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Unlock the potential of Python and Streamlit to create and monetize your own Generative AI Micro-SaaS application. This comprehensive course takes you through the journey of building a fully-functional SaaS application, integrating cutting-edge generative AI components, and deploying it globally with a custom domain. You’ll learn to manage subscriptions using Stripe and MongoDB, and harness the power of cloud platforms like AWS and OpenAI ChatGPT to enhance your application’s capabilities.
Whether you’re a Python developer, an aspiring entrepreneur, or a tech enthusiast eager to explore the realms of AI and cloud computing, this course will equip you with the practical skills and knowledge you need to succeed. You’ll not only build your own project but also understand how to market it effectively using landing pages, email campaigns, and more.
With over 3 hours of video content, interactive coding exercises, and real-world projects, you’ll gain hands-on experience that’s directly transferable to building your own SaaS solutions. Dive into the world of SaaS with us and transform your ideas into reality!!
Course Content Overview:
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Section 1: Course Introduction and Demos
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Introduction to the course and its objectives.
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Course overview and what to expect.
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Advanced project showcase demonstrating the power of Streamlit with AI for SaaS.
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Introduction to the course project: Automated Tenant Management Portal.
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Section 2: Streamlit Basics
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Exploring the reasons behind choosing Streamlit for SaaS applications.
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Setting up your development environment for success.
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Diving into interactivity in Streamlit: Widgets, Layout, Session State.
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Displaying Data: How to effectively use Tables, Charts, and Dynamic Content.
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Building a ChatGPT-like chatbot clone with Streamlit and OpenAI.
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Open-Source LLM integration into your chatbot app w AnyScale or Together AI.
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Section 3: Building a Streamlit Micro-SaaS: The Cookbook
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Walking through app showcases and discussing features.
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Local code and environment setup for efficient development.
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Integrating Stripe for subscription management.
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Setting up a MongoDB user database.
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Email verification with FastAPI and local debugging techniques.
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Deploying to Cloud (choices between Railway or Streamlit Cloud).
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Customizing your Domain Name for a professional touch.
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Section 4: Integrating Multimodal Generative AI in SaaS Applications
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Introduction to Multimodal Generative AI in SaaS.
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Demo of Multimodal AI Features: Photos, Audio, Video.
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Setup for Multimodal AI Development: OpenAI and Replicate.
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Automated Social Media Posts with GPT-4 Vision.
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Generating TikTok Content with GPT-4-V Vision and Audio.
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SEO Optimization with AI-Generated ALT Text.
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Advanced AI Photo Editing Techniques.
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Enhancing Image Quality through AI Upscaling.
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Section 5: Course Project: AI Tenant Management System (Part 1)
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Introduction and preamble to the complex course project.
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In-depth discussion on technologies involved and AWS S3 setup.
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Detailed walkthrough on setting up AWS S3 Secret Keys and additional technology setups.
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Coding the main Tenant Application Portal.
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Deployment strategies and reviews for Railway.
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Section 6: Course Project: AI Tenant Management System (Part 2)
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Introduction to Management Portal and AI document analysis.
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Comprehensive guide on technology setup including Conda, AWS S3, Stripe, OpenAI, MongoDB.
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Detailed explanation of utility methods and S3 Data Manipulation.
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Creation of the EmbedChain Chatbot and analysis of tenant documents using OpenAI API.
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Implementing “Map Reduce”: AI Analysis Summary of Summaries and chatbot interactions.
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Section 7: Bonus: Landing Page Creation, Pain Points, Bootstrapping, Email Marketing
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Introduction to Landing Pages, identifying Pain points, and Bootstrapping strategies.
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Practical guide to creating landing pages with Carrd and Mixo.
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Effective Email Marketing with EmailOctopus..
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Real-world marketing, measuring results, and bootstrapping examples including Reddit campaigns and email strategies.
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Join us on this comprehensive journey to build and scale your very own Generative AI Micro-SaaS App with Python & Streamlit. Take the first step towards becoming a successful SaaS entrepreneur today!
Streamlit Basics and Chatbot Builder BootCamp
Building a Streamlit Micro-SaaS: The Cookbook
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5Why Streamlit?
