Information Package / Course Catalogue
The Use of Artificial Intelligence Applications in Agricultural Education
Course Code: ZZO577
Course Type: Area Elective
Couse Group: Second Cycle (Master's Degree)
Education Language: Turkish
Work Placement: N/A
Theory: 3
Prt.: 0
Credit: 3
Lab: 0
ECTS: 8
Objectives of the Course

Enable graduate students to benefit from developed artificial intelligence tools for research, submitting an application, academic writing, and presentation of prepared texts using language models developed throughout their education and rest of their lives.

Course Content

Learning the basics of artificial intelligence and the developed language models, and create requests to obtain correct answers while using suitable language models according to the need. Afterwards, learn how to benefit from artificial intelligence to overcome challenges such as saving time when converting research results into written text and avoiding plagiarism.

Name of Lecturer(s)
Lec. Nezih ATA
Learning Outcomes
1.Understanding the fundamental concepts in Artificial Intelligence and Natural Language Processing
2.Gaining knowledge about NLP models and selecting models based on specific needs
3.Learning about the current approaches of Artificial Intelligence in the agricultural studies
4.Understanding to creating prompts to enhance the effectiveness of utilizing Artificial Intelligence
5.Acquiring knowledge on utilizing Artificial Intelligence for literature review purposes
6.Understanding how to leverage Artificial Intelligence for writing articles in a foreign language in competitive publishing houses
Recommended or Required Reading
1.Kose, U., Prasath, V. S., Mondal, M. R. H., Podder, P., & Bharati, S. (Eds.). (2022). Artificial Intelligence and Smart Agriculture Technology. CRC Press.
2.Tomar, P., & Kaur, G. (Eds.). (2021). Artificial Intelligence and IoT-based Technologies for Sustainable Farming and Smart Agriculture. IGI Global.
3.Churi, P.P., Joshi, S., Elhoseny, M., & Omrane, A. (Eds.). (2022). Artificial Intelligence in Higher Education: A Practical Approach (1st ed.). CRC Press. https://doi.org/10.1201/9781003184157
4.Roommate, F., (Ed.) . (2023). Artificial Intelligence in Higher Education and Scientific Research Future Development. (Part of the book series: Bridging Human and Machine: Future Education with Intelligence, E-ISSN:2662-5350) Springer.
Weekly Detailed Course Contents
Week 1 - Theoretical
Introduction to Artificial Intelligence and Basic Concepts
Week 2 - Theoretical
Natural Language Processing (NLP) and Basic Concepts
Week 3 - Theoretical
Language models developed in NLP (GPT, BERT, T5, XLNET, Transformer-XL, Bard, Electra, XLM, CTRL, ProphetNET...)
Week 4 - Theoretical
Development Process and Comparison of NLP Models
Week 5 - Theoretical
Artificial intelligence approaches on Agriculture
Week 6 - Theoretical
What is a prompt, and general concepts related to prompt creating
Week 7 - Theoretical
Prompt Engineering in NLP
Week 8 - Theoretical
Approaches to Prompt Engineering
Week 9 - Theoretical
Resources for Prompt Generation (Prompt Vibes, OpenAI playgrounds...)
Week 10 - Theoretical
Source Searching and Summarization with AI (SciSpace Copilot, Perplexity...)
Week 11 - Theoretical
Improving Writing Skills with AI (Viola.ai, Notion.so, Quillbot...)
Week 12 - Theoretical
Presentation Preparation and Visual Designs with AI
Week 13 - Theoretical
Yapay zeka ve Prompt Engineering'de Etik
Week 14 - Theoretical
General Review
Assessment Methods and Criteria
Type of AssessmentCountPercent
Midterm Examination1%30
Final Examination1%70
Workload Calculation
ActivitiesCountPreparationTimeTotal Work Load (hours)
Lecture - Theory143384
Assignment57245
Midterm Examination130232
Final Examination140242
TOTAL WORKLOAD (hours)203
Contribution of Learning Outcomes to Programme Outcomes
PÇ-1
PÇ-2
PÇ-3
PÇ-4
PÇ-5
PÇ-6
PÇ-7
OÇ-1
2
4
OÇ-2
1
3
OÇ-3
2
2
3
3
OÇ-4
5
OÇ-5
2
3
1
2
OÇ-6
4
2
3
Adnan Menderes University - Information Package / Course Catalogue
2026