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Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS BLP 4125 DIGITAL TECHNOLOGIES COMPULSORY 2 1 0 4

Offered By

Computer Programming

Level of Course Unit

Short Cycle Programmes (Associate's Degree)

Course Coordinator

MURAT GÜNEY

Offered to

Computer Programming Computer Programming (Evening)

Course Objective

With this course, the student: To raise awareness about the practical equivalents of competencies in digital transformation processes in production and service processes.

Learning Outcomes of the Course Unit

1   Industrial algorithm and design awareness is created. 2   ERP, MES, ioT, Artificial intelligence etc. processes can be interpreted 3   The infrastructure required for data analysis is provided 4   The perception of efficiency and competence is digitalized. 5   Infrastructure needs analysis can be made for Industry 4.0. 6   Digital maturity levels of businesses can be measured. 7   The integration of Big Data and Artificial Intelligence (AI) can become meaningful and industrial algorithms can be developed.

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description 1 Digital technologies 2 Digital Ecosystems and Platforms 3 Industrial Algorithm and Technology Integrations 4 Digitalization in Lean Production 5 Enterprise Resource Planning (MRP-1, MRP-2) 6 Enterprise Resource Planning (ERP) 7 Application Development for Course Topics 8 Midterm 9 Internet of Things (IoT) 10 Big Data and Artificial Intelligence 11 Augmented Reality (AR) and Virtual Reality (VR) 12 Robotic Process Automations 13 Sample Business Practices 14 Case Studies 15 Application Development for Course Topics 16 Final Exam

Recomended or Required Reading

Textbook(s): Dijital Dönüşüm / Akıllı Fabrikalar -Prof. Dr. Lutfi Apiliogullari Supplementary Book(s): Current articles and Digitalization documents References: Materials:

Planned Learning Activities and Teaching Methods

1. Lectures 2. Case Study

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA 1 MTE MIDTERM EXAM 2 FN Final 3 FCG FINAL COURSE GRADE VZ*0.40 + FN* 0.60 4 RST RESIT 5 FCGR FINAL COURSE GRADE (RESIT) VZ*0.40 + BUT* 0.60

Further Notes About Assessment Methods

None

Assessment Criteria

Mid-term exam and final exam to measure learning outcomes, and in-class applications with the seven outcomes that will be followed in reaching the stage of the student.

Language of Instruction

Turkish

Course Policies and Rules

70% of the classes is compulsory to attend. Disciplinary investigation will be concluded with the opening of any act of dishonesty.

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 2 28 Tutorials 14 1 14 Preparations before/after weekly lectures 14 3 42 Preparation for midterm exam 1 10 10 Preparation for final exam 1 16 16 Final 1 1 1 Midterm 1 1 1 TOTAL WORKLOAD (hours) 112

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 PO.14 PO.15 LO.1 4 5 3 4 3 2 LO.2 4 5 3 4 3 2 LO.3 4 5 3 4 3 2 LO.4 4 5 3 4 3 2 LO.5 4 5 3 4 3 2 LO.6 3 5 3 4 3 2 LO.7 3 5 3 4 3 2