Computer Engineering (English)
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

General Introduction Information of the Course

Course Code:

COMP4055

Course Title:

Big Data Analytics

Course Semester:

Spring

Ders Kredileri:

Theoretical	Practical	Credit	ECTS
3	0	3	6

Language of instruction:

Course Prerequisites:

Does the Course Require Work Experience?:

Type of course:

Departmental Elective

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Dr.Öğr.Üyesi Osman SELVİ

Course Lecturer(s):

Course Assistants:

Course Objectives and Content

Course Objectives:	Become a contributor on a data science team Deploy a structured lifecycle approach to data analytics problems Apply appropriate analytic techniques and tools to analyzing big data
Course Content:	the course focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) Knows Concurrent, Coupled, and Correlated Processes
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Course Weekly Plan

Week	Subject	Related Preparation
1)	Introduction to Big Data Analytics
2)	Big Data Overview
3)	State of the Practice in Analytics
4)	Key Roles for the New Big Data Ecosystem
5)	Examples of Big Data Analytics
6)	Data Analytics Lifecycle
7)	Phase 1: Discovery
8)	Midterm
9)	Phase 2: Data Preparation
10)	Phase 3: Model Planning
11)	Phase 4: Model Building
12)	Phase 5: Communicate Results
13)	Phase 6: Operationalize
14)	Data Analytics Lifecycle
15)	Application
16)	Final Exam

Sources

Course Notes / Textbooks:	Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing and Presenting Data by EMC Education Services
References:	sunumlar, ders notları vs. presentations, notes etc.

Relationship Between Course and Program Learning Outcomes

Course Learning Outcomes	1
Program Outcomes
1) Engineering Knowledge: Has basic knowledge and skills specific to mathematics, science and computer engineering; uses this knowledge effectively in solving complex engineering problems and contributes to innovation processes by developing innovative solutions.
2) Problem Analysis: Define, analyze and solve complex computer engineering problems using knowledge of basic science, mathematics and engineering. In this process, they design energy-efficient systems and efficient algorithms while developing innovative and sustainable computing solutions. Build reliable, scalable and resilient digital infrastructures while considering social and economic impacts such as data security, ethical use of artificial intelligence and digital accessibility. Apply these principles effectively by selecting appropriate modeling and analysis methods.
3) Engineering Design: Design a system, process, device or product in line with real-world constraints and requirements; develop innovative solutions, apply modern engineering methods and contribute to innovation processes.
4) Use of Techniques and Tools: To be able to select and use modern techniques, information technologies and engineering tools effectively to solve problems encountered in engineering practice.
5) Research and Investigation: Understanding scientific research methods and experimental designs, designing and conducting experiments, collecting data, analyzing results and making interpretations based on scientific foundations.
6) Global Impact of Engineering Applications: Assesses the impact of computer engineering solutions on health, safety, economics, sustainability and the environment. Demonstrate in-depth knowledge to contribute to global development goals, with a focus on developing energy efficient systems, sustainable digital infrastructures and environmentally friendly software. Consider the societal impacts of engineering applications in areas such as artificial intelligence, big data and digital security and develop an awareness of ethical responsibilities.
7) Ethical Behavior: Acts in accordance with the ethical principles of the engineering profession and makes and implements decisions with a sense of professional responsibility towards society, the environment and humanity.
8) Individual and Team Work: Work individually and in disciplinary or multidisciplinary teams, with team members from different cultures and languages, competently in written, oral and visual communication in both Turkish and English; successfully manage projects as a team member or leader in remote, face-to-face or blended models.
9) Communication Skills: To be able to communicate effectively orally, in writing and visually on technical issues, taking into account the educational, linguistic and professional differences of the target audience.
10) Project Management and Business Life Applications: Good command of business processes such as project management, risk analysis, economic feasibility analysis and change management; awareness of entrepreneurship, innovation and sustainability.
11) Lifelong Learning: Understands the importance of independent and continuous learning; follows scientific and technological developments by using ways of accessing information and constantly renews itself.

Relationship Between Course and Learning Outcome

No Effect	1 Lowest	2 Low	3 Medium	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Engineering Knowledge: Has basic knowledge and skills specific to mathematics, science and computer engineering; uses this knowledge effectively in solving complex engineering problems and contributes to innovation processes by developing innovative solutions.
2)	Problem Analysis: Define, analyze and solve complex computer engineering problems using knowledge of basic science, mathematics and engineering. In this process, they design energy-efficient systems and efficient algorithms while developing innovative and sustainable computing solutions. Build reliable, scalable and resilient digital infrastructures while considering social and economic impacts such as data security, ethical use of artificial intelligence and digital accessibility. Apply these principles effectively by selecting appropriate modeling and analysis methods.
3)	Engineering Design: Design a system, process, device or product in line with real-world constraints and requirements; develop innovative solutions, apply modern engineering methods and contribute to innovation processes.
4)	Use of Techniques and Tools: To be able to select and use modern techniques, information technologies and engineering tools effectively to solve problems encountered in engineering practice.
5)	Research and Investigation: Understanding scientific research methods and experimental designs, designing and conducting experiments, collecting data, analyzing results and making interpretations based on scientific foundations.
6)	Global Impact of Engineering Applications: Assesses the impact of computer engineering solutions on health, safety, economics, sustainability and the environment. Demonstrate in-depth knowledge to contribute to global development goals, with a focus on developing energy efficient systems, sustainable digital infrastructures and environmentally friendly software. Consider the societal impacts of engineering applications in areas such as artificial intelligence, big data and digital security and develop an awareness of ethical responsibilities.
7)	Ethical Behavior: Acts in accordance with the ethical principles of the engineering profession and makes and implements decisions with a sense of professional responsibility towards society, the environment and humanity.
8)	Individual and Team Work: Work individually and in disciplinary or multidisciplinary teams, with team members from different cultures and languages, competently in written, oral and visual communication in both Turkish and English; successfully manage projects as a team member or leader in remote, face-to-face or blended models.
9)	Communication Skills: To be able to communicate effectively orally, in writing and visually on technical issues, taking into account the educational, linguistic and professional differences of the target audience.
10)	Project Management and Business Life Applications: Good command of business processes such as project management, risk analysis, economic feasibility analysis and change management; awareness of entrepreneurship, innovation and sustainability.
11)	Lifelong Learning: Understands the importance of independent and continuous learning; follows scientific and technological developments by using ways of accessing information and constantly renews itself.

Learning Activities and Teaching Methods

Individual study and homework
Course
Reading

Assessment and Evaluation Methods and Criteria

Written Exam (open-ended questions, multiple-choice, true/false, matching, fill-in-the-blanks, ordering)
Sözlü sınav
Homework

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Quizzes	4	% 10
Homework Assignments	4	% 10
Project	1	% 20
Midterms	1	% 20
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
Total		% 100

Workload and ECTS Credit Calculation

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	2	28
Application	14	2	28
Study Hours Out of Class	14	1	14
Project	1	25	25
Homework Assignments	4	3	12
Quizzes	4	3	12
Midterms	1	10	10
Final	1	25	25
Total Workload			154