Course Outline
Foundations of Agentic AI and Bootcamp Introduction
- Exploring the concept of agentic AI and the bootcamp’s structure
- Reviewing essential tools, frameworks, and dependencies
- Adopting best practices for project setup and team collaboration
Project 1: Intelligent Assistant with Prompt-Oriented Reasoning
- Designing a task-focused conversational agent
- Leveraging structured prompts to drive reasoning and decision-making
- Developing and testing 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 tasks
- Producing executive reports from both structured and unstructured data
Project 3: Tool-Using Agent for Workflow Automation
- Integrating external APIs to automate repetitive business tasks
- Managing multi-step processes via agentic loops
- Building a compact automation assistant tailored to real-world business workflows
Project 4: Data Analysis and Insight Generation Agent
- Connecting agents to diverse data sources such as CSV, SQL, or APIs
- Conducting exploratory data analysis assisted by 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 architecture
- Deploying and validating a prototype multi-agent system
Conclusion and Future Directions
- Presenting projects and gathering peer feedback
- Discussing strategies for optimization and scaling
- Accessing resources for ongoing learning and experimentation
Requirements
- Intermediate-level proficiency in Python programming
- Foundational knowledge of AI or machine learning principles
- Working familiarity with APIs and data processing workflows
Target Audience
- Engineers and developers aiming to build applied AI solutions
- Technical teams seeking to enhance rapid prototyping capabilities in agentic AI
- Professionals involved in AI integration and pilot program development
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.
