TEXTILE AND FASHION DESIGN
Bachelor TR-NQF-HE: Level 6 QF-EHEA: First Cycle EQF-LLL: Level 6

Course Introduction and Application Information

Course Code Course Name Semester Theoretical Practical Credit ECTS
COP4434 IBM Big Data and Analytics Spring 3 0 3 6
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction: English
Type of course: Non-Departmental Elective
Course Level: Bachelor’s Degree (First Cycle)
Mode of Delivery: Face to face
Course Coordinator : Assoc. Prof. CEMAL OKAN ŞAKAR
Course Lecturer(s): Prof. Dr. TAŞKIN KOÇAK
Assoc. Prof. CEMAL OKAN ŞAKAR
Recommended Optional Program Components: None
Course Objectives: The students will take lectures from senior executives from IBM. Each lecture will focus on a different subject and the lecturer will share his/her own experiences together with the theoretical basis of the subject.
The courses will include Business Analytics & Big Data capabilities and service areas including key concepts, services, IBM software, hardware offerings and IBM assets. In addition, industry use cases are used to illustrate effective use of Big Data services. The courses will help students to prepare for a successful professional career.

Learning Outcomes

The students who have succeeded in this course;
Expected benefits are multidimensional such as:
- Graduating engineers being much more ready for the professional work
- Directing academic research (including thesis) to real life problems and business needs
- Creating new industry projects formed as the application of new technologies
Hence, this course will be another good addition to our activities in industry-academia partnership.

Course Content

The course will include Big Data and analytics capabilities and service areas including key concepts, services, IBM software, hardware offerings and IBM assets. In addition, industry use cases are used to illustrate effective use of Big Data services. The teaching methods of the course include lectures, group work, technology-assisted learning, project preparation, and practice.

Weekly Detailed Course Contents

Week Subject Related Preparation
1) Big Data & Analytics for Better Business Outcomes
2) Industry Aligned Big Data, Top Use Cases
3) Overview of Big Data Technology & IBM Big Data Platform
4) IBM Big Data Platform, Data Explorer
5) Data Warehousing
6) Information Integration, Master Data Management, Guardium, OPTIM
7) Hadoop Technology
8) Midterm
9) Master Data Management for Customer
10) Integrating Unstructured Data in the Enterprise
11) Text Analytics
12) Infrastructure for Big Data & Analytics
13) Infrastructure for Big Data & Analytics
14) Recap

Sources

Course Notes / Textbooks: Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by E. Siegel
References: S Chandramouli et al, Big Data Analytics, ISBN: 9789393330468 | Year: 2024

Evaluation System

Semester Requirements Number of Activities Level of Contribution
Quizzes 2 % 5
Project 1 % 25
Midterms 1 % 30
Final 1 % 40
Total % 100
PERCENTAGE OF SEMESTER WORK % 35
PERCENTAGE OF FINAL WORK % 65
Total % 100

ECTS / Workload Table

Activities Number of Activities Duration (Hours) Workload
Course Hours 14 3 42
Project 1 20 20
Quizzes 2 14 28
Midterms 1 25 25
Final 1 30 30
Total Workload 145

Contribution of Learning Outcomes to Programme Outcomes

No Effect 1 Lowest 2 Low 3 Average 4 High 5 Highest
           
Program Outcomes Level of Contribution
1) Understands the principles of artistic creation and basic design and applies the art and design objects he creates within this framework.
2) Conducts the multifaceted research required for textile and fashion design processes and analyzes and interprets the results.
3) Creates original and applicable fabric, clothing and pattern designs by using elements from different historical periods and cultures in accordance with his purpose.
4) Recognizes textile raw materials and equipments.
5) Uses computer programs effectively in the garment and fabric surface design process.
6) Has professional technical knowledge regarding the implementation of clothing designs and production; In this context, recognizes and uses technological tools and equipment.
7) Understands the importance of interdisciplinary interaction and communication in textile and clothing design-production-presentation processes and reflects this on the processes.
8) Works in a programmed and disciplined manner in professional practices.
9) Realizes the necessity of lifelong learning to maintain his productivity, creativity and professional competence.
10) Understands, adopts and applies ethical responsibilities in professional practices; Has knowledge of relevant legal regulations.
11) Establishes effective visual, written and verbal communication in the field of textile and fashion design.
12) Reflects his knowledge on current and contemporary issues from all fields to his professional theoretical and practical studies on textile and clothing design; Understands the social and universal effects of these issues.
13) Has sufficient awareness about social justice, environmental awareness, quality culture and protection of cultural values.