Uniwersytet Warszawski, Wydział Nauk Ekonomicznych - Centralny System Uwierzytelniania
Strona główna

Artificial Intelligence – Practical Introduction to AI Usage for Data Science and Business

Informacje ogólne

Kod przedmiotu: 2400-ZEWW911
Kod Erasmus / ISCED: (brak danych) / (brak danych)
Nazwa przedmiotu: Artificial Intelligence – Practical Introduction to AI Usage for Data Science and Business
Jednostka: Wydział Nauk Ekonomicznych
Grupy: Przedmioty kierunkowe dla Data Science
Przedmioty kierunkowe do wyboru - studia II stopnia EM - grupa 3 (3*30h)
Przedmioty kierunkowe do wyboru - studia II stopnia IE - grupa 2 (2*30h)
Przedmioty wyboru kierunkowego dla studiów licencjackich EM
Przedmioty wyboru kierunkowego dla studiów licencjackich IE
Przedmioty wyboru kierunkowego dla studiów licencjackich MSEM
Punkty ECTS i inne: 3.00 Podstawowe informacje o zasadach przyporządkowania punktów ECTS:
  • roczny wymiar godzinowy nakładu pracy studenta konieczny do osiągnięcia zakładanych efektów uczenia się dla danego etapu studiów wynosi 1500-1800 h, co odpowiada 60 ECTS;
  • tygodniowy wymiar godzinowy nakładu pracy studenta wynosi 45 h;
  • 1 punkt ECTS odpowiada 25-30 godzinom pracy studenta potrzebnej do osiągnięcia zakładanych efektów uczenia się;
  • tygodniowy nakład pracy studenta konieczny do osiągnięcia zakładanych efektów uczenia się pozwala uzyskać 1,5 ECTS;
  • nakład pracy potrzebny do zaliczenia przedmiotu, któremu przypisano 3 ECTS, stanowi 10% semestralnego obciążenia studenta.

zobacz reguły punktacji
Język prowadzenia: angielski
Rodzaj przedmiotu:

nieobowiązkowe

Skrócony opis: (tylko po angielsku)

The goal of this course is to make students familiar with the intricacies of AI, empowering them to understand, utilise, and critically assess its applications. Beginning with an exploration of AI fundamentals (including the discussion on structure and training of Large Language Models) and the importance of creativity, the course progresses to practical communication with AI through effective prompts. Students learn practical AI applications by generating text, graphics and other media. The critical thinking module equips them to recognise, assess, and improve AI output, addressing potential AI hallucinations. Ethical and legal considerations are explored, emphasising responsible AI use in academic and professional settings. Practical applications in academia and data analytics, leveraging AI as an assistant, and a dedicated session on daily life use cases provide hands-on experience.

Pełny opis: (tylko po angielsku)

Class 1: Understanding AI

- Introduction to AI, LLM models, and their applications in data science.

- AI tools - demystifying the "magic" - how LLM models are build and trained.

- Critical overview of AI's pros and cons.

- Importance of creativity and its role in AI applications.

- Discussion on the repetitive nature of AI tasks.

Class 2-3: Efficient Communication with AI - Writing Effective Prompts

- Exploration of text-generating models like ChatGPT.

- Challenges of communication with LLM - concept of prompts.

- Importance and creation of well-crafted prompts.

- Practical prompt writing exercises on the example of ChatGPT / Bing.

- Creating roles and context for AI tasks.

- Examples and detailed prompt making for text generation.

Class 4-5: AI Applications Beyond Text - Generating Graphics, Sounds, Videos, and other

- Overview of AI applications beyond text generation.

- Introduction to various chatbots and other AI tools for graphics, voices, and videos.

- Discussion and brainstorming session about novel AI techniques.

- Hands-on experience with AI chatbots hosted on Discord and other platforms.

- Dedicated session for graphic generation.

Class 6-7: Critical Thinking and AI

- Importance of critical thinking in assessing AI-generated content.

- Practical exercises on assessing and verifying output from AI models.

- AI hallucinations - what is it, how to identify, how to improve.

- Analysing text for ideas, sources, and truth.

- Discussion on the evolving nature and the rising importance of critical thinking in the AI era.

- Critical thinking exercises in a workshop setting.

Class 8: Threats, Ethics, and Legal Considerations of AI

- Exploration of AI-related threats like deep fakes and misinformation.

- Examples of AI interference in media and political news.

- Techniques for recognising fake photos and videos.

- The role of critical thinking in addressing AI-related threats.

