Training Format
- Live sessions
- Hands-on activities
- Weekly AI challenges
- Mini projects
- Final capstone project
Course Curriculum
Module 1: Introduction to AI & Modern Workplace Productivity
Session 1What is AI; ML vs Deep Learning vs Generative AI; understanding LLMs; AI capabilities, limitations, myths vs reality; responsible AI usage; choosing the right AI tool; the AI application lifecycle. Hands-on with ChatGPT and Google AI Studio.
Module 2: Prompt Engineering & AI Communication
Session 2Anatomy of an effective prompt; context, role, task, output; zero-shot, one-shot, few-shot; chain-of-thought; persona prompting; prompt templates; structured outputs (tables, JSON, reports); prompt optimization.
Module 3: AI for Everyday Work & Productivity
Session 3AI-powered workplace productivity; research with AI; document summarization; presentation generation; AI for Excel and data analysis; AI for communication and collaboration; best practices. Tools: ChatGPT, Google AI Studio.
Module 4: Python, APIs & GitHub Essentials
Sessions 4–5Python fundamentals (variables, conditionals, loops, functions, files); API fundamentals (REST, HTTP, JSON, authentication, API keys, calling LLM APIs); Git & GitHub (repositories, commits, branches, README, documentation, open-source best practices).
Module 5: Building AI Applications
Sessions 6–7Components of AI applications; input/output handling; prompt engineering within applications; structured responses; error handling; introduction to AI agents; connecting AI with external services. No-code platform: n8n. Build a chatbot, email assistant, FAQ assistant, meeting notes generator and content generator.
Module 6: Retrieval-Augmented Generation (RAG)
Sessions 8–9Why LLMs hallucinate; introduction to RAG; RAG architecture; embeddings; chunking strategies; vector databases (conceptual); similarity search; context retrieval; source grounding and citations; improving response accuracy.
Module 7: AI Evaluation, Testing & Responsible AI
Session 10Why AI applications need evaluation; functional testing; prompt testing; hallucination detection; response quality metrics; human evaluation; AI benchmarking; responsible AI; privacy and security; ethical AI usage; AI governance basics.
Module 8: Deployment, Monitoring & Cost Awareness
Session 11Preparing AI applications for production; FastAPI basics; Streamlit basics; deploying AI applications; hosting options; monitoring AI systems; logging and debugging; API usage monitoring; token management; cost estimation and optimization; scaling.
Module 9: Capstone Project & Future of AI
Session 12Future trends: AI agents, multimodal AI, voice AI, AI in software development, AI in business automation, emerging tools, and career pathways in AI. Participants design, build, test, deploy, and document a complete AI solution for a real-world business problem.
Capstone Requirements
- Define a real business use case
- Design the solution architecture
- Build the application using Python
- Integrate an LLM API
- Use n8n where appropriate
- Implement RAG for document-based use cases
- Evaluate AI responses
- Deploy the application
- Publish the project on GitHub
- Write professional documentation
- Present the solution
Weekly AI Challenges
- Week 1: Create an AI assistant that helps with your daily work.
- Week 2: Design reusable prompts for your profession.
- Week 3: Use AI to automate a repetitive workplace task.
- Week 4: Build a Python application that integrates an AI API and publish it on GitHub.
- Week 5: Create an AI assistant using n8n and develop a document-based chatbot using RAG.
- Week 6 (Capstone Project): Evaluate and improve your AI application's performance and reliability, deploy the application while optimizing operating costs, and present your completed capstone project with:
- Live demo
- GitHub repository
- Documentation
- Deployment link
- Evaluation results
- Lessons learned
Tools Used Throughout the Course
AI Platforms
No-Code Automation
Programming & Development
Suggested Capstone Projects
Ready to build with AI?
Talk to an advisor about the next cohort and enrollment details.