Course Outline
Introduction to Agentic AI and Bootcamp Structure
- Exploring agentic AI and the bootcamp framework
- Overview of essential tools, frameworks, and dependencies
- Guidelines for efficient project setup and collaboration
Project 1: Intelligent Assistant with Prompt-Driven Reasoning
- Designing a task-focused conversational agent
- Leveraging structured prompts for reasoning and decision processes
- Building and validating in 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
- Producing executive reports from both structured and unstructured content
Project 3: Tool-Using Agent for Workflow Automation
- Integrating external APIs to automate repetitive tasks
- Overseeing multi-step processes via agentic loops
- Constructing a compact automation assistant for actual business workflows
Project 4: Data Analysis and Insight Generation Agent
- Linking agents to data sources such as CSV, SQL, or API
- Conducting exploratory data analysis with Python and AI support
- Generating visual insights and performance dashboards
Project 5: Multi-Agent Collaboration and Orchestration
- Orchestrating multiple agents for task delegation
- Architecting a controller–worker model
- Deploying and evaluating a prototype multi-agent system
Conclusion and Future Steps
- Project presentations and peer reviews
- Exploring optimization and scaling strategies
- Resources for ongoing learning and experimentation
Requirements
- Intermediate-level Python programming skills
- Familiarity with core AI or machine learning concepts
- Experience with APIs and data processing pipelines
Target Audience
- Engineers and developers seeking to develop applied AI solutions
- Technical teams looking to acquire rapid prototyping skills in agentic AI
- Professionals involved in AI integration and pilot project 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.
