Udemy - MLflow for MLOps and LLMOps - Master MLflow with Databricks torrent

MLflow for MLOps & LLMOps: Master MLflow with Databricks
https://WebToolTip.com
Published 4/2026

Created by Rahul Jha

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch

Level: Intermediate | Genre: eLearning | Language: English | Duration: 29 Lectures ( 6h 28m ) | Size: 3 GB
Learn MLflow for experiment tracking, model registry, model deployment, prompt management, and Databricks AI Functions
What you'll learn

✓ Understand how MLflow works internally and how it fits into real MLOps workflows for experiment tracking, model lifecycle management, and deployment.

✓ Track machine learning experiments using MLflow by logging parameters, metrics, artifacts, and runs in a structured and reproducible way.

✓ Build and manage ML models using MLflow Model Registry including versioning, lineage tracking, and production model management.

✓ Deploy ML models as REST APIs using MLflow’s built-in model serving capabilities for real-time inference.

✓ Implement LLMOps workflows using MLflow including prompt registry, prompt versioning, evaluation, and prompt management.

✓ Integrate MLflow with Databricks to manage machine learning experiments and production ML pipelines.

✓ Use Databricks AI Functions to perform tasks like sentiment analysis, classification, text extraction, and schema extraction using SQL.

✓ Build an end-to-end ML workflow including experiment tracking, model logging, model registry, and deployment.
Requirements

● Basic understanding of Python programming

● Familiarity with machine learning concepts such as models, datasets, and training

● A computer capable of running Python and Jupyter / VS Code

● A free Databricks account (we will show how to set it up)

● Curiosity to understand how real MLOps and LLMOps systems work in production