AI & Data

Training: MLflow

The MLflow training is an intensive two-day course focusing on the practical application of MLflow for managing the machine learning lifecycle.

Duration
6h
Ask about the program → See all
Who it's for

Ideal for teams that…

1 Data scientists and data engineers who want to expand their skills in ML lifecycle management
2 IT specialists looking to use MLflow to automate ML processes in their organizations
3 ML engineers and developers aiming to deploy and monitor ML models in production
Outcomes after the program

Hands-on AI and data analytics workshops — built around your team's real cases.

✓

How to configure and manage MLflow for tracking ML experiments

✓

How to monitor and update deployed ML models

✓

How to register, store, and deploy ML models using MLflow

✓

How to integrate MLflow with popular ML frameworks and cloud platforms

Program · 2 modules

What we actually do

M01
Day 1: Introduction to MLflow and Model Management Basics
  • · MLflow fundamentals
  • · Introduction to MLflow and its architecture
  • · Installation and configuration of MLflow
  • · Tracking ML experiments with MLflow Tracking
  • · Recording and managing ML experiment metadata and results
  • · Model management and storage
  • · Registering models with MLflow Models
  • · Storing models in the MLflow Model Registry
  • · Hands-on practice: registering and tracking ML experiments
  • · Analysis and interpretation of experiment results
M02
Day 2: Advanced Techniques and Practical Applications
  • · Model deployment with MLflow Projects
  • · Creating and configuring MLflow projects
  • · Deploying models across different platforms
  • · Monitoring with MLflow Models
  • · Tracking and optimizing deployed models
  • · Integration with tools and services
  • · Integrating MLflow with popular ML frameworks (TensorFlow, PyTorch, Scikit-learn)
  • · Integrating MLflow with cloud platforms (AWS, Azure, GCP)
  • · Hands-on practice: deploying and monitoring models with MLflow
  • · Optimizing and maintaining deployed ML models
Every module is adapted to your stack and context. The above is a starting point — not a fixed agenda.
How we work

From brief to retro in 30 days.

01

Brief & diagnosis

A call with the team lead + a short survey for participants. We define goals, gap and context.

02

Program customization

We adapt modules, case studies and code examples to your stack. Approval in 5 days.

03

Workshop

Trainer-led sessions, hands-on, code review. Mentor available between sessions too.

04

Retro + report

Outcome report for the team and lead. 30 days of consulting included.

Inquiry

Send a brief. We'll reply within 1 day.

After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.

✓Quote within 48h of the brief
✓First session within 30 days
✓Pilot before the full decision
✓VAT invoice, payment in instalments possible

Ochrona antyspamowa (Cloudflare Turnstile) zostanie aktywowana po wpięciu klucza.

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