DATA ANALYTICS I PROGRAMME COURSE DESCRIPTION

Code	Name of the Course Unit	Semester	In-Class Hours (T+P)	Credit	ECTS Credit
YBS317	DATA ANALYTICS I	5	3	3	8

GENERAL INFORMATION
Language of Instruction :	Turkish
Level of the Course Unit :	BACHELOR'S DEGREE, TYY: + 6.Level, EQF-LLL: 6.Level, QF-EHEA: First Cycle
Type of the Course :	Compulsory
Mode of Delivery of the Course Unit	-
Coordinator of the Course Unit	Assist.Prof. DİDEM TETİK KÜÇÜKELÇİ
Instructor(s) of the Course Unit	Assist.Prof. SÜREYYA İMRE BIYIKLI
Course Prerequisite	No

OBJECTIVES AND CONTENTS
Objectives of the Course Unit:	The aim of this course is to prepare students to collect, define and analyze data and to use advanced statistical tools to make decisions about the field of business. In the scope of the course, data mining algorithms based mainly on prediction will be included and business applications will be made with R language. It is aimed to provide students with problem solving and project development habits with a systematic approach.
Contents of the Course Unit:	Contents of the course include the subjects such as algorithms and programming concepts, variables, data types, input and output statements, series, lists, dictionaries, functions, file processing.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)
Use different file formats for data input and output. {use}
Analyze statistical analyses in R, which is an open source platform. {analysis}
Evaluate the accuracy of the analysed data.{evaluate}
Develop his/her own analysis technique himself/herself.{develop}
Assess data extraction and data reduction techniques.{assess}

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY
Week	Preparatory	Topics(Subjects)	Method
1	-	Course Information (Syllabus) and Introduction to Data Analytics and R Programming	Lecture & Discussion & Practice
2	Literature Review, Assignment	Basic Data Structures in R	Lecture & Discussion & Practice
3	Literature Review, Assignment	Control Statements and Loops in R	Lecture & Discussion & Practice
4	Literature Review, Assignment	Functions in R	Lecture & Discussion & Practice
5	Literature Review, Assignment	Data Visualization with R	Lecture & Discussion & Practice
6	Literature Review, Assignment	Data Preprocessing with R	Lecture & Discussion & Practice
7	Literature Review, Assignment	Simple and Multiple Regression Models	Lecture & Discussion & Practice
8	Literature Review, Assignment	K-Means Clustering Algorithm	Lecture & Discussion & Practice
9	Literature Review, Assignment	K-Nearest Neighbors (KNN) Algorithm	Lecture & Discussion & Practice
10	-	MID-TERM EXAM	-
11	Literature Review, Assignment	Decision Trees: Regression and Classification	Lecture & Discussion & Practice
12	Literature Review, Assignment	Random Forests: Regression and Classification	Lecture & Discussion & Practice
13	Literature Review, Assignment	Q&A Session on Final Projects	Lecture & Discussion & Practice
14	Literature Review, Assignment	Q&A Session on Final Projects	Lecture & Discussion & Practice
15	FINAL	FINAL	Lecture & Discussion & Practice
16	-	FINAL EXAM	-
17	-	FINAL EXAM	-

SOURCE MATERIALS & RECOMMENDED READING
Karacay, T. (2016). Python 3: Veri Yapilari. Seckin Publications.
Aksoy, A. (2016). Yeni Baslayanlar Icin Python. Abakus Publications.

ASSESSMENT
Assessment & Grading of In-Term Activities	Number of Activities	Degree of Contribution (%)	Description	Examination Method
Mid-Term Exam	1	50		Classical Exam
Final Exam	1	50		Project Submission (No Examination)
TOTAL	2	100

Level of Contribution
0	1	2	3	4	5

KNOWLEDGE
Theoretical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Define concepts such as management, manager and leader.						5
2	Analyze the accuracy, reliability and validity of the new information obtained from the data.						5

KNOWLEDGE
Factual
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Report the obtained data.						5
2	Prepare software and projects related with the field.						5

SKILLS
Cognitive
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Use the appropriate resources for data analysis related with the field.						5
2	Analyze the work processes.					4

SKILLS
Practical
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Manage projects as part of a team.					4
2	Apply the material, techniques and analyzes in relation with the subject for project and work flows.						5

OCCUPATIONAL
Autonomy & Responsibility
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Fulfill responsibility with a focus on result in individual and team studies.						5

OCCUPATIONAL
Learning to Learn
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Recognizes what he/she knows about his/her field or not.						5
2	Act the theoretical knowledge in real life with learning to learn approach.						5
3	Apply different methods and techniques with an innovative approach in his/her research.						5

OCCUPATIONAL
Communication & Social
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Apply the results obtained in accordance with voluntarism and social responsibility projects.						5
2	Establish a healthy contact with colleagues					4
3	Share the analyzes and obtained results with colleagues.					4
4	Cooperate with colleagues at international level with the help of foreign language competency.				3

OCCUPATIONAL
Occupational and/or Vocational
	Programme Learning Outcomes	Level of Contribution
		0	1	2	3	4	5
1	Behave in accordance with ethical values regarding the collection, analysis and reporting of data.						5
2	Participate the design of work processes and systems with full quality.						5
3	Cooperate with other employees for the continuation of sustainability in the profession.					4

WORKLOAD & ECTS CREDITS OF THE COURSE UNIT
Workload for Learning & Teaching Activities
Type of the Learning Activites	Learning Activities (# of week)	Duration (hours, h)	Workload (h)
Lecture & In-Class Activities	14	3	42
Preliminary & Further Study	13	3	39
Land Surveying	0	0	0
Group Work	13	2	26
Laboratory	0	0	0
Reading	14	1	14
Assignment (Homework)	13	2	26
Project Work	1	23	23
Seminar	0	0	0
Internship	0	0	0
Technical Visit	0	0	0
Web Based Learning	0	0	0
Implementation/Application/Practice	0	0	0
Practice at a workplace	0	0	0
Occupational Activity	0	0	0
Social Activity	0	0	0
Thesis Work	0	0	0
Field Study	0	0	0
Report Writing	1	10	10
Final Exam	1	1	1
Preparation for the Final Exam	1	14	14
Mid-Term Exam	1	1	1
Preparation for the Mid-Term Exam	1	7	7
Short Exam	0	0	0
Preparation for the Short Exam	0	0	0
TOTAL	73	0	203