Our guest today is Noah Gift, MLOps Leader and award winning book author. Noah has over 30 years of experience in the field and has taught to hundreds of thousands of students online.

In our conversation, we first talk about Noah's experience building data pipelines in the movie industry and his experience in the startup world. We then dive into MLOps. Noah highlights the importance of MLOps,  outlines the Software Engineering best practices that Data Scientists must learn and explains why we shouldn't always use Python. Noah finally shares his thoughts on the difference between MLOps and LLMOps, Python vs Rust and the future of the field.

If you enjoyed the episode, please leave a 5 star review and subscribe to the AI Stories Youtube channel.

Link to Train in Data courses (use the code AISTORIES to get a 10% discount): https://www.trainindata.com/courses?affcode=1218302_5n7kraba

Follow Noah on LinkedIn: https://www.linkedin.com/in/noahgift/

Follow Neil on LinkedIn: https://www.linkedin.com/in/leiserneil/  

————
(00:00 ) - Intro

(02:14 ) - Building data pipelines in the film industry

(11:47 ) - Noah's experience in Startups 

(17:57 ) - What is MLOps? 

(20:52 ) - Why should Data Scientists learn Software Engineering?

(27:59 ) - Importance of MLOps

(30:54 ) - Rust vs Python

(43:48 ) - Why we shouldn't always use Python

(49:26 ) - Difference between LLMOps and MLOps

(53:50 ) - Security and ethical concerns with LLMOps

(56:27 ) - The future of the field

(01:08:41 ) - Career advice