Course Outline
Introduction to Agentic AI and Bootcamp Overview
- Exploring agentic AI concepts and the structure of the bootcamp
- Overview of essential tools, frameworks, and dependencies
- Recommended practices for setting up projects and collaborating effectively
Project 1: Intelligent Assistant with Prompt-Oriented Reasoning
- Architecting a conversational agent focused on specific tasks
- Leveraging structured prompts for logical reasoning and decision-making
- Constructing and validating the agent within Jupyter Notebook
Project 2: Document Analysis and Summarization Agent
- Extracting and condensing information from PDFs and text documents
- Utilizing LangChain for document ingestion and retrieval processes
- Synthesizing executive reports from both structured and unstructured data
Project 3: Tool-Using Agent for Workflow Automation
- Connecting external APIs to automate routine operational tasks
- Orchestrating multi-step processes via agentic feedback loops
- Developing a compact automation assistant for genuine business workflows
Project 4: Data Analysis and Insight Generation Agent
- Linking agents to various data sources (CSV, SQL, or API)
- Conducting exploratory data analysis with the support of Python and AI
- Generating visual insights and performance dashboards
Project 5: Multi-Agent Collaboration and Orchestration
- Coordinating multiple agents for effective task delegation
- Implementing a controller–worker architectural model
- Deploying and evaluating a prototype multi-agent system
Conclusion and Future Directions
- Presentation of projects and receipt of peer feedback
- Exploration of optimization techniques and scaling strategies
- Access to resources for ongoing learning and experimentation
Requirements
- Intermediate level proficiency in Python programming
- Fundamental knowledge of AI or machine learning concepts
- Experience with API interactions and data processing workflows
Target Audience
- Engineers and developers aiming to create applied AI solutions
- Technical teams seeking to accelerate prototyping skills in agentic AI
- Professionals engaged 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.
