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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS VYA 5013 INTRODUCTION TO BIG DATA AND DATA SCIENCE COMPULSORY 3 0 0 6

Offered By

DATA MANAGEMENT AND ANALYSIS

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

Offered to

DATA MANAGEMENT AND ANALYSIS

Course Objective

The objective of this course is to define the concepts of big data and related technologies and use softwares in the estimated level.

Learning Outcomes of the Course Unit

1   1. To be able to define basic information related to database. 2   2. To be able to understand the benefits of design of database in daily applications and its necessity. 3   3. To be able to distinguish data structures and differences related to database. 4   4. To be able to present logical data design in database management system. 5   5. To be able to grasp practical aspects of database design.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Data and Database Concept and Database Management System Approach. Data Mapping Software Applications (MapForce) 2 Logical Database Concept and Its Advantages. Data Mapping Software Applications (MapForce) 3 MS ACCESS and SQL Presentations of Project 4 Basic Access Objects: Tables, Forms Final Exam 5 Basic Access Objects: Queries, Reports 6 Reports Applications, Authorising Access to Database 7 Security Applications 8 Midterm 9 Data Mapping Concept 10 Data Mapping Applications

Recomended or Required Reading

Big Data in Practice, Bernard Marr

Planned Learning Activities and Teaching Methods

1- Explanation Method, 2-Explanation by examples, 3-Discussing and analyzing particular issues

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 PRS PRESENTATION 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MTE * 0.30 + PRS * 0.30 + FIN * 0.40 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.30 + PRS * 0.30 + RST* 0.40 *** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 13 3 39 Preparations before/after weekly lectures 13 4 52 Preparation for midterm exam 1 10 10 Preparation for final exam 1 10 10 Preparing assignments 10 4 40 Final 1 2 2 Midterm 1 2 2 TOTAL WORKLOAD (hours) 155

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 LO.1 1 1 1 LO.2 1 1 1 1 1 1 LO.3 1 1 LO.4 1 1 LO.5 1