COMPUTER ENGINEERING
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

1410002024

Ders İsmi:

Cloud Computing and Big Data Analytics

Ders Yarıyılı:

Spring

Ders Kredileri:

Theoretical	Practical	Credit	ECTS
3	0	3	5

Language of instruction:

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Type of course:

Bölüm Seçmeli

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 Recep DURANAY

Course Lecturer(s):

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	The aim of this course will be to teach students cloud programming models and cloud programming tools for applications used in data-intensive sciences. Students will learn about the latest technologies related to cloud computing platforms.
Course Content:	In the course, topics such as new programming paradigms, virtualization environments, big scientific data analysis within the scope of cloud programming will be covered. In addition, many research articles in the field of cloud computing will be learned, presented and discussed.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
1) It will gain knowledge and skills to learn and apply the basic concepts of Cloud Computing and Big Data.
2) It will gain the ability to find and extract information from Big Data stacks in the Cloud Computing environment.
2 - Skills
Cognitive - Practical
3 - Competences
Communication and Social Competence
1) It will gain the ability to extract and analyze information from large data stacks on the Cloud Computing platform.
Learning Competence
1) Skills related to Cloud Computing platforms will be gained.
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	Introduction to Course	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
2)	Distributed System Models and Enabling Technologies	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
3)	Computer Clusters for Scalable Computing	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
4)	Virtual Machines and Virtualization of Clusters and Datacenters	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
5)	Cloud Platform Architecture over Virtualized Data Centers: Data Center Design and Networking	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
6)	Cloud Platform Architecture over Virtualized Data Centers: Cloud Computing Service Models	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
7)	Cloud Platform Architecture over Virtualized Data Centers: Major Cloud Service Providers	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
8)	Midterm
9)	Big Data Computing Platforms - I	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
10)	Big Data Computing Platforms - II	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
11)	Cloud Computing Platforms - I	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
12)	Cloud Computing Platforms - II	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
13)	Grid Computing and Resource Management	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
14)	Project presentation
15)	Final

Sources

Course Notes / Textbooks:	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.
References:	Distributed and Cloud Computing: From Parallel Processing to The Internet of Things, K. Hwang, G. Fox and J. Dongarra, Morgan Kaufmann Publishers, 2012.

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	3	4
Program Outcomes
1) PO 1.1) Sufficient knowledge in mathematics, science and computer engineering
2) PO 1.2) Ability to apply theoretical and applied knowledge in mathematics, science and computer engineering for modeling and solving engineering problems.
3) PO 2.1) Identifying complex engineering problems
4) PO 2.2) Defining complex engineering problems
5) PO 2.3) Formulating complex engineering problems
6) PO 2.4) Ability to solve complex engineering problems
7) PO 2.5) Ability to choose and apply appropriate analysis and modeling methods
8) PO 3.1) Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions.
9) PO 3.2) Ability to apply modern design methods under realistic constraints and conditions for a complex system, process, device or product
10) PO 4.1) Developing modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications
11) PO 4.2) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications
12) PO 4.3) Ability to use information technologies effectively.
13) PO 5.1) Examination of complex engineering problems or discipline-specific research topics, designing experiments
14) PO 5.2) Examination of complex engineering problems or discipline-specific research topics, experimentation
15) PO 5.3 ) Analysis of complex engineering problems or discipline-specific research topics, data collection
16) PO 5.4) Analyzing the results of complex engineering problems or discipline-specific research topics
17) PO 5.5) Examining and interpreting complex engineering problems or discipline-specific research topics

Ders - Öğrenme Kazanımı İlişkisi

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

	Program Outcomes	Level of Contribution
1)	PO 1.1) Sufficient knowledge in mathematics, science and computer engineering
2)	PO 1.2) Ability to apply theoretical and applied knowledge in mathematics, science and computer engineering for modeling and solving engineering problems.
3)	PO 2.1) Identifying complex engineering problems
4)	PO 2.2) Defining complex engineering problems
5)	PO 2.3) Formulating complex engineering problems
6)	PO 2.4) Ability to solve complex engineering problems
7)	PO 2.5) Ability to choose and apply appropriate analysis and modeling methods
8)	PO 3.1) Ability to design a complex system, process, device or product to meet specific requirements under realistic constraints and conditions.
9)	PO 3.2) Ability to apply modern design methods under realistic constraints and conditions for a complex system, process, device or product
10)	PO 4.1) Developing modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications	5
11)	PO 4.2) Ability to select and use modern techniques and tools necessary for the analysis and solution of complex problems encountered in engineering applications
12)	PO 4.3) Ability to use information technologies effectively.
13)	PO 5.1) Examination of complex engineering problems or discipline-specific research topics, designing experiments
14)	PO 5.2) Examination of complex engineering problems or discipline-specific research topics, experimentation
15)	PO 5.3 ) Analysis of complex engineering problems or discipline-specific research topics, data collection
16)	PO 5.4) Analyzing the results of complex engineering problems or discipline-specific research topics
17)	PO 5.5) Examining and interpreting complex engineering problems or discipline-specific research topics

Öğrenme Etkinliği ve Öğretme Yöntemleri

Ölçme ve Değerlendirme Yöntemleri ve Kriterleri

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Project	1	% 20
Midterms	1	% 40
Semester Final Exam	1	% 40
total		% 100
PERCENTAGE OF SEMESTER WORK		% 60
PERCENTAGE OF FINAL WORK		% 40
total		% 100

İş Yükü ve AKTS Kredisi Hesaplaması

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	13	3	39
Study Hours Out of Class	13	4	52
Project	1	20	20
Midterms	1	8	8
Final	1	10	10
Total Workload			129