🎁Azure · AWS · Google — 1 free certification per learner, up to $400.Get the offer →
← Back

Training MLflow - Manage your ML experiments effectively

Ref: IWL707
10 people max.
5250 € HT / per person
−15% from 2 people−30% from 3 people−50% from 5 people
Pay in 3 installments · +$170/day onsite · +$500 with certification exam
5 journées
distanciel

Share in 2 clicks

EquansAptarArcelorMittalUbisoftINSEECLa PlateformeCESIEFREIEPSIINGETISMy Digital SchoolYnovEquansAptarArcelorMittalUbisoftINSEECLa PlateformeCESIEFREIEPSIINGETISMy Digital SchoolYnov

Learning objectives

  • Install and configure MLflow in a local environment
  • Create and organize ML tracking experiments
  • Log parameters, metrics, and artifacts automatically
  • Use the UI interface to visualize and compare runs
  • Deploy ML models with MLflow Model Registry
  • Integrate MLflow into an end-to-end workflow
  • Apply best practices for reproducible projects

The Learni story

Founded by passionate learning and innovation experts, Learni's mission is to make professional training accessible to everyone, anywhere in the world. Our team operates in major hubs — London, New York, Boston — and internationally, to support talents and organizations in upskilling.

Don't let this gap widen

Why this program matters

  • Without MLflow, 70% of ML projects fail due to lack of reproducibility, wasting up to 40% of time recreating environments and endless debugging.

  • Imagine losing weeks tracking why a model worked yesterday but not today, or manually comparing hundreds of runs in chaotic notebooks.

  • Data scientists lose 25 hours per week on manual tracking, according to Gartner, leading to project delays and exploding budgets.

  • With this training, avoid these pitfalls: track everything automatically, deploy without risk, and boost ML ROI by 300%.

  • Don't let your experiments evaporate anymore.

Allan Busi
Allan Busi

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Introduction to MLflow: installation and first runs (CLI tools, UI Tracking Server)

Discover MLflow by installing the tool via pip, configure your first local tracking server, run simple Python scripts to log basic parameters, perform practical exercises on Iris datasets, visualize your runs in the intuitive UI, and produce your first automated reports that transform your trials into actionable insights.

Module 2Advanced Tracking: logging metrics and artifacts (MLflow Tracking API, autologging)

Dive into logging with the MLflow API, record precise metrics like accuracy and loss on Scikit-learn models, upload artifacts like graphs and CSV files, enable autologging for TensorFlow, perform collaborative exercises on real classification cases, and generate dynamic dashboards that accelerate your iterations.

Module 3Visualization and Comparison: MLflow UI and Experiments (run search, sorting)

Master the MLflow UI to navigate experiments, compare parallel runs via interactive graphs, filter by key metrics on real projects like churn prediction, perform advanced search exercises, export visualizations as PNG, and learn to identify the best models in a few clicks to boost your productivity.

Module 4Model Management: MLflow Models and Registry (packaging, staging)

Move to model management by packaging your trainings with mlflow.pyfunc, register them in the Model Registry, test staging and production via REST API, deploy on concrete regression cases, perform A/B testing exercises, and validate deployable deliverables that secure your ML pipelines in the enterprise.

Module 5Integrated Projects and Best Practices: end-to-end workflows (Git integration, CI/CD)

Synthesize in a complete project a reproducible ML pipeline with MLflow, integrate Git for versioning, simulate CI/CD with Docker, optimize via best practices like nested runs, collaborate in a team on a real business case, produce a personal portfolio, and leave with ready-to-scale templates for your future ML projects.

Evaluation method

  • Continuous formative evaluation through practical exercises
  • MCQ at the end of the module
  • Final project with oral presentation
  • Internal MLflow certification quiz

Learning method

  • 30% theory, 70% hands-on alternation
  • Individual and pair exercises
  • Real business case studies
  • Post-training video support

Methods, materials and delivery

The Training MLflow - Manage your ML experiments effectively program is delivered onsite or remote (blended-learning, e-learning, virtual classroom, remote presence). At Learni, an industry-certified training organization, every program is built to maximize skills acquisition regardless of the chosen format.

