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Training App Engine 2026 - Deploying Your ML Models to Production

Ref: IAI746
10 people max.
From $4,620 HT / per person
On-site on request · +$540 with certification exam
4 days
Remote

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Equans
EDF
Ubisoft
Microsoft
Aptar
ArcelorMittal
Equans
EDF
Ubisoft
Microsoft
Aptar
ArcelorMittal
Equans
EDF
Ubisoft
Microsoft
Aptar
ArcelorMittal
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Learning objectives

  • Master the deployment of TensorFlow and PyTorch models on App Engine
  • Develop professional MLOps skills for enterprise projects
  • Design certified training and production pipelines
  • Implement effective scalability and monitoring strategies
  • Optimize costs and performance of your enterprise ML applications
A child walking to school with a backpack
Our social commitment

A school kit donated to a child for every training

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

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.

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.

Allan BUSI
Allan BUSI

Learni trainer · AI expert

73%productivity gap
×3cost of inaction

Program

Module 1Theme: Introduction to App Engine for ML (TensorFlow, PyTorch, initial deployments)

Participants discover Google App Engine through concrete examples of deploying TensorFlow and PyTorch models. They configure their first service, complete hands-on exercises for going live, and deliver a simple ML application. The day alternates short theory sessions with guided workshops to build core MLOps fundamentals.

Module 2Theme: MLOps pipelines and continuous integration on App Engine (CI tools, testing, versioning)

This day focuses on building robust MLOps pipelines. Learners integrate TensorFlow and PyTorch into automated workflows, implement automated testing, and manage model versions. Real business cases enable delivery of a functional pipeline ready for production.

Module 3Theme: Scalability and monitoring of ML models on App Engine (supervision tools, alerts)

Participants learn to scale their ML applications and implement advanced monitoring. They use supervision tools to track TensorFlow and PyTorch model performance, create alerts, and optimize resources. Hands-on exercises result in a complete dashboard delivered by the end of the day.

Module 4Theme: Securing and optimizing MLOps costs on App Engine (best practices, audits)

The final day covers securing deployments and controlling costs. Learners apply MLOps best practices, conduct an audit of their solution, and optimize their App Engine configuration. They deliver a final project integrating TensorFlow, PyTorch, and professional production processes.

Evaluation method

  • Knowledge validation quiz after each day
  • Individual final project with presentation and feedback
  • Professional certified training certificate

Learning method

  • Hands-on workshops on Google Cloud
  • Real-world business case studies
  • Experience sharing and interactive discussions
  • Reusable resources and templates

Methods, materials and delivery

The Training App Engine 2026 - Deploying Your ML Models to Production 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 App Engine 2026 - Deploying Your ML Models to Production 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 App Engine 2026 - Deploying Your ML Models to Production 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.

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.

FAQ

Frequently asked questions

How much does the Training App Engine 2026 - Deploying Your ML Models to Production training cost?+
The individual price is $4,620 (USD). The