Course Outline
Foundations of Agentic AI and Workshop Introduction
- Exploring agentic AI concepts and the structure of the workshop
- Overview of essential tools, frameworks, and dependencies
- Best practices for project initialization and collaborative development
Project 1: Intelligent Assistant Focused on Prompt Reasoning
- Architecting a task-driven conversational agent
- Leveraging structured prompts to drive reasoning and decision-making
- Construction and validation within Jupyter Notebook
Project 2: Agent for Document Analysis and Summarization
- Pulling and condensing data from PDFs and text documents
- Utilizing LangChain for document ingestion and retrieval processes
- Synthesizing executive reports from both structured and unstructured content
Project 3: Tool-Integrated Agent for Workflow Automation
- Connecting external APIs to automate repetitive operational tasks
- Oversight of multi-step processes via agentic loops
- Creating a compact automation assistant for specific business workflows
Project 4: Agent for Data Analysis and Insight Generation
- Linking agents to data sources such as CSV files, SQL databases, or APIs
- Conducting exploratory data analysis using Python with AI support
- Developing visual insights and performance dashboards
Project 5: Multi-Agent Collaboration and Orchestration
- Orchestrating multiple agents for effective task delegation
- Structuring a controller–worker architecture
- Deployment and testing of a prototype multi-agent system
Conclusion and Future Directions
- Project showcases and peer review feedback
- Exploring optimization and scaling methodologies
- Access to resources for ongoing learning and experimentation
Requirements
- Intermediate level proficiency in Python programming
- Foundational knowledge of AI or machine learning concepts
- Experience with APIs and data processing pipelines
Target Audience
- Engineers and developers aiming to implement applied AI solutions
- Technical teams looking to accelerate prototyping in the agentic AI space
- Professionals involved in AI integration and pilot program initiatives
Testimonials (1)
First most valuable: Practical data analysis tasks using AI without copy-pasting - but through my own application of what I learned. Second most valuable: definition of terms that everyone uses (skills, agents, MCP, API). Now that I understand them, I feel much more confident in trying AI Third: your input on how AI works, what it can do, what it can't (I will remember your 80/20 rule forever). Fourth: Having everything you taught us in written and accessible form.
