Build a Full-Stack SaaS LLM ChatBot + WebApp In Production

Build & Deploy a Production-Ready SaaS Flask-App + LLM powered chatbot that handles text, audio, images, documents

What you'll learn
- Build complex web applications with Flask, Redis, Celery, PostgreSQL, Docker
- Build Machine Learning APIs with Flask with Large Language Models (LLMs)
- Build LLM powered chatbots that can handle text, images, audio, documents
- Deploy to SaaS apps to production on Railway
- Gain new skills to enhance your career portfolio

Requirements
- A computer running Windows, OSX or Linux with at least 8GB of RAM
- Basic understanding of HTML, CSS and JavaScript
- Basic understanding of Computer Science and AI

Description
Build a Full-Stack SaaS GenAI ChatBot + WebApp In Production

Are you ready to become a highly-paid Machine Learning Engineer in today's AI revolution?

Hi, I'm Dylan P., and as a Lead Machine Learning Engineer with over 5 years of experience at major tech companies, I've watched ML Engineering become the hottest job in tech. Why? Because companies desperately need professionals who can both build AI models AND deploy them to production.

But here's the problem:Most courses either teach you theoretical ML modeling without real-world application, or web development without any ML integration. Neither prepares you for what companies actually need.

That's why I've created this comprehensive course that bridges the gap and teaches you to build production-ready ML applications from start to finish.

What makes this course different?

Unlike tutorials that show you toy examples with disclaimers like "you wouldn't do this in production…" I'll show you the REAL way professionals build and deploy ML systems. The techniques in this course are battle-tested from my years building production ML systems:

Use industry best practices and tools like Docker, Databases, Caching, Distributed Computing, Unit / Integration Testing

System design that allows your app to scale up to thousands of users without breaking

Utilize cutting-edge models from traditional ML to state-of-the-art Transformers and LLMs

Deliver measurable business impact while optimizing cost and performance

"This course provides exactly what I needed - not just theory, but practical implementation that translates directly to my work projects." -James Wong

Here's what you'll learn by taking my course:

Full-Stack Development:Create both the front end and backend with Flask, Docker, Celery & Redis

ML System Design:How to design an AI web app + chatbot that can scale effectively

Large Language Models (LLM):Use various Hugging Face LLMs to handle text, audio, image, documents

Production-Grade APIs:Turn an AI model into high performance APIs with FastAPI

Database Integration:Connect your app with production databases with PostgreSQL

Deployment Mastery:Take your application live using Railway

The best part? By the end of this course, you'll have a complete, impressive project for your portfolio that demonstrates exactly the skills employers are desperately seeking.

Who is this course for?

Software engineers looking to transition into the lucrative field of ML engineering

Data scientists who want to level up by learning deployment and production skills

CS students or mid career switchers who want to build up their portfolio

Freelance Consultants/Entrepreneurs keen in creating their own ML-powered applications or SaaS products

"I was stuck in data science theory for years. After this course, I finally know how to build end-to-end ML systems that actually solve real problems." -Jamus Tsai

Course Structure

Each chapter follows a hands-on approach:

Learn:Clear slides introducing new concepts and technologies

Watch:Video walkthroughs of actual code implementation

Build:Hands-on coding to construct your application

Visualize:See your results in action

Challenge:Chapter exercises to cement your understanding

Invest in Your Future

The skills taught in this course regularly command $120,000-$180,000+ salaries in the industry. As AI continues transforming every sector, these skills will only become more valuable.

Don't waste months piecing together fragmented tutorials or building projects that don't reflect real-world requirements. Join me, and in just a few weeks, you'll have mastered the complete skillset needed to thrive as a modern ML Engineer.

Ready to become the ML Engineer companies are looking to hire?Enroll now and start building your first production-ready GenAI Webapp + Chatbot today!

Who this course is for:
- Software Engineers looking to learn how to build production-ready apps with AI
- Aspiring SaaS Founders who want to build AI-powered web applications
- Freelancers learning to expand their skillset with AI web development
- Tech industry professionals or mid-career switchers looking to upskill themselves
More Info