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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS LGM 4029 DATA ANALYTICS ELECTIVE 3 0 0 5

Offered By

Logistics Management (English)

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

ASSISTANT PROFESSOR VOLKAN ÇETINKAYA

Offered to

Logistics Management (English)

Course Objective

Giving essential tools of data science and data analytics to enable them for make model and scientifically based decisions production environments.

Learning Outcomes of the Course Unit

1   1. To Develop Data Literacy. 2   2. To Acquire Data Collection and Processing Skills 3   3. To Utilize Data Visualization Techniques 4   4. Make Data-Driven Business Decisions 5   5. To Identify Business Trends and Patterns regarding data 6   6. To Collaborate on Data-Driven Business Projects

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Introduction to Data Science 2 Basic Statistics Concept 3 Data Cleaning and Preparing 4 Basic Data Processes on Excel 5 Data Analysis via Phyton 6 Data Visualization 7 Mid-Term Exam 8 Data Analytics Applications in Business 9 Exploratory Data Analysis (EDA) 10 Introduction to machine learning Unsupervised and supervised learning 11 Regression 12 Classification models 13 Clustering Analysis 14 Time Series 15 Final Exam

Recomended or Required Reading

To be announced.

Planned Learning Activities and Teaching Methods

Literature review, case studies, problem solving, applications

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MD Midterm 2 HW Homework 3 FIN FINAL EXAM 4 FCG FINAL COURSE GRADE MD * 0.30 + HW * 0.20 + FN * 0.50 5 RST RESIT 6 FCGR FINAL COURSE GRADE (RESIT) MD * 0.30 + HW * 0.20 + BUT * 0.50

Further Notes About Assessment Methods

None

Assessment Criteria

Oral and written competencies regarding the use of knowledge, abilities and skills in the field of Data Science in terms of research, investigation and evaluation will be evaluated.

Language of Instruction

English

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

To be announced.

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours) Lectures 14 3 42 Preparations before/after weekly lectures 13 1 13 Preparation for midterm exam 1 15 15 Preparation for final exam 1 20 20 Preparing assignments 1 30 30 Midterm 1 1 1 Final 1 1 1 TOTAL WORKLOAD (hours) 122

Contribution of Learning Outcomes to Programme Outcomes

PO/LO PO.1 PO.2 PO.3 PO.4 PO.5 PO.6 PO.7 PO.8 PO.9 PO.10 PO.11 PO.12 PO.13 LO.1 5 5 5 5 5 5 5 5 LO.2 5 5 5 5 5 5 5 5 LO.3 5 5 5 5 5 5 5 5 LO.4 5 5 5 5 5 5 5 5 LO.5 5 5 5 5 5 5 5 5 LO.6 5 5 5 5 5 5 5 5