Course Outline
Foundations of Agentic AI and Bootcamp Introduction
- Exploring agentic AI concepts and the course structure
- Overview of essential tools, frameworks, and dependencies
- Guidelines for effective project setup and team collaboration
Project 1: Building an Intelligent Assistant with Prompt-Driven Reasoning
- Architecting a task-focused conversational agent
- Leveraging structured prompts to enhance reasoning and decision-making
- Development and testing within Jupyter Notebook
Project 2: Creating a 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: Developing a Tool-Integrated Agent for Workflow Automation
- Connecting external APIs to automate routine tasks
- Orchestrating multi-step processes via agentic loops
- Constructing a specialized automation assistant for specific business workflows
Project 4: Implementing a Data Analysis and Insight Generation Agent
- Linking agents to diverse data sources such as CSV, SQL, or APIs
- Conducting exploratory data analysis with the support of Python and AI
- Generating visual insights and performance dashboards
Project 5: Managing Multi-Agent Collaboration and Orchestration
- Coordinating multiple agents for efficient task delegation
- Structuring a controller–worker architecture
- Deploying and validating a prototype multi-agent system
Conclusion and Future Directions
- Project presentations and peer reviews
- Exploring strategies for optimization and system scaling
- Accessing resources for ongoing learning and experimentation
Requirements
- Intermediate level command of Python programming
- Foundational 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 looking to acquire rapid prototyping skills in agentic AI
- Professionals engaged 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.
