MECHATRONICS (TURKISH)
Associate	TR-NQF-HE: Level 5	QF-EHEA: Short Cycle	EQF-LLL: Level 5

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:	Associate (Short 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 improve fundamental computer knowledge, to encourage students using office and package programs.
2)	Ability to have and use of fundamental mathematics knowledge and skills the usage of relevant materials.
3)	Ability to recognize general structures of machine equipments and the features of shaping
4)	Ability to grasp manufacturing processes and cutting tool materials, materials, statics, mechanics and fluid science fundemantal knowledge.
5)	Ability to draw assembly and auxilary devices as well as to draw whole or details of a system.
6)	Ability to have a knowledge of fundemantal manufacturing process such as turning, milling, punching,grinding and welding techniques and to have a self esteem in order to work behind the bench.
7)	Ability to do computer aided design and write program on digital benches.
8)	Ability to prepare project report, follow up project process and implement projects.
9)	ability to learn the areas of usage of electronic circuit components. Ability to grasp and write programs for micro controllers and for their components. Ability to design relevant circuits.
10)	Ability to understand the electric motors principles and AC-DC analysis
11)	Ability to gain a dominaion on visual programming
12)	Having the ability to communicate efficiently in verbal and written Turkish, to know at least one foreign language in order to communicate with the colleagues and customers.