Course Outline
Introduction to Agentic AI and Bootcamp Structure
- Overview of agentic AI concepts and course organization
- Review of essential tools, frameworks, and dependencies
- Best practices for setting up projects and collaborating effectively
Project 1: Intelligent Assistant with Prompt-Driven Reasoning
- Designing a task-oriented conversational agent
- Utilizing structured prompts to facilitate reasoning and decision-making
- Building and testing the agent within Jupyter Notebook
Project 2: Document Analysis and Summarization Agent
- Extracting and summarizing data from PDFs and text documents
- Leveraging LangChain for document ingestion and retrieval tasks
- Generating executive reports from both structured and unstructured content
Project 3: Tool-Enabled Agent for Workflow Automation
- Integrating external APIs to automate repetitive tasks
- Managing multi-step processes using agentic loops
- Creating a specialized automation assistant for real-world business workflows
Project 4: Data Analysis and Insight Generation Agent
- Connecting agents to various data sources such as CSV, SQL, or APIs
- 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 efficient task delegation
- Designing a controller–worker architectural model
- Deploying and testing a prototype multi-agent system
Conclusion and Future Directions
- Project presentations and feedback from peers
- Discussion of strategies for optimization and system scaling
- Resources for ongoing learning and experimentation
Requirements
- Intermediate-level proficiency in Python programming
- Foundational knowledge of AI or machine learning concepts
- Familiarity with API interactions and data processing workflows
Target Audience
- Engineers and developers aiming to develop practical AI solutions
- Technical teams seeking to acquire rapid prototyping skills in agentic AI
- 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.
