Course Outline
Introduction to Agentic AI and Bootcamp Structure
- Overview of agentic AI concepts and the bootcamp framework
- Review of essential tools, frameworks, and dependencies
- Best practices for project initialization and team collaboration
Project 1: Intelligent Assistant with Prompt-Driven Reasoning
- Architecting a task-focused conversational agent
- Leveraging structured prompts for logical reasoning and decision-making
- Development and testing within a Jupyter Notebook environment
Project 2: Document Analysis and Summarization Agent
- Extracting key data and generating summaries from PDFs and text files
- Utilizing LangChain for efficient document ingestion and retrieval
- Producing executive reports from both structured and unstructured content
Project 3: Tool-Using Agent for Workflow Automation
- Connecting external APIs and automating repetitive operational tasks
- Orchestrating multi-step processes via agentic loops
- Creating a compact automation assistant tailored for real business workflows
Project 4: Data Analysis and Insight Generation Agent
- Linking agents to various data sources, including CSV, SQL, or APIs
- Conducting exploratory data analysis with the aid of Python and AI
- Generating visual insights and performance dashboards
Project 5: Multi-Agent Collaboration and Orchestration
- Coordinating multiple agents for effective task delegation
- Implementing a controller–worker architecture
- Deploying and validating a prototype multi-agent system
Conclusion and Future Directions
- Project presentations and constructive peer feedback
- Exploration of optimization techniques and scaling strategies
- Access to resources for continuous learning and experimentation
Requirements
- Intermediate-level proficiency in Python programming
- Fundamental understanding of AI or machine learning concepts
- Experience with APIs and data processing pipelines
Target Audience
- Engineers and developers aiming to create applied AI solutions
- Technical teams seeking to accelerate prototyping in agentic AI
- Practitioners engaged in AI integration and pilot program initiatives
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.