The trainer alternates between demonstrative, interrogative and active methods (through hands-on labs and/or scenarios). This pedagogical approach guarantees concrete learning that's immediately applicable at work.

Equipment required

For the smooth delivery of the Training MLflow - Manage your ML experiments effectively program, the following equipment is required:

  • Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, projector or interactive touch screen (for remote sessions)
  • Training environments installed on workstations or accessible online
  • Course materials, hands-on exercises and complementary resources
  • Post-training access to materials and educational resources

For intra-company training on a site outside Learni, the client commits to providing all required teaching materials (computers, internet, etc.) for the smooth delivery of the program in line with the prerequisites in the communicated program.

* contact us for remote delivery feasibility** ratio varies depending on the program

Skills assessment methods

Assessment of skills acquired during the Training MLflow - Manage your ML experiments effectively program is performed through:

  • During training: case studies, hands-on labs and professional scenarios
  • End of training: self-assessment questionnaire and skills evaluation by the trainer
  • After training: completion certificate detailing acquired skills

Program accessibility

Learni is committed to making its programs accessible. All our programs are accessible to people with disabilities. Our teams are available to adapt the pedagogical methods to your specific needs. Please contact us for any adjustment request.

Enrollment terms and lead times

Learni programs are available inter-company and intra-company, onsite or remote. Enrollments are possible up to 48 business hours before the program starts. Our programs are eligible for corporate funding paths. Contact us to discuss your training project and funding options.

Verified reviews

What our learners

4.9 · +100 verified reviews
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
★★★★★

« cool, j'ai appris des trucs »

TomFormation AWS — Cloud Practitioner
★★★★★

« j'etais perdu au debut mais Ramy Saharaoui m'a pas laché, il a pris le temps. merci vraiment »

Eva CarpentierFormation LLM en Entreprise — Claude, ChatGPT, Mistral
★★★★★

« la formation dev etait intense mais grave bien. merci Anthony Khelil »

NolanDWWM - Développeur Web et Web Mobile
★★★★★

« 😊👍 »

AmbreDWWM - Développement Web & Mobile React
★★★★★

« bien 👍 »

Léo BlanchardFormation AWS — DevOps Engineer Professional
★★★★★

« Allan Busi t'es au top, continue comme ça. formation géniale »

MargotFormation Claude & ChatGPT — Comparatif et Cas d'Usage
Read all reviews
Our method

Training quality, guaranteed at every step

Before, during, after: we frame the brief, introduce the trainer, tailor the content and measure impact. You stay in control from kickoff to wrap-up.

Step 1

Rigorous trainer selection

Each trainer is validated on three criteria: hands-on field expertise, proven pedagogy and alignment with your industry.

  • Triple validation: technical, pedagogical, sectoral.
  • Minimum rating 4.8/5 over the last 12 sessions.
Step 2

You meet the trainer beforehand

30-minute video call between you and the selected trainer to validate the fit, adjust content and clear any final doubts.

  • Live briefing on goals and team context.
  • Veto right — we swap the trainer for free if needed.
Step 3

Content tailored to your context

No recycled slides. The syllabus is reworked from your real cases: tools, constraints, vocabulary, ongoing projects.

  • Hands-on cases drawn from your stack and projects.
  • Program co-written then validated by your team.
Step 4

Continuous quality follow-up

Live evaluations, 30/90/180-day check-ins and a consolidation plan. If the impact misses the mark, we rework it.

  • NPS, knowledge quizzes and skills self-assessment.
  • Satisfaction guarantee: fully satisfied or free rework.

A simple promise: you don't pay to discover the trainer on day one. Everything is validated upfront, by you.

Your professional training, anywhere

Let's build
your next
program.

30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.

Reply within 24 h · Industry-certified · Corporate funding
WhatsApp