Today I want to share with you 3 skills that will help you differentiate yourself in the job market, and help you land an ML job.
Let’s get to it!
1. Building Real-time LLM apps
Companies do not store data in static CSV files, but dynamic sources, like databases, or even better, Feature Stores.
This is why, LangChain demos inside Jupyter notebooks are very cool, but have 0 business value until you “plug” them to live data sources.
So, if you go beyond demos and build real-time LLMs apps, you will stand out from the crowd.
Hands-on tutorial 👩💻
In this hands-on tutorial with full source code you will learn to build a scalable real-time LLM app using an open-source library called Pathway.
2. Automatic testing of LLMs
Large Language Models are bound to make mistakes, like
hallucinations
misinformation, or
disclosures of sensitive information
These mistakes are no big deal when you are building a demo. However, when you build a real-world LLM app, that real customers interact with, these same mistakes become a deal breaker ❗
If you learn to build automatic testing workflows for LLM apps, you will stand out from the crowd.
Hands-on tutorial 👩💻
In this hands-on tutorial with full source code you will learn to build an automatic testing workflow of LLM apps, using Continuous Integration best-practices, and an open-source library called Giskard.
3. MLOps system design
Learning how to design MLOps systems is an evergreen 🌱 in the ML job market.
Every company needs to establish a basic ML platform, before ML can have any significant business impact.
So, if you learn how to go beyond ML demos in notebooks and learn to build ML products, you will stand out from the crowd.
The Real-World ML tutorial 🌍👩💻
In the Real-World ML Tutorial you will learn to design, build and automate a batch-scoring system that predicts taxi demand in NYC.Join the Real-World ML Tutorial + Community and get lifetime access to
→ 3 hours of video lectures 🎬
→ Full source code implementation 👨💻
→ Discord community, to connect with me and 100+ students 👨👩👦
Let’s keep on learning together!
Enjoy the weekend,
Pau