AI in Business 2600-MSdz2AIBen
The course gives a comprehensive overview of AI – from its early history to the latest large language model (LLM) and generative AI services. Students will learn about:
* using internet tools (ChatGPT, Gemini, Perplexity, Notepad LLM), AWS AI services,
* running open source LLMs locally,
* generating AI created images,
* building Retrieval Augmented Generation (RAG) pipelines,
* using knowledge graphs,
* designing simple AI agents,
* AI security threats,
* cost management for AI usage,
* AI in marketing, research and education,
* advanced LLM configuration and fine tuning
Course coordinators
Type of course
Mode
Learning outcomes
Knowledge
K_W05 – Knowledge of the key milestones in the development of AI.
K_W06 – Ability to distinguish classical paradigms of ML, deep learning, and LLM.
K_W07 – Knowledge of major public AI services and AWS Bedrock offerings.
K_W08 – Ability to choose between cloud-based and local open-source LLM depending on the use case.
K_W09 – Understanding of RAG concepts and the role of knowledge graphs (RAGgraph).
K_W10 – Knowledge of AI applications in marketing and commerce.
K_W11 – Knowledge of the possibilities of using AI in research and education.
K_W12 – Understanding the role and limitations of fine-tuning LLM models.
K_W13 – Understanding the factors for optimizing the costs of AI services.
Skills
K_U01 – Ability to generate and evaluate AI-created images for business applications.
K_U02 – Ability to build a basic AI agent and assess its level of automation and limitations.
K_U03 – Identification of major AI security risks.
Social Competences
K_K01 – Ability to critically evaluate the use of AI in organizations and projects.
K_K07 – Ability to reflectively analyze the social, ethical, and business implications of AI use, demonstrating responsible decision-making.
Assessment criteria
Participation in lessons and written exam – 100 % of the final grade. The exam will test theory, practical prompt‑engineering, RAG design, cost‑management, fine‑tuning concepts and security/compliance.
Written exam (0.5 h, remote, supervised via Zoom)
Bibliography
1. Agentic Artificial Intelligence: Harnessing AI Agents to Reinvent Business, Work, and Life by Pascal Bornet
2. Intelligent Automation: Learn How to Harness Artificial Intelligence to Boost Business & Make Our World More Human by Pascal Bornet
3. ChatGPT is bullshit - Michael Townsen Hicks, James Humphries, Joe Slater
4. Build a RAG agent with LangChain - https://docs.langchain.com/oss/python/langchain/rag
5. AWS Bedrock documentation - https://docs.aws.amazon.com/bedrock/latest/userguide/what-is-bedrock.html