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DATA ANALYTICS II PROGRAMME COURSE DESCRIPTION

Code Name of the Course Unit Semester In-Class Hours (T+P) Credit ECTS Credit
YBS316 DATA ANALYTICS II 6 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
Course Prerequisite No

OBJECTIVES AND CONTENTS

Objectives of the Course Unit: This course aims to enable students to develop basic algorithms in order to solve different types of problems and to teach the basic structures of programming and programming in a computerized environment; thus, it aims to make students think like a data scientist.
Contents of the Course Unit: The content of the course is the concepts of algorithms and programming, variables, data types, input and output statements, arrays, lists, dictionaries, functions, file operations and the use of Python as a data analytics tool.

KEY LEARNING OUTCOMES OF THE COURSE UNIT (On successful completion of this course unit, students/learners will or will be able to)

Develop algorithm for solving problems encountered in daily life. {develop}
Evaluate the functions of the Python programming language.{evaluate}
Design algorithms with Python programming language. {design}
Test the usability of algorithms.{testing}
Apply machine learning design to create solutions that meet the needs identified taking into account global, cultural, social, environmental and economic factors, as well as public health, safety and well-being.{Application}

WEEKLY COURSE CONTENTS AND STUDY MATERIALS FOR PRELIMINARY & FURTHER STUDY

Week Preparatory Topics(Subjects) Method
1 - Data, Information, Knowledge Concepts Lecture & Studying on Sample & Practice
2 Studying on Sample, Assignment Explaining R infrastructure and its installation Lecture & Studying on Sample & Practice
3 Studying on Sample, Assignment Loop structure and its functions Lecture & Studying on Sample & Practice
4 Studying on Sample, Assignment Data types (structural, non-structural nominal, ordinal data) Lecture & Studying on Sample & Practice
5 Studying on Sample, Assignment Basic statistical calculation and visualisation Lecture & Studying on Sample & Practice
6 Studying on Sample, Assignment Data pre-processing process Lecture & Studying on Sample & Practice
7 Studying on Sample, Assignment Principal Component Analysis Lecture & Studying on Sample & Practice
8 - MID-TERM EXAM -
9 Studying on Sample, Assignment Regression analysis Lecture & Studying on Sample & Practice
10 Studying on Sample, Assignment Hypothesis tests Lecture & Studying on Sample & Practice
11 Studying on Sample, Assignment Decision trees Lecture & Studying on Sample & Practice
12 Studying on Sample, Assignment Choosing Model and its methods Lecture & Studying on Sample & Practice
13 Studying on Sample, Assignment Logistic Regression Lecture & Studying on Sample & Practice
14 Studying on Sample, Assignment Practice Studying on Sample & Practice
15 Studying on Sample, Assignment Practice Studying on Sample & Practice
16 - FINAL EXAM -
17 - FINAL EXAM -

SOURCE MATERIALS & RECOMMENDED READING

Gursakal, N. (2014). Istatistikte R ile Programlama.
Arslan, I. (2015). R ile Istatistiksel Programlama. Pusula Publications, Istanbul.

ASSESSMENT

Assessment & Grading of In-Term Activities Number of Activities Degree of Contribution (%) Description
Level of Contribution
0 1 2 3 4 5

CONTRIBUTION OF THE COURSE UNIT TO THE PROGRAMME LEARNING OUTCOMES

KNOWLEDGE

Theoretical

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Define concepts such as management, manager and leader.
4
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.
5

SKILLS

Practical

Programme Learning Outcomes Level of Contribution
0 1 2 3 4 5
1
Manage projects as part of a team.
5
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.
4
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
3
3
Share the analyzes and obtained results with colleagues.
3
4
Cooperate with colleagues at international level with the help of foreign language competency.
4

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.
4
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.
3

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 7 4 28
Laboratory 0 0 0
Reading 0 0 0
Assignment (Homework) 0 0 0
Project Work 0 0 0
Seminar 0 0 0
Internship 0 0 0
Technical Visit 0 0 0
Web Based Learning 0 0 0
Implementation/Application/Practice 14 2 28
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 0 0 0
Final Exam 1 1 1
Preparation for the Final Exam 7 5 35
Mid-Term Exam 1 1 1
Preparation for the Mid-Term Exam 7 4 28
Short Exam 0 0 0
Preparation for the Short Exam 0 0 0
TOTAL 64 0 202
Total Workload of the Course Unit 202
Workload (h) / 25.5 7,9
ECTS Credits allocated for the Course Unit 8,0