Course Outline
Introduction to Agentic AI and Bootcamp Structure
- Overview of agentic AI concepts and the bootcamp layout
- Review of necessary tools, frameworks, and dependencies
- Best practices for project initialization and team collaboration
Project 1: Intelligent Assistant with Prompt-Focused Reasoning
- Designing a conversational agent for specific tasks
- Employing structured prompts to drive reasoning and decision-making
- Construction and testing within Jupyter Notebook
Project 2: Document Analysis and Summarization Agent
- Extracting and condensing data from PDFs and text files
- Utilizing LangChain for document ingestion and retrieval
- Producing executive reports from both structured and unstructured content
Project 3: Tool-Using Agent for Workflow Automation
- Connecting external APIs and automating recurring tasks
- Orchestrating multi-step processes via agentic loops
- Developing a compact automation assistant for genuine business workflows
Project 4: Data Analysis and Insight Generation Agent
- Linking agents to data sources (CSV, SQL, or API)
- Conducting exploratory data analysis with the aid of Python and AI
- Generating visual insights and performance dashboards
Project 5: Multi-Agent Collaboration and Orchestration
- Coordinating multiple agents for task delegation
- Architecting a controller-worker model
- Deploying and testing a prototype multi-agent system
Conclusion and Future Steps
- Project presentations and peer reviews
- Exploration of optimization and scaling strategies
- Resources for ongoing learning and experimentation
Requirements
- Intermediate-level skills in Python programming
- Fundamental knowledge of AI or machine learning concepts
- Experience with APIs and data processing workflows
Audience
- Engineers and developers aiming to build practical AI projects
- Technical teams seeking to enhance rapid prototyping capabilities in agentic AI
- Practitioners engaged in AI integration and pilot program creation
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.
