Information Package / Course Catalogue
| Course Code | : ST308 |
| Course Type | : Required |
| Couse Group | : First Cycle (Bachelor's Degree) |
| Education Language | : Turkish |
| Work Placement | : N/A |
| Theory | : 2 |
| Prt. | : 1 |
| Credit | : 3 |
| Lab | : 0 |
| ECTS | : 4 |
The aim of this course is to provide students with the knowledge and skills required to apply artificial intelligence technologies in quality control systems. Students will learn AI applications for monitoring, analysing, and predicting quality parameters in dairy and food processing, while gaining experience in intelligent manufacturing systems, data analytics, and decision-support technologies.
This course introduces the principles of quality control together with the fundamentals of artificial intelligence, machine learning, deep learning, computer vision, sensor technologies, image processing, and big data analytics. AI applications in microbiological quality control, physicochemical analyses, process optimization, defect detection, quality prediction, and intelligent manufacturing systems are discussed using examples from dairy and food processing.
| 1. | 1. able to use the quality control analyses for starter cultures and solve the resultant problems |
| 2. | 2. Students should be able to; employ the methods for controlling the microbiological quality of dairy products and evaluate the results |
| 3. | 3. able to remark about the microbiological properties of dairy products and classify according to microbiological quality |
| 4. | 4. able to apply the hygiene control methods for equipment, water, package and personnel |
| 5. | 5. able to carry out the CIP system calculations |
| 1. | Zhang, Y., & Zhang, M. (2021). Artificial Intelligence in Food Industry. Springer. |
| 2. | Pathania, A., & Kumar, V. (2024). Artificial Intelligence Applications in Food Processing and Quality Control. CRC Press. |
| Type of Assessment | Count | Percent |
|---|---|---|
| Attending Lectures | 1 | %5 |
| Quiz | 1 | %5 |
| Midterm Examination | 1 | %30 |
| Final Examination | 1 | %60 |
| Activities | Count | Preparation | Time | Total Work Load (hours) |
|---|---|---|---|---|
| Lecture - Theory | 14 | 1 | 2 | 42 |
| Lecture - Practice | 14 | 2 | 1 | 42 |
| Quiz | 1 | 2 | 2 | 4 |
| Midterm Examination | 1 | 4 | 2 | 6 |
| Final Examination | 1 | 6 | 2 | 8 |
| TOTAL WORKLOAD (hours) | 102 | |||
PÇ-1 | PÇ-2 | PÇ-3 | PÇ-4 | PÇ-5 | PÇ-6 | PÇ-7 | PÇ-8 | PÇ-9 | PÇ-10 | PÇ-11 | |
OÇ-1 | 4 | 5 | 5 | 5 | 4 | ||||||
OÇ-2 | 4 | 5 | 5 | 5 | 4 | ||||||
OÇ-3 | 4 | 5 | 5 | 5 | 4 | ||||||
OÇ-4 | 4 | 5 | 5 | 5 | 4 | ||||||
OÇ-5 | 4 | 5 | 5 | 5 | 4 | ||||||