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Fundamentals of Artificial Intelligence and Application in Practice
Study Course Description
Course Description Statuss:Approved
Course Description Version:3.00
Study Course Accepted:26.03.2024 13:22:22
| Study Course Information | |||||||||
| Course Code: | SZF_036 | LQF level: | All Levels | ||||||
| Credit Points: | 2.00 | ECTS: | 3.00 | ||||||
| Branch of Science: | Computer sciences and informatics; Other computer sciences | Target Audience: | Public Health; Business Management; Midwifery; Civil and Military Defense; Social Welfare and Social Work; Social Anthropology; Biology; Information and Communication Science; Communication Science; Pharmacy; Life Science; Nursing Science; Health Management; Marketing and Advertising; Pedagogy; Dentistry; Psychology; Political Science; Juridical Science; Sports Trainer; Medical Services; Medical Technologies; Sociology; Medicine; Person and Property Defence; Rehabilitation; Law; Clinical Pharmacy; Management Science | ||||||
| Study Course Supervisor | |||||||||
| Course Supervisor: | Agate Ambulte | ||||||||
| Study Course Implementer | |||||||||
| Structural Unit: | Faculty of Social Sciences | ||||||||
| The Head of Structural Unit: | |||||||||
| Contacts: | Dzirciema street 16, Rīga, szf rsu[pnkts]lv | ||||||||
| Study Course Planning | |||||||||
| Full-Time - Semester No.1 | |||||||||
| Lectures (count) | 7 | Lecture Length (academic hours) | 2 | Total Contact Hours of Lectures | 14 | ||||
| Classes (count) | 8 | Class Length (academic hours) | 2 | Total Contact Hours of Classes | 16 | ||||
| Total Contact Hours | 30 | ||||||||
| Part-Time - Semester No.1 | |||||||||
| Lectures (count) | 7 | Lecture Length (academic hours) | 2 | Total Contact Hours of Lectures | 14 | ||||
| Classes (count) | 8 | Class Length (academic hours) | 2 | Total Contact Hours of Classes | 16 | ||||
| Total Contact Hours | 30 | ||||||||
| Study course description | |||||||||
| Preliminary Knowledge: | Computer skills; basic knowledge of English. | ||||||||
| Objective: | The study course is designed to inform about artificial intelligence technologies and to promote the practical application of artificial intelligence technologies in learning, medicine and improving personal and professional productivity. During the course, it is planned to learn practical skills and gain an insight into artificial intelligence technologies, with the aim of implementing them in speeding up various processes and improving quality. Students will gain practical knowledge of artificial intelligence tools that generate text and images. | ||||||||
| Topic Layout (Full-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | Introduction. Types and Tools of Artificial Intelligence | Lectures | 1.00 | auditorium | |||||
| 2 | Introduction. Restrictions, Copyright, Ethics and Threats | Lectures | 1.00 | auditorium | |||||
| 3 | Practical Seminar on Creating Prompts I – Basic Level; Introduction to ChatGPT | Classes | 1.00 | computer room | |||||
| 4 | Practical Seminar on Creating Prompts II – Prompt Optimisation and Applications in Different Situations | Classes | 1.00 | computer room | |||||
| 5 | Practical Seminar on Prompt Engineering I | Classes | 1.00 | computer room | |||||
| 6 | Practical Seminar on Prompt Engineering II | Classes | 1.00 | computer room | |||||
| 7 | Practical Seminar on Prompt Engineering III | Classes | 1.00 | computer room | |||||
| 8 | Artificial Intelligence Tools for Text Generation I – Their Capabilities, Limitations and Differences | Lectures | 1.00 | computer room | |||||
| 9 | Artificial Intelligence Tools for Text Generation II – Their Capabilities, Limitations and Differences | Lectures | 1.00 | auditorium | |||||
| 10 | Artificial Intelligence and Image Generation I (Image Generation Platforms) | Classes | 1.00 | computer room | |||||
| 11 | Artificial Intelligence and Image Generation II (Image Generation Servers) | Classes | 1.00 | computer room | |||||
| 12 | Generative Artificial Intelligence in Medicine | Lectures | 1.00 | auditorium | |||||
| 13 | Digitising Processes With Artificial Intelligence Tools | Classes | 1.00 | computer room | |||||
| 14 | Practical Applications of AI and Industry Expertise | Lectures | 1.00 | auditorium | |||||
| 15 | AI Applications and Future Perspectives | Lectures | 1.00 | auditorium | |||||
| Topic Layout (Part-Time) | |||||||||
| No. | Topic | Type of Implementation | Number | Venue | |||||
| 1 | Introduction. Types and Tools of Artificial Intelligence | Lectures | 1.00 | auditorium | |||||
| 2 | Introduction. Restrictions, Copyright, Ethics and Threats | Lectures | 1.00 | auditorium | |||||
| 3 | Practical Seminar on Creating Prompts I – Basic Level; Introduction to ChatGPT | Classes | 1.00 | computer room | |||||
| 4 | Practical Seminar on Creating Prompts II – Prompt Optimisation and Applications in Different Situations | Classes | 1.00 | computer room | |||||
| 5 | Practical Seminar on Prompt Engineering I | Classes | 1.00 | computer room | |||||
