Applications: creativity and application DM-KW-SL>AplKreZas
The course "Applications: Creativity and Application" provides a comprehensive introduction to modern technologies related to artificial intelligence, prompt engineering, chatbot development, and programming solutions based on the Internet of Things (IoT). The classes combine theory with intensive practical workshops, developing the skills necessary for the creative and effective use of digital tools in contemporary applications.
As part of the course, students are introduced to the mechanisms of large language models such as ChatGPT, Claude, and Perplexity, which form the foundation of modern AI solutions. Particular emphasis is placed on developing skills in prompt engineering — a technique for optimizing queries and communication with language models to obtain precise and valuable results. Students learn to formulate advanced prompts by analyzing examples based on film and literary preferences, allowing them to understand how artificial intelligence processes input data and generates responses.
Another key aspect of the course is learning to generate images using AI. In this module, students have the opportunity to explore the capabilities of modern generative models and experiment with creating visual content based on textual prompts. These classes develop both technical skills and creativity in the use of tools such as DALL·E and Stable Diffusion.
An integral part of the program is a module dedicated to building chatbots based on language models. Students work in the Botpress environment, which enables them to design and implement intelligent conversational bots. Through this process, they gain knowledge about chatbot architecture and the mechanisms for integrating them with external systems, preparing them to implement similar solutions in professional environments.
Later in the course, students are introduced to the basics of programming Raspberry Pi microcontrollers using the Node-RED platform. This module focuses on the practical application of Internet of Things (IoT) technology, enabling the creation of simple remote-controlled applications and data integration from various sources. Students learn how to connect microcontrollers with AI-based solutions, opening up vast possibilities for automation and intelligent systems.
An additional educational value is provided by a study visit to the smart building laboratory, which is part of the international EduNet network. The laboratory, located at the Faculty of Electrical and Computer Engineering of the Cracow University of Technology, offers an excellent space for showcasing modern technological solutions in the context of smart management systems and building automation.
The course concludes with a final project in which students independently develop solutions based on the creative and automated use of digital tools, with a particular focus on advanced prompt engineering techniques. This project aims to combine theoretical knowledge with practical skills, as well as to develop students' capacity for independent project thinking and teamwork.
The course "Applications: Creativity and Application" prepares students to work in interdisciplinary teams, developing the skills needed to implement modern technologies in various fields of life and industry. By combining artificial intelligence, IoT, and prompt engineering, students gain a broad perspective on the possibilities of contemporary technological solutions and their applications.
(in Polish) Tryb zajęć
Course coordinators
Term 2023/2024-Z: | Term 2022/2023-Z: | Term 2024/2025-Z: |
Learning outcomes
Knowledge:
The student understands the basic principles of large language models (e.g., ChatGPT, Claude, Perplexity) and the mechanisms for generating texts and images using artificial intelligence.
They are familiar with the concepts and techniques of prompt engineering and its application in interacting with AI models.
They understand the principles of chatbot development and the architecture of tools such as Botpress.
They possess knowledge of Internet of Things (IoT) technologies and the basics of programming Raspberry Pi microcontrollers using Node-RED.
Skills:
The student is capable of creating advanced prompts tailored to specific tasks to achieve precise and relevant responses from large language models.
They can generate images using artificial intelligence while maintaining a creative and technically sound approach.
They can independently design and implement conversational chatbots using Botpress, adapting them to specific use-case scenarios.
They are able to program Raspberry Pi microcontrollers using Node-RED to implement IoT-based solutions.
They can integrate AI-driven solutions with automation elements in practical applications.
Social Competencies:
The student is able to work effectively in a team on project implementation, demonstrating clear communication and task-sharing skills.
They display creativity in seeking technological solutions and show openness to new methods of working with AI and IoT tools.
They understand the need for continuous improvement of their technological competencies and adaptability to a dynamically changing job market.
They can present and justify the results of their work, both orally and in writing, using appropriate multimedia tools.
Assessment criteria
Methods and Assessment Criteria
The final grade for the course “Applications: Creativity and Use” is based on the completion of the project and ongoing participation during classes. Students earn points for successfully completed tasks, engagement, and the accuracy of their work. Detailed guidelines have been streamlined to simplify the assessment process and provide greater flexibility in evaluating student performance.
Final Grade Breakdown
Final Project – 60% of the final grade
Ongoing Participation – 40% of the final grade
The final project involves creating an application or a solution integrating elements of prompt engineering, image generation, process automation, or IoT. The key assessment aspects include functionality, creativity, and overall quality of the project. The ability to justify design decisions and effectively present the outcomes is also evaluated.
Ongoing participation is assessed based on systematic work, engagement, and the accuracy of tasks completed during classes. Regular attendance, initiative, and the ability to solve problems that arise during exercises are of particular importance.
Assessment Criteria
The final grade takes into account:
the quality and functionality of the final project,
the level of refinement and compliance with guidelines,
participation and engagement during classes,
the ability to work in a team and solve problems.
The final assessment considers both individual work outcomes and participation during practical exercises. High engagement, systematic effort, and creativity are key to achieving the best results.
Bibliography
Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach. Pearson Education.
Brownlee, J. (2021). Deep Learning for Natural Language Processing: Develop Deep Learning Models for your Text Data. Machine Learning Mastery.
Botpress Team. (2023). Botpress Documentation and User Manual. Botpress Inc.
Raspberry Pi Foundation. (2022). Getting Started with Raspberry Pi and Node-RED. Raspberry Pi Press.
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: