Course Outline
Introduction to Agentic AI and Bootcamp Structure
- Overview of agentic AI and the bootcamp framework
- Review of essential tools, frameworks, and dependencies
- Best practices for project setup and team collaboration
Project 1: Intelligent Assistant with Prompt-Oriented Reasoning
- Designing a task-focused conversational agent
- Applying structured prompts for reasoning and decision-making
- Developing and testing in Jupyter Notebook
Project 2: Document Analysis and Summarization Agent
- Extracting and summarising data from PDFs and text files
- Utilising LangChain for document ingestion and retrieval
- Producing executive reports from structured and unstructured content
Project 3: Tool-Using Agent for Workflow Automation
- Integrating external APIs and automating repetitive tasks
- Managing multi-step processes through agentic loops
- Building a small automation assistant for real business workflows
Project 4: Data Analysis and Insight Generation Agent
- Connecting agents to data sources (CSV, SQL, or API)
- Conducting exploratory data analysis with Python and AI assistance
- Creating visual insights and performance dashboards
Project 5: Multi-Agent Collaboration and Orchestration
- Coordinating multiple agents for task delegation
- Designing a controller–worker architecture
- Deploying and testing a prototype multi-agent system
Conclusion and Next Steps
- Project presentations and peer feedback
- Discussion on optimisation and scaling strategies
- Resources for continued learning and experimentation
Requirements
- Intermediate level of Python programming skill
- Fundamental knowledge of AI or machine learning concepts
- Experience with APIs and data processing workflows
Intended Audience
- Engineers and developers focused on building applied AI projects
- Technical teams looking to develop rapid prototyping capabilities 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.
