Elective
Course Objective
This course lays the foundation for the more advanced courses related to data science and analytics. The broad goal of this course is to provide an introduction to the field of data science and familiarize students with the applications of statistical techniques and computational methods for analyzing data and extracting knowledge.
Course Content
In this course, (1) statistical methods to summarize data and identify relationships (2) methods for formulating new hypotheses and drawing accurate conclusions from data and (3) techniques for statistical and computational analysis to make predictions based on data will be covered
Prerequisites
No the prerequisite of lesson.
Corequisite
No the corequisite of lesson.
Mode of Delivery
Face to Face
COURSE LEARNING OUTCOMES
COURSE'S CONTRIBUTION TO PROGRAM
Data not found.
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
3
42
Assignments
2
40
80
Mid-terms
1
13
13
Final examination
1
18
18
Total Work Load
ECTS Credit of the Course
195
7,5
COURSE DETAILS
Select Year
All Years
2024-2025 Fall
2023-2024 Spring
2020-2021 Fall
Course Term
No
Instructors
Details
2024-2025 Fall
1
ÖZLÜ DOLMA
Details
2023-2024 Spring
1
ÖZLÜ DOLMA
Print
Course Details
Course Code
Course Title
L+P Hour
Course Code
Language Of Instruction
Course Semester
YOBS 538
INTRODUCTION TO DATA SCIENCE
3 + 1
1
Turkish
2024-2025 Fall
Course Coordinator
E-Mail
Phone Number
Course Location
Attendance
Asts. Prof. Dr. ÖZLÜ DOLMA
odolma@pau.edu.tr
Course location is not specified.
%
Goals
This course lays the foundation for the more advanced courses related to data science and analytics. The broad goal of this course is to provide an introduction to the field of data science and familiarize students with the applications of statistical techniques and computational methods for analyzing data and extracting knowledge.
Content
In this course, (1) statistical methods to summarize data and identify relationships (2) methods for formulating new hypotheses and drawing accurate conclusions from data and (3) techniques for statistical and computational analysis to make predictions based on data will be covered
Topics
Materials
Materials are not specified.
Resources
Course Assessment
Assesment Methods
Percentage (%)
Assesment Methods Title
Final Exam
50
Final Exam
Midterm Exam
50
Midterm Exam
L+P:
Lecture and Practice
PQ:
Program Learning Outcomes
LO:
Course Learning Outcomes
{1}
##LOC[OK]##
{1}
##LOC[OK]##
##LOC[Cancel]##
{1}
##LOC[OK]##
##LOC[Cancel]##
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