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Training MLflow - Mastering ML Tracking in the Enterprise

Ref: AQB617
10 people max.
5500€ 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

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Learning objectives

  • Master MLflow for tracking experiments in certified professional training
  • Develop reproducible ML pipelines tailored to business needs
  • Implement model packaging and deployment with advanced skills
  • Optimize hyperparameters via MLflow to boost performance
  • Set up collaborative environments for international teams
  • Acquire certified MLOps skills for international trade

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 this upskilling, your team accumulates a technological gap that translates directly into productivity loss.

  • Organizations that don't train their talents on key topics see their competitiveness drop.

  • Every quarter without training is a gap widening with competitors who invest.

  • The cost of inaction quickly exceeds that of well-targeted training.

Fouzi Benzidane
Fouzi Benzidane

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1MLflow: Installation and Experiment Tracking (Python Tools, MLflow UI)

Discover the quick installation of MLflow locally and in the cloud, configure your first environment with pip and conda, launch simple ML experiments on import-export datasets, log metrics, parameters, and artifacts using mlflow.log_metric and mlflow.log_param, explore the UI interface to visualize runs and compare performances, perform practical exercises on logistic regression applied to commercial flows, produce your first automated reports for international teams.

Module 2MLflow: Advanced Experiment and Project Management (MLflow Projects, Git Integrations)

Dive into MLflow Projects to encapsulate environments and dependencies, structure your ML scripts with MLproject.yaml, integrate Git for automatic versioning of code and customs data, execute remote runs via backend tracking server, analyze artifacts like trained models on Incoterms predictions, collaborate in real-time with multinational teams, generate comparative dashboards, apply to concrete cases of international logistics optimization, deliver reusable templates for your company.

Module 3MLflow: Models and Registry (MLflow Models, Model Registry)

Learn to package ML models in MLflow format via mlflow.pyfunc and save_model, test inferences on international trade data, deploy in Model Registry for staging and production, manage versions and aliases for smooth transitions, integrate with Docker and Kubernetes for scalability, evaluate models on custom customs metrics, perform A/B testing exercises on export predictions, secure registry access for global teams, produce deployable deliverables ready for certified enterprise deployment.

Module 4MLflow: Hyperparameter Tuning (Hyperopt Integrations, Optuna)

Optimize hyperparameters with MLflow and Hyperopt, launch automated sweeps on grids and Bayesian methods applied to Incoterms datasets, track all trials in parallel, visualize performance surfaces in the UI, integrate Optuna for advanced tuning on clusters, analyze best models for import-export forecasts, apply to real international supply chain cases, generate automated reports with best configurations, prepare end-to-end pipelines for production, strengthen professional skills in collaborative MLOps.

Module 5MLflow: Deployment and MLOps in Production (Serving, CI/CD with MLflow)

Master mlflow models serve for fast REST APIs, deploy on AWS SageMaker or Azure ML with integrated tracking, configure CI/CD pipelines with GitHub Actions for automations, monitor models in production via custom metrics on commercial flows, manage automatic retraining on new customs data, integrate Prometheus monitoring, test robustness on import-export failure scenarios, finalize with a personal capstone project, obtain MLOps skills certification, receive post-training kit for the company.

Evaluation method

  • Daily interactive quiz on MLflow concepts
  • Final project: Complete ML tracking pipeline applied to trade
  • Practical evaluation by Qualiopi-certified trainer

Learning method

  • Active methods with 70% hands-on practice on real cases
  • Small groups for personalized support
  • Video resources and documentation post-training
  • Qualiopi certification validating MLOps skills

Methods, materials and delivery

The Training MLflow - Mastering ML Tracking in the Enterprise 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 - Mastering ML Tracking in the Enterprise 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 - Mastering ML Tracking in the Enterprise 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.

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