Artificial Intelligence and Data Analytics in Mechanical EngineeringSyllabus

Subject code

MM-0706

Credits

6

Student workload

180

Semester

Spring semester

Academic year

2025-2026

Subject type

Mandatory

Form of education

Full-time

Language of instruction

English

In-class hours

Lecture:30 Seminar:15

Out-of-class hours

Independent Study (TSİ):81 MRTSI:54

“Artificial Intelligence and Data Analytics in Mechanical Engineering Production” is an advanced Master’s level course designed to bridge the gap between traditional mechanical engineering and modern intelligent technologies. The primary objective of this discipline is to equip graduate students with the theoretical knowledge and practical skills required to implement data-driven methods, predictive modeling, and artificial intelligence within contemporary manufacturing environments. Throughout the curriculum, students explore advanced methodologies for collecting, processing, and analyzing complex engineering data derived from actual production lines, design cycles, and CAD/CAM/CAE system outputs. Special emphasis is placed on developing intelligent algorithms for the early detection of manufacturing defects, predicting structural or system failures, and optimizing technological performance indicators. To successfully enroll in this course, students are expected to possess foundational knowledge in mechanical engineering principles, strength of materials, automated control systems, and basic statistical analysis. This highly interdisciplinary course is academically interconnected with core engineering fields, ensuring that students can seamlessly apply data analytics to evaluate simulation results and enhance production efficiency. Ultimately, the course fosters a technical mindset focused on data-driven decision-making, enabling future engineers to accurately interpret analytical results and implement smart optimization models in the industrial sector.

• lecture
• seminar
• interactive discussion
• case study
• problem-based learning
• presentations
• teamwork

No learning outcomes have been added.

No topics have been added.

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