Course Outline
Introduction to Agentic AI and Bootcamp Overview
- Exploring the concept of agentic AI and the structure of the bootcamp
- Reviewing essential tools, frameworks, and dependencies
- Establishing best practices for project setup and collaborative workflows
Project 1: Intelligent Assistant with Prompt-Oriented Reasoning
- Designing a conversational agent focused on specific tasks
- Leveraging structured prompts to drive reasoning and decision-making
- Building and testing the agent within a Jupyter Notebook environment
Project 2: Document Analysis and Summarization Agent
- Extracting and summarizing data from PDFs and text documents
- Utilizing LangChain for document ingestion and retrieval processes
- Generating executive reports from both structured and unstructured content
Project 3: Tool-Using Agent for Workflow Automation
- Integrating external APIs to automate repetitive tasks
- Managing multi-step processes through agentic loops
- Developing a compact automation assistant for practical 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 using Python with AI assistance
- Generating visual insights and performance dashboards
Project 5: Multi-Agent Collaboration and Orchestration
- Coordinating multiple agents for effective task delegation
- Designing a controller–worker architecture
- Deploying and testing a prototype of a multi-agent system
Wrap-Up and Next Steps
- Presenting projects and receiving peer feedback
- Discussing strategies for optimization and scaling
- Accessing resources for ongoing learning and experimentation
Requirements
- Intermediate level proficiency in Python programming
- Fundamental understanding of AI or machine learning concepts
- Working knowledge of APIs and data processing workflows
Target Audience
- Engineers and developers aiming to construct applied AI projects
- Technical teams seeking to accelerate prototyping skills in agentic AI
- Professionals engaged in AI integration and the development of pilot programs
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.
