Course Language:
English
Course Coordinator:
Course Objectives:
To be able to convey necessary information about collecting data with methods of agricultural, meteorological, and phenolic etc. and analyzing the data based on these methods in order to make informed decisions, To explain hot information systems can be used to increase agricultural production.
Course Content:
Current studies and research studies using big data analysis to solve various problems in agriculture. Problems addressed, proposed solutions, tools, algorithms and data used, nature and dimensions of big data used, scale of use and overall impact.
Teaching Methods:
1: Lecture, 2: Question-Answer, 3: Discussion, 4: Simulation, 5: Case-study
Assessment Methods:
A: Testing, B: Presentation, C: Homework, D: Project, E: Lab
Vertical Tabs
Course Learning Outcomes
| Course Learning Outcomes |
Program
Learning Outcomes |
Teaching Methods | Assessment Methods |
| Can define the technologies used in data collection for agricultural production. | 5,11 | 1,2,3 | A,B,C,E |
| Can collect necessary data for agricultural data. | 5,11 | 1,2,3 | A,B,C,E |
| Can model the data collected. | 5,11 | 1,2,3 | A,B,C,E |
| Can make decision-supported predictions with data | 5,11 | 1,2,3 | A,B,C,E |
| Can use information technologies to increase agricultural production and reduce inputs | 5,11 | 1,2,3 | A,B,C,E |
| Can report the data obtained and the decisions based on this data | 5,11 | 1,2,3 | A,B,C,E |
Course Flow
| Week | Topics | Study Materials |
| 1 | Introduction to agricultural information systems, big data | Lecture notes |
| 2 | Data collection methods (sensors, soil analysis, satelite tracking etc.) | Lecture notes |
| 3 | Processing data with cloud operations and artificial intelligence algorithms | Lecture notes |
| 4 | Modelling of data | Lecture notes |
| 5 | Modelling of data | Lecture notes |
| 6 | Data-based forecast: Drought, disease, yield etc. predictions | Lecture notes |
| 7 | Data-based forecast: Drought, disease, yield etc. predictions | Lecture notes |
| 8 | Midterm | |
| 9 | Reporting decision-supported forecasts and transforming data into the value chain | Lecture notes |
| 10 | Case study | Lecture notes |
| 11 | Case study | Lecture notes |
| 12 | Case study | Lecture notes |
| 13 | Case study | Lecture notes |
| 14 | Student presentations | Lecture notes |
Recommended Sources
| Lecture Notes | |
| Additional Resources | Various Publications and Lecture Notes |
Material Sharing
| Documents | Lecture Notes |
| Assignments | Homework, Presentation |
| Exams | Midterm, Final |
Assessment
| IN-TERM STUDIES | NUMBER | PERCENTAGE |
| Midterm | 60 | |
| Homework | 20 | |
| Presentation | 20 | |
| Total | 100 | |
| Final to Success | 40 | |
| Semester to Success | 60 | |
| Total | 100 |
Course’s Contribution to Program
| No | Program Learning Outcomes | Contribution | ||||
| 1 | 2 | 3 | 4 | 5 | ||
| 1 | To be able to comprehend the economic problems of agriculture; collecting, analyzing, and interpreting data at micro and macro levels for economic applications; analyzing the ways of increasing production by applying the basic principles of economy in agriculture; to make the right decision for the future; to produce project-based solutions; ability to apply with contemporary techniques. | |||||
| 2 | To be able to monitor national and international agricultural markets, to understand the behavior of market actors; ability to predict the effects of economic and political developments on the Turkish agricultural sector and interpret and make decisions. | |||||
| 3 | Marketing of agricultural products by using marketing principles and methods; have the basic knowledge about market research and ability to interpret. | |||||
| 4 | Agricultural production tools, equipment, methods and equipment to recognize; application of plant and animal production techniques and models; Ability to use the theoretical and practical knowledge related to plant breeding, plant breeding, seed production, genetics, physiology, ecology, biotechnology, plant gene resources, organic agriculture and meadow-pasture management in the field of field crops. |
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| 5 | To develop and deepen their knowledge in the field of information systems at the level of expertise; interpreting and integrating the information acquired in information systems with the information coming from related disciplines; ability to develop new approaches to complex problems in applications in information systems. | X | ||||
| 6 | Ability to possess wide and deep knowledge in the field of Agricultural Trade and Management including the most recent advances; ability to possess advanced level of required skill, techniques and methods to conduct research by using and evaluating up-to-date information; ability to model, design and develop solutions, a system, a process or a product under realistic constraints by generating innovative and original ideas. | |||||
| 7 | Ability to perceive, design and apply an original research process (analytical, modeling or experimental) independently: ability to solve complex problems and critically evaluate the ideas and developments in the field of specialization. Ability to transfer advancements in scientific, technical and cultural developments to the society with the ethical responsibility and scientific objectivity. | |||||
| 8 | Ability to communicate effectively in oral and written English; the ability to write and understand effective reports, to make effective presentations, to give and receive clear and understandable instructions. | X | ||||
| 9 | Ability to work effectively in disciplinary and multidisciplinary teams; self-study skills. | X | ||||
| 10 | To act in accordance with ethical principles, professional and ethical responsibility awareness; the ability to inform the society on issues related to biodiversity, natural resources, air, water, soil pollution, recycling, environmental sensitivity, environmental protection. | |||||
| 11 | Awareness of the necessity of lifelong learning; the ability to access information, follow developments in science and technology, and constantly renew oneself. | X | ||||
ECTS
| Etkinlik | SAYISI |
Süresi (Saat) |
Toplam İş Yükü (Saat) |
| Ders Süresi (Sınav haftası dahildir: 14x toplam ders saati) | 14 | 3 | 42 |
| Sınavlara Çalışma Süresi | 1 | 25 | 25 |
| Ara Sınav | 1 | 2 | 2 |
| Sınıf dışı makale okuma ve ödevler | 14 | 10 | 140 |
| Sunum ve sunuma hazırlık | 1 | 25 | 25 |
| Final | 1 | 3 | 3 |
| Toplam İş Yükü | 237 | ||
| Toplam İş Yükü / 25 (s) | 9,5 | ||
| Dersin AKTS Kredisi | 10 |