Artificial Intelligence in the Social Sciences

Study Course Description

Course Description Statuss:Approved

Course Description Version:2.00

Study Course Accepted:29.04.2024 09:53:16

Study Course Information
Course Code:		SZF_119		LQF level:		All Levels
Credit Points:		2.00		ECTS:		3.00
Branch of Science:		Computer sciences and informatics; Other computer sciences		Target Audience:		Communication Science; Management Science; Law; Political Science; Psychology; Person and Property Defence; Social Anthropology; Civil and Military Defense; Sociology; Marketing and Advertising; Juridical 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, szfrsu[pnkts]lv
Study Course Planning
Full-Time - Semester No.1
Lectures (count)		11	Lecture Length (academic hours)		2	Total Contact Hours of Lectures		22
Classes (count)		5	Class Length (academic hours)		2	Total Contact Hours of Classes		10
Total Contact Hours								32
Part-Time - Semester No.1
Lectures (count)		4	Lecture Length (academic hours)		2	Total Contact Hours of Lectures		8
Classes (count)		4	Class Length (academic hours)		2	Total Contact Hours of Classes		8
Total Contact Hours								16
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 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	other
4	Practical Seminar on Creating Prompts II – Basic Level; Introduction to ChatGPT			Classes		1.00	other
5	Practical Seminar on Creating Prompts III – Prompt Optimisation and Applications in Different Situations			Classes		1.00	computer room
6	Practical Seminar on Prompt Engineering I			Lectures		1.00	other
7	Practical Seminar on Prompt Engineering II			Lectures		1.00	other
8	Practical Seminar on Prompt Engineering III			Classes		1.00	computer room
9	Artificial Intelligence Tools for Text Generation I – Their Capabilities, Limitations and Differences			Lectures		1.00	other
10	Artificial Intelligence Tools for Text Generation II – Their Capabilities, Limitations and Differences			Lectures		1.00	other
11	Artificial Intelligence and Image Generation I (Image Generation Platforms)			Lectures		1.00	other
12	Artificial Intelligence and Image Generation I (Image Generation Servers)			Lectures		1.00	other
13	Generative Artificial Intelligence in Social Sciences – Use Cases and Future Perspectives			Lectures		1.00	auditorium
14	Digitising Processes With Artificial Intelligence Tools			Classes		1.00	computer room
15	Practical Applications of AI and Industry Expertise			Lectures		1.00	auditorium
16	AI Applications and Future Perspectives			Lectures		1.00	auditorium
Topic Layout (Part-Time)
No.	Topic			Type of Implementation		Number	Venue
3	Practical Seminar on Creating Prompts I – Basic Level; Introduction to ChatGPT			Classes		1.00	other
5	Practical Seminar on Creating Prompts III – Prompt Optimisation and Applications in Different Situations			Classes		1.00	computer room
6	Practical Seminar on Prompt Engineering I			Lectures		1.00	other
8	Practical Seminar on Prompt Engineering III			Classes		1.00	computer room
11	Artificial Intelligence and Image Generation I (Image Generation Platforms)			Lectures		1.00	other
13	Generative Artificial Intelligence in Social Sciences – Use Cases and Future Perspectives			Lectures		1.00	auditorium
14	Digitising Processes With Artificial Intelligence Tools			Classes		1.00	computer room
15	Practical Applications of AI and Industry Expertise			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)