COP4434 IBM Big Data and AnalyticsBahçeşehir UniversityDegree Programs POLITICAL SCIENCE AND INTERNATIONAL RELATIONSGeneral Information For StudentsDiploma SupplementErasmus Policy StatementNational QualificationsBologna Commission
POLITICAL SCIENCE AND INTERNATIONAL RELATIONS
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
Fall
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) Grasp basic theoretical and conceptual knowledge about the field and relations between them at the level of practice.
2) Possess basic knowledge about the causes and effects of political transformations in societies.
3) Possess knowledge about quantitative, qualitative and mixed research methods in social and behavioral sciences.
4) Recognize historical patterns while evaluating contemporary political and social developments.
5) Demonstrate interdisciplinary and critical approach while analyzing, synthesizing and forecasting domestic and foreign policy.
6) Conduct studies in the field professionally, both independently or as a team member.
7) Possess consciousness about lifelong learning based on Research & Development.
8) Communicate with peers both orally and in writing, by using a foreign language at least at a level of European Language Portfolio B1 General Level and the necessary informatics and communication technologies.
9) Apply field-related knowledge and competences into career advancement, projects for sustainable development goals, and social responsibility initiatives.
10) Possess the habit to monitor domestic and foreign policy agenda as well as international developments.
11) Possess competence to interpret the new political actors, theories and concepts in a global era.
12) Evaluate the legal and ethical implications of advanced technologies on politics.