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.
Training MLflow - Master ML Project Management
Trusted by — schools, companies and industrial groups
25,807 programs · 25 countries
Every program built with a dedicated engineer
Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft and Microsoft.
MLflow training objectives
- Set up an MLflow server to track experiments
- Log and compare ML experiment runs
- Version and manage models with MLflow Model Registry
- Deploy models in local or cloud serving
- Integrate MLflow into existing CI/CD pipelines
- Analyze performance via UI and automated metrics
MLflow curriculum: 1 module over 1 day
Module 1 : MLflow: Tracking, Models, and Deployment (tools, exercises, ML deliverables)
Install MLflow, launch a tracking server, track experiments with Scikit-learn and TensorFlow on concrete classification cases, compare hyperparameters via the interactive UI, register versioned models in the registry, deploy in REST serving, integrate with a GitHub Actions pipeline, produce a results dashboard and a ready-to-use deployed model, transform your ML workflows into reproducible successes.
How MLflow skills are assessed
- Interactive quizzes, practical exercises, final project with personalized feedback
How the MLflow course is taught
- 80% hands-on with real cases, 20% applied theory
MLflow training: access and practical arrangements
The Training MLflow - Master ML Project Management program is delivered onsite or remote (blended-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 - Master ML Project Management 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 - Master ML Project Management 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
Registration is possible up to 48 business hours before the start of training. All our programs are built for corporate L&D budgets and delivered onsite or remotely.
The Learni story
Founded by engineers and learning experts, Learni's mission is to make high-impact tech training accessible to teams everywhere. We work remotely with organizations across the US and Canada, in your time zone, to help teams upskill fast.
Our method
How Learni guarantees the quality of your MLflow training
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.
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.
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.
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.
Our social commitment
A school kit donated to a child for every training booked
To fight inequalities in access to education, Learni donates a complete school kit to a child in need for every training booked. You build your skills, a child heads back to school.
- Backpack, notebooks and essential supplies
- Distributed through our partner charities
- Included, at no extra cost to you
FAQ
MLflow: frequently asked questions
Which tools are used in MLflow training?+
Hands-on work runs on tools, exercises and ML deliverables. Those tools come from the MLflow program itself, delivered on site over 1 day, so participants practise on the stack they will use at work.
What can participants do after MLflow training?+
They can set up an MLflow server to track experiments, log and compare ML experiment runs and version and manage models with MLflow Model Registry. Those are the stated objectives of the MLflow program at Intermediate level, checked by the end-of-session assessment.
How is MLflow training assessed?+
Assessment relies on interactive quizzes, practical exercises, final project with personalized feedback. Learni issues a completion certificate together with the individual assessment report at the end of the MLflow program, which an L&D team can file as evidence.
How much does MLflow training cost per participant?+
MLflow training costs $1,155 per participant. For an in-company team, the flat rate starts at $2,195 for the whole group, up to 8 people. The detailed quote, sent within one business day, adjusts the amount to the format and how far the syllabus is tailored to your team.
How long does MLflow training take?+
1 day, available live online (US time zones) or on-site at your offices. Half-day tracks spread over several weeks are possible so the team stays operational.
Who pays for MLflow training?+
Most US teams pay directly through their company L&D or training budget. Learni invoices in US dollars and accepts bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
What do participants need to know before MLflow training?+
Mastery of Python, basics in Machine Learning (Scikit-learn, TensorFlow), Git usage.
Is a certificate issued after MLflow training?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report. Learni is a certified training provider and prepares for third-party certifications, but does not award them itself.
Does Learni provide the equipment for MLflow training?+
No. A computer and a stable internet connection are required for each participant. Learni provides the learning platform, the trainer and all course materials.
Your professional training, anywhere
Let's build your MLflow learning path.
30 minutes with a learning advisor. No commitment. No sales pitch dressed up as a demo.
Reply within 24h · Vetted experts · USD invoicing · W-9 available
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On-site & remote
MLflow training in your city
Available on-site and remotely. Pick your city to see the local training center.