- Ethical considerations in academic and professional AI usage.

- Legal restrictions and considerations, including data secrecy and potential leakage.

Class 9-10: Academic and Data Analytics Usage. Can AI be an assistant in our job?

- AI as an assistant in academic settings, including text improvement and idea refinement.

- Discussion on where not to use AI due to issues with originality and academic ethics.

- Practical usage of AI in data analytics projects.

- Leveraging AI applications for repetitive tasks, while highlighting the importance of own style originality and developing human creativity.

- Discussion on limited trust in AI generated content - critical assessment of AI output.

- Using AI as an assistant for learning, writing and proofreading - speeding up your workflow and making it more efficient with the help of AI.

Class 11: Utilising AI Plug-ins and Understanding How They Work

- Overview of existing AI plug-ins for data science - examples and discussion.

- Integration of chat with plug-ins.

- Connecting chats to the internet for real-time information.

- Structure of AI plug-ins - how LLM model output can be linked to your applications.

Class 12: Using AI for Daily Life Use Cases

- Discussion about creative ways to leverage AI possibilities in daily life.

- Applying AI in daily life scenarios.

- Building trip plans, language learning, creating business models, and generating content for social media using AI.

- Is AI the new Google? Discussion and brainstorming on the relation between user-generated and AI-generated content in daily life applications.

- Can AI be your teacher? How to make the best of your AI assistant - learning new skills with AI, while critically considering its possible limitations.

Class 13-14: Winning with AI Transformation

- Identifying and practising the essential skills for success in the AI era.

- Developing critical thinking and creative skills.

- Building deep understanding of the opportunities and challenges of AI integration.

- Utilising AI as a personal assistant - becoming more efficient, and speeding up mundane tasks with AI automation.

- Utilising AI as a tool for personal and professional growth.

- Strategies for staying ahead in the rapidly evolving field of AI.

Class 15: Course Review and Reflection

- Recap of key concepts and skills learned.

- Reflection on personal growth and development throughout the course.

- Open discussion on future applications and trends in AI.

Assessment:

- Attendance at the lectures and participation in critical thinking discussions.

- Weekly assignments and practical exercises.

- Final project incorporating AI tools.

Literatura: (tylko po angielsku)

- Own materials and resources provided during the classes.

Literature:

- Bell, S. (2023). The write algorithm: promoting responsible artificial intelligence usage and accountability in academic writing. BMC medicine, 21(1), 334.

- Eke, D. O. (2023). ChatGPT and the rise of generative AI: threat to academic integrity?. Journal of Responsible Technology, 13, 100060.

- McKinsey, M. (2023). ChatGPT, GPTs, and LLMs Survey Paper.

Efekty uczenia się: (tylko po angielsku)

After this course, the student:

- Understands the fundamentals of AI, including LLM models and their applications in data science and business.

- Possesses practical communication skills with AI, writes effective prompts and understands their importance.

- Utilizes AI tools in various contexts, like generation of text, graphics and other media.

- Develops critical thinking skills, and is capable of assessing and improving AI-generated content while navigating potential problems with AI hallucinations and originality issues.

- Gains ethical awareness regarding AI usage for academic and professional setting, including recognizing and addressing threats like deep fakes and misinformation.

- Applies AI in various practical scenarios, from academia and data analytics to daily life, fostering efficiency and creativity.

K_U02, K_U05

Metody i kryteria oceniania: (tylko po angielsku)

- Attendance at the lectures and participation in critical thinking discussions.

- Weekly assignments and practical exercises.

- Final project incorporating AI tools.

Zajęcia w cyklu "Semestr letni 2023/24"

Okres: 2024-02-19 - 2024-06-16
Wybrany podział planu:
Przejdź do planu
Typ zajęć:
Konwersatorium, 30 godzin więcej informacji
Koordynatorzy: Maria Kubara
Prowadzący grup: Maria Kubara
Lista studentów: (nie masz dostępu)
Zaliczenie: Przedmiot - Zaliczenie na ocenę
Konwersatorium - Zaliczenie na ocenę
Opisy przedmiotów w USOS i USOSweb są chronione prawem autorskim.
Właścicielem praw autorskich jest Uniwersytet Warszawski, Wydział Nauk Ekonomicznych.
ul. Długa 44/50
00-241 Warszawa
tel: +48 22 55 49 126 https://www.wne.uw.edu.pl/
kontakt deklaracja dostępności mapa serwisu USOSweb 7.0.4.0-3 (2024-06-10)