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6Setting up your development environment
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7Interactivity in Streamlit: Widgets, Layout, Session State
A basic slider widget.
A checkbox in the sidebar that toggles additional content.
A select box dropdown.
A date input widget placed in the sidebar.
A simple multi-page simulation using radio buttons.
Session states
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8Displaying Data: Tables, Charts, and Dynamic Content
Notes & Explanations:
Displaying Tables: st.table() offers a way to display static tables. This is great for showcasing smaller sets of data without needing interactive capabilities.
Displaying DataFrames: st.write(df) or st.dataframe(df) can be used to display data frames in an interactive table format. This widget has capabilities like scrolling, which makes it ideal for larger datasets.
Built-in Line Chart: Streamlit comes with a basic charting capability using functions like st.line_chart(), st.bar_chart(), and st.area_chart().
Custom Visualizations: You can also integrate visualizations from libraries like Matplotlib and Seaborn. This allows for tailored visualizations that can be more intricate or specific than Streamlit's built-in chart capabilities.
Dynamic Content: Streamlit can embed and render various dynamic content types, including:
Markdown: With st.markdown(), you can embed markdown text directly into your Streamlit apps.
Images: st.image() lets you display images from various sources.
Videos: st.video() can be used to embed videos.
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9Building a ChatGPT-like clone with Streamlit and OpenAI
This tutorial showcased a simple yet powerful way to build a ChatGPT-like application using Streamlit and OpenAI's API. The usage of session_state ensures that our chat remains interactive and stateful across reruns, providing a smooth user experience. As you can see, in just a few lines of code, we've built a robust chat interface for users to interact with GPT models.
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10Integrate Open Source Models into your chatbot
Explains how to leverage open source inference platforms as an alternative to OpenAI/ChatGPT. Here we use Together AI and AnyScale.
Multimodal Gen-AI with photos, audio and video with OpenAI and Replicate.com
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11App showcase, demo and features walkthrough
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12Local code and environment setup
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13Stripe integration
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14MongoDB user database setup
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15Email verification server with FastAPI Part 1
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16Email verification local debug with FastAPI Part 2
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17Deploying to Cloud (Railway.io or Streamlit Cloud)
Use Railway.io to deploy your app to cloud
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18Customize your Domain Name!
How to customize your domain and next steps for this course
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19Course Check-in! Midway Point.
Course Project: AI Tenant Management System (Part 1)
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20Introduction to the app/technology we're building
We're building an automated social media post maker for realtors.
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21Full demo of the app we're building
Full walkthrough demo of Real Estate Social Media Automation app.
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22Setting up the development environment
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23Automated Facebook Post with GPT-4 Vision
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24TikTok Video with GPT-4-V Vision and OpenAI Voices Client
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25Optimized SEO ALT Text for Images
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26AI Photo Editing with Replicate.com and instruct-pix2pix
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27AI Photo Upscaling & Contact Us Form
Course Project: AI Tenant Management System (Part 2)
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28Intro and Preamble to Course Project
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29Technologies involved and AWS S3 setup
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30AWS S3 Secret Keys Setup
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31More technology setup: Google Tesseract, Poppler, Conda env
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32Explaining Utility Functions/Method Part 1
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33Explaining Utility Functions/Method (Mongo) Part 2
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34Explaining Utility Functions/Method Part 3
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35Coding the Main Tenant Application Portal
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36Deploy to Railway Part 1 (Review)
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37Deploy to Railway Part 2 (Poppler and Tesseract)
Additional Content: Landing Page Creation, Pain Point Marketing, Bootstrapping
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38Intro to Management Portal and AI document analysis
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39Technology setup: Conda, AWS S3, Stripe, OpenAI, MongoDB
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40Utility methods and S3 Data Manipulation
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41How to create the EmbedChain Chatbot
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42Analyzing Tenant Documents with OpenAI API
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43"Map Reduce": AI Analysis Summary of Summaries
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44Chatbot with Tenants using EmbedChain
How long do I have access to the course materials?
You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don't have an internet connection, some instructors also let their students download course lectures. That's up to the instructor though, so make sure you get on their good side!
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