Course Outline
Introduction to Agentic AI and Bootcamp Overview
- Exploring agentic AI concepts and the bootcamp's structure
- Reviewing necessary tools, frameworks, and dependencies
- Best practices for setting up projects and collaborating
Project 1: Intelligent Assistant with Prompt-Oriented Reasoning
- Designing a task-driven conversational agent
- Leveraging structured prompts for 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
- Generating executive reports from both structured and unstructured content
Project 3: Tool-Using Agent for Workflow Automation
- Integrating external APIs and automating repetitive tasks
- Managing multi-step processes via agentic loops
- Creating a small automation assistant for actual business workflows
Project 4: Data Analysis and Insight Generation Agent
- Linking agents to data sources such as CSV, SQL, or APIs
- Conducting exploratory data analysis using Python and AI support
- Creating visual insights and performance dashboards
Project 5: Multi-Agent Collaboration and Orchestration
- Coordinating multiple agents for task delegation
- Designing a controller–worker architecture
- Deployment and testing of a prototype multi-agent system
Wrap-Up and Next Steps
- Project presentations and peer feedback sessions
- Discussion on optimization and scaling strategies
- Resources for ongoing learning and experimentation
Requirements
- Intermediate level of proficiency in Python programming
- Fundamental knowledge of AI or machine learning concepts
- Experience with APIs and data processing workflows
Target Audience
- Engineers and developers seeking to create practical AI projects
- Technical teams aiming to acquire rapid prototyping capabilities in agentic AI
- Practitioners 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.
