PAÜ .:. Eğitim Öğretim Bilgi Sistemi

COURSE INFORMATION

Course Code	Course Title	L+P Hour	Semester	ECTS
CENG 546	DATA ANALYSIS IN INTERNET OF THINGS	3 + 0	1st Semester	7,5

COURSE DESCRIPTION

Course Level	Master's Degree
Course Type	Elective
Course Objective	The aim of this course is to understand the characteristics of big data that generated in the Internet of Things (IoT), to define the problems that arise in data analysis, to investigate cloud, fog and edge computing approaches to solve the defined problems, and to develop machine learning algorithms for solving existing problems.
Course Content	Internet of Things (IoT) overview, IoT devices and communication protocols, IoT data and characteristics, IoT data analytics and challenges, IoT data analysis approaches / algorithms, IoT data analytics on the cloud, IoT data analysis on edge / fog, Future direction and open research problems in data analysis
Prerequisites	No the prerequisite of lesson.
Corequisite	No the corequisite of lesson.
Mode of Delivery	Face to Face

COURSE LEARNING OUTCOMES

1	Define IoT concepts
2	Explain IoT architecture and components
3	Explain the characteristics of IoT data
4	Analyze IoT data analysis challenges
5	Offer solutions to IoT data analysis challenges
6	Develop models / algorithms to solve IoT data analysis challenges

COURSE'S CONTRIBUTION TO PROGRAM

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION

Activities	Quantity	Duration (Hour)	Total Work Load (Hour)
Course Duration (14 weeks/theoric+practical)	14	3	42
Hours for off-the-classroom study (Pre-study, practice)	14	5	70
Assignments	5	8	40
Mid-terms	1	15	15
Final examination	1	28	28
Total Work Load ECTS Credit of the Course			195 7,5

COURSE DETAILS

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L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes

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