https://github.com/rogaha/applied-ai
https://github.com/rogaha/applied-ai
Last synced: 7 months ago
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- Host: GitHub
- URL: https://github.com/rogaha/applied-ai
- Owner: rogaha
- Created: 2025-03-07T22:30:15.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-15T01:07:12.000Z (about 1 year ago)
- Last Synced: 2025-04-11T16:28:20.455Z (about 1 year ago)
- Size: 16.6 KB
- Stars: 0
- Watchers: 1
- Forks: 5
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# **Final Project Class Structure & Assignments**
## **📚 Course Overview**
Students will build an AI chatbot integrating **WhatsApp, N8N, OpenAI, Supabase, and RAG**, culminating in a **live demo presentation**. Each class includes **theory, hands-on practice, and assignments**.
---
## **📊 Evaluation & Grading Rubric**
The final project is graded on **100 points**, distributed as follows:
| **Stage** | **Task** | **Points** | **Grading Criteria** |
|------------|--------------------------------------------------|------------|-----------------------------------------|
| **Class 1** | Define chatbot scope & set up infrastructure | **10 pts** | Clear definition, proper setup of N8N & Supabase |
| **Class 2** | Connect WhatsApp API & process messages | **15 pts** | Successful message reception & logging in Supabase |
| **Class 3** | Integrate OpenAI (GPT-4) for chatbot responses | **15 pts** | AI-generated responses with well-structured prompts |
| **Class 4** | Implement Retrieval-Augmented Generation (RAG) | **15 pts** | Proper knowledge base integration & query retrieval |
| **Class 5** | Store chat history & analyze conversations | **15 pts** | Well-structured Supabase storage & insightful analytics |
| **Class 6** | Automate workflows using N8N | **15 pts** | Successful chatbot automation & scheduled tasks |
| **Class 7** | Deploy & fine-tune chatbot | **15 pts** | Optimized chatbot performance & deployment setup |
| **Class 8** | Live demo & final presentation | **10 pts** | Clear explanation, working chatbot, innovation |
✔ **Late submissions:** -2 points per day delay.
✔ **Extra credit:** Up to +5 pts for outstanding creativity or business impact.
---
## **🗓 Course Schedule & Assignments**
Each class is **2 hours long**, blending **theory and hands-on activities**.
### **🔹 Class 1: Defining the Chatbot Scope & Setting Up** (10 pts)
🎯 **Objective:** Understand chatbot fundamentals & set up the project.
🛠 **Hands-On:**
- Define chatbot purpose, audience & workflows.
- Set up N8N, Supabase & obtain WhatsApp API credentials.
📌 **Assignment:**
- Write a **Chatbot Project Summary** (business goal, features, users).
- Install & configure **N8N and Supabase**.
---
### **🔹 Class 2: Connecting WhatsApp API & Processing Messages** (15 pts)
🎯 **Objective:** Integrate WhatsApp API with N8N to receive messages.
🛠 **Hands-On:**
- Set up **WhatsApp API** & test message reception.
- Create an **N8N workflow** for WhatsApp message logging.
📌 **Assignment:**
- Ensure **WhatsApp API is fully configured**.
- Build an **N8N workflow to log messages** in Supabase.
---
### **🔹 Class 3: Integrating OpenAI for AI-Powered Responses** (15 pts)
🎯 **Objective:** Use OpenAI (GPT-4) for chatbot responses.
🛠 **Hands-On:**
- Set up **OpenAI API** & integrate it into N8N.
- Experiment with **prompt engineering** to refine responses.
📌 **Assignment:**
- Test different **prompt styles** to enhance chatbot responses.
- Store **chat history in Supabase** for personalization.
---
### **🔹 Class 4: Implementing Retrieval-Augmented Generation (RAG)** (15 pts)
🎯 **Objective:** Improve chatbot intelligence using knowledge retrieval.
🛠 **Hands-On:**
- Set up **a vector database** for RAG.
- Implement **document embeddings & query processing**.
📌 **Assignment:**
- Upload sample **knowledge base documents**.
- Test **retrieval accuracy** with sample queries.
---
### **🔹 Class 5: Storing Chat History & Analyzing Conversations** (15 pts)
🎯 **Objective:** Store and analyze chatbot conversations in Supabase.
🛠 **Hands-On:**
- Design **a chat history table** in Supabase.
- Implement **querying & analytics** to improve interactions.
📌 **Assignment:**
- Visualize **chat statistics** (most common queries, response time).
- Generate insights on **how to enhance chatbot interactions**.
---
### **🔹 Class 6: Automating Workflows Using N8N** (15 pts)
🎯 **Objective:** Automate chatbot interactions and tasks.
🛠 **Hands-On:**
- Create **automated chatbot actions** based on user intent.
- Implement **scheduled tasks** (e.g., follow-ups, reminders).
📌 **Assignment:**
- Develop an **automated response flow** for common user interactions.
- Configure **alerts for unanswered queries**.
---
### **🔹 Class 7: Deploying & Fine-Tuning the Chatbot** (15 pts)
🎯 **Objective:** Deploy the chatbot for real-world use & optimize performance.
🛠 **Hands-On:**
- Deploy chatbot for **external testing**.
- Optimize **response speed and database queries**.
📌 **Assignment:**
- Collect **user feedback** & iterate chatbot improvements.
- Ensure chatbot is **ready for final demo**.
---
### **🔹 Class 8: Live Demo & Final Presentation** (10 pts)
🎯 **Objective:** Showcase chatbot functionality & key learnings.
🛠 **Hands-On:**
- Each student/team **presents their chatbot**.
- Showcase **real-time interaction & workflow automation**.
📌 **Final Submission:**
- **Final report** (architecture, features, challenges, improvements).
- **GitHub repository** with chatbot code.
- **Live demo evaluation** based on chatbot functionality & creativity.
---
## **🏆 Final Deliverables**
By the end of the course, students will have a **fully functional AI chatbot** integrated with **WhatsApp, OpenAI, Supabase, and N8N**, capable of retrieving information via **RAG**, storing conversations, and automating interactions.
Each student/team will **pitch their chatbot** and demonstrate it working **live**.
✔ **Bonus:** Up to +5 pts for **exceptional performance, innovation, or UX design**.