| 6 | Practical Seminar on Prompt Engineering II | Classes | 1.00 | computer room | |||||
| 7 | Practical Seminar on Prompt Engineering III | Classes | 1.00 | computer room | |||||
| 8 | Artificial Intelligence Tools for Text Generation I – Their Capabilities, Limitations and Differences | Lectures | 1.00 | computer room | |||||
| 9 | Artificial Intelligence Tools for Text Generation II – Their Capabilities, Limitations and Differences | Lectures | 1.00 | auditorium | |||||
| 10 | Artificial Intelligence and Image Generation I (Image Generation Platforms) | Classes | 1.00 | computer room | |||||
| 11 | Artificial Intelligence and Image Generation II (Image Generation Servers) | Classes | 1.00 | computer room | |||||
| 12 | Generative Artificial Intelligence in Medicine | Lectures | 1.00 | auditorium | |||||
| 13 | Digitising Processes With Artificial Intelligence Tools | Classes | 1.00 | computer room | |||||
| 14 | Practical Applications of AI and Industry Expertise | Lectures | 1.00 | auditorium | |||||
| 15 | AI Applications and Future Perspectives | Lectures | 1.00 | auditorium | |||||
| Assessment | |||||||||
| Unaided Work: | 1. Students independently study the required reading on each class topic, using the resources in the university’s online databases. Textual content generation - to create a clear, logical text relevant to the target audience using AI tools. Generating graphical content - create visually appealing and informative images or diagrams that meet the requirements of the task. Prompt development - to formulate precise and detailed prompts to get the desired results from AI generative tools. 2. More specific tasks are updated each year and presented on the e-learning platform. 3. To assess the overall quality of the study course, the student must complete the course evaluation questionnaire on the Student Portal. | ||||||||
| Assessment Criteria: | 1. Regular attendance of lectures, active participation in practical classes – 20%. 2. Assessment of independent learning – 50%. 3. Passing the tests – 30%. | ||||||||
| Final Examination (Full-Time): | Exam | ||||||||
| Final Examination (Part-Time): | Exam | ||||||||
| Learning Outcomes | |||||||||
| Knowledge: | 1. Students will have good knowledge of artificial intelligence solutions and industry trends. 2. Students will have all the necessary knowledge to discuss the applications of AI and to argue for the use of different solutions. 3. Students will have mastered at least 10 AI tools and will be able to operate freely in various generative artificial intelligence solutions. 4. Students will have mastered at least 10 different prompt engineering techniques and will be able to generate high-quality and meaningful content. | ||||||||
| Skills: | 1. Students will be able to generate results in both text and image format. 2. Students will be able to write prompts to achieve effective results when generating a wide variety of content. 3. Students will be able to freely discuss the ethics and applications of artificial intelligence tools. 4. Students will be able to design and digitise various processes, as well as streamline their personal work and increase productivity using AI tools. | ||||||||
| Competencies: | 1. Competence to generate high-quality content. 2. Competence to critically evaluate AI tools and their applications: Students must not only freely orient in artificial intelligence solutions and industry trends, but also be able to critically evaluate different AI tools and their applications based on their knowledge of different AI tools and their capabilities. 3. Understanding of ethics and responsibility: Competence includes the ability to discuss and argue about the ethics and responsible use of artificial intelligence tools, an understanding of potential risks and opportunities, and the ability to make informed choices based on ethical considerations. 4. Students must be able not only to create and digitise different processes, but also to streamline their personal work and productivity using artificial intelligence tools. This includes the ability to adapt and integrate AI tools into different work processes to improve efficiency and performance. 5. Prompt engineering and problem-solving competence: Students must have learned different methods of prompt engineering and be able to use these methods to generate meaningful content of high quality. This includes the ability to analyse and define the problem, design an effective prompt and use critical thinking to adapt and optimise generation processes according to specific needs and objectives. | ||||||||
| Bibliography | |||||||||
| No. | Reference | ||||||||
| Required Reading | |||||||||
| 1 | Prompt Engineering Guide | ||||||||
| 2 | Fatih Kadir Akin. The Art of ChatGPT Prompting: A Guide to Crafting Clear and Effective Prompts | ||||||||
| 3 | Fatih Kadir Akin. The Art of Midjourney AI: A Guide to Creating Images from Text | ||||||||
| Additional Reading | |||||||||
| 1 | Mākslīgais intelekts augstākajā izglītībā. RSU, 2024 (latviešu plūsmai) | ||||||||
