AI Project Ideas and Tutorials — Key Points

Objective

This summary serves as detailed class notes or a reference guide for learners and developers interested in five hands-on AI projects. Each project is broken down into three levels: beginner (no-code), intermediate (coding), and advanced (full applications).

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Projects Overview

1. Personal Finance AI Chatbot

Level 1: Prompt Engineering (No-code Tools)

• Use platforms like ChatGPT, GPT for All, or open-source models.
• Download bank statements.
• Apply the 5W framework in prompts (Who, What, When, Where, Why).
• Example prompt: “Act as a finance advisor, help me save $200K by end of 2025. Analyze my attached statements.”
• Categorize expenses and identify savings.

Level 2: Intermediate (Coding)

• Use Python, AMA, dashboards (e.g., Plotly).
• Programmatically clean and analyze financial statements.
• Automate data aggregation and dashboard creation.

Level 3: Full Custom Application

• Implement RAG (Retrieval Augmented Generation) with Langchain.
• Build a custom web app using Flask.
• Custom data handling and privacy.

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2. Personal AI Assistant with Video Capabilities

Level 1: Prompt Engineering (No-code)

• Use AI chatbots for interactive assistance (text, audio, images).
• Note: Real-time video input delayed by OpenAI.

Level 2: Process Video & Audio

• Extract audio using Whisper for speech-to-text.
• Convert video into image frames for analysis.
• Combine responses using OpenAI API and text-to-speech modules.

Level 3: Build Web Application

• Use frameworks like Shiny for web app development.
• Deploy assistant that receives video, analyzes it, and interacts via audio/text.
• UI components for user interaction and video upload.

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3. Custom AI Travel Planner

Level 1: Prompt Engineering (No-code)

• Use ChatGPT to act as a travel agent.
• Input preferences, destinations, budget, etc.
• Iteratively refine travel itinerary.

Level 2: Integrate Automation Tools

• Use make.com for no-code workflow automation (calendar, Notion integration).
• Organize itinerary as calendar events with detailed info.

Level 3: Advanced Custom Dashboard

• Use Python, Streamlit, or similar dashboard tools.
• Integrate APIs: Google Maps for route tracking, weather, events, and restaurants.
• Visual display of journey, interactive itinerary planning.

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4. AI Music Composer

Level 1: Use AI Music Platforms (No-code)

• Platforms: Udio, Suno.
• Generate music tracks with custom lyrics, mood, and genre.
• Experiment with different prompts and controls.

Level 2: Automated Playlist Creation

• Use Python and Udio API to collect generated songs.
• Build playlists programmatically.
• Automate song gathering and sharing.

Level 3: Multimedia Playlist App

• Use OpenAI’s Whisper for lyrics-to-text.
• Use GPT-4 to generate image prompts based on mood/lyrics.
• Use DALL-E to create matching visuals.
• Script combines audio and visuals into a full playlist presentation (YouTube-style).

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5. Automated Workbooks for Books

Level 1: Prompt Engineering

• Find PDF or text version of book.
• Feed into LLM, prompt to summarize and extract exercises.
• Assemble workbook (may need to split file due to context limits).

Level 2: No-code/Low-code Web App

• Use Bubble to connect to OpenAI API.
• Auto-generate workbook content, render as web app.
• Drag-and-drop UI, user accounts.

Level 3: Advanced Editable Workbooks

• Use pdf.co API for PDF editing, HTML export, and database integration.
• Allow users to edit, save, and download custom workbooks.

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General Tools & Technologies Mentioned

• No-code/Low-code: make.com, Bubble, GPT for All, Shiny, Streamlit
• Programming Languages: Python
• AI/ML APIs: OpenAI (ChatGPT, Whisper, DALL-E), Udio, Suno
• RAG Tools: Langchain
• Web Frameworks: Flask, Shiny
• PDF Automation: pdf.co
• Automation & Integration: Notion, Google Calendar, Google Maps API

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Learning Approach

• Start with prompt engineering and no-code tools for rapid prototyping.
• Move to code for customization, automation, and advanced features.
• Full-stack application for deployable, user-facing products.
• Consider privacy, UX/UI, and integration with other tools/data.

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Resources & Recommendations

• Leverage AI and automation to boost productivity and personal/professional workflows.
• Check out free AI productivity resources from sponsors (e.g., HubSpot).
• Example use cases: research consolidation, news updates, workflow streamlining.
• Recommended for AI learners, tinkerers, indie hackers, and aspiring tech entrepreneurs.

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Call to Action

• Try building these projects at any desired level.
• Share your GitHub links if you complete a project.
• Suggest or request new project ideas in the community for continuous learning!