COP4434 IBM Big Data and AnalyticsBahçeşehir UniversityDegree Programs ADVERTISINGGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
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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 : Dr. Öğr. Üyesi CEMAL OKAN ŞAKAR
Course Lecturer(s): Prof. Dr. TAŞKIN KOÇAK
Dr. Öğr. Üyesi 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.

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:

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) To be able to apply theoretical concepts related to mass communication, consumer behavior, psychology, persuasion,sociology, marketing, and other related fields to understand how advertising and brand communication works in a free-market economy. 2
2) To be able to critically discuss and interpret theories, concepts, methods, tools and ideas in the field of advertising. 2
3) To be able to research, create, design, write, and present an advertising campaign and brand strategies of their own creation and compete for an account as they would at an advertising agency. 2
4) To be able to analyze primary and secondary research data for a variety of products and services. 2
5) To be able to develop an understanding of the history of advertising as it relates to the emergence of mass media outlets and the importance of advertising in the marketplace. 2
6) To be able to follow developments, techniques, methods, as well as research in advertising field; and to be able to communicate with international colleagues in a foreign language. (“European Language Portfolio Global Scale”, Level B1) 2
7) To be able to take responsibility in an individual capacity or as a team in generating solutions to unexpected problems that arise during implementation process in the Advertising field. 3
8) To be able to understand how advertising works in a global economy, taking into account cultural, societal, political, and economic differences that exist across countries and cultures. 2
9) To be able to approach the dynamics of the field with an integrated perspective, with creative and critical thinking, develop original and creative strategies. 2
10) To be able to to create strategic advertisements for print, broadcast, online and other media, as well as how to integrate a campaign idea across several media categories in a culturally diverse marketplace. 2
11) To be able to use computer software required by the discipline and to possess advanced-level computing and IT skills. (“European Computer Driving Licence”, Advanced Level) 2
12) To be able to identify and meet the demands of learning requirements. 2
13) To be able to develop an understanding and appreciation of the core ethical principles of the advertising profession. 2