Course Outline
Introduction to Agentic AI and Course Overview
- Exploring the concept of agentic AI and the bootcamp structure
- Reviewing essential tools, frameworks, and dependencies
- Establishing best practices for project setup and team collaboration
Project 1: Intelligent Assistant with Prompt-Oriented Reasoning
- Designing a task-focused conversational agent
- Utilizing structured prompts to enhance reasoning and decision-making
- Developing and testing within a Jupyter Notebook environment
Project 2: Document Analysis and Summarization Agent
- Extracting and summarizing data from PDFs and text files
- Leveraging LangChain for document ingestion and retrieval tasks
- Producing 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 via agentic loops
- Constructing a small-scale automation assistant for real business workflows
Project 4: Data Analysis and Insight Generation Agent
- Connecting agents to various data sources (CSV, SQL, or API)
- Conducting exploratory data analysis using Python and AI assistance
- 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 testing a prototype multi-agent system
Conclusion and Future Steps
- Project presentations and peer review sessions
- Discussion on optimization and scaling strategies
- Providing resources for continued learning and experimentation
Requirements
- Intermediate-level proficiency in Python programming
- Foundational understanding of AI or machine learning principles
- Experience with APIs and data processing workflows
Target Audience
- Engineers and developers seeking to create applied AI solutions
- Technical teams aiming to master rapid prototyping 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.
