1. SECOND CYCLE - MASTER'S DEGREE
  2. THE GRADUATE SCHOOL OF SOCIAL SCIENCES
  3. MANAGEMENT INFORMATION SYSTEMS DEPARTMENT
  4. 2315 MANAGEMENT INFORMATION SYSTEMS
Course Information Course Learning Outcomes Course's Contribution To Program ECTS Workload Course Details
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COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
YOBS 538INTRODUCTION TO DATA SCIENCE3 + 11st Semester7,5

COURSE DESCRIPTION
Course Level Master's 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
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)14342
Hours for off-the-classroom study (Pre-study, practice)14342
Assignments24080
Mid-terms11313
Final examination11818
Total Work Load

ECTS Credit of the Course





195

7,5
COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2023-2024 Spring1ÖZLÜ DOLMA


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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 2023-2024 Spring
Course Coordinator  E-Mail  Phone Number  Course Location Attendance
Asts. Prof. Dr. ÖZLÜ DOLMA odolma@pau.edu.tr İİBF B0212 %
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 MethodsPercentage (%)Assesment Methods Title
Final Exam50Final Exam
Midterm Exam50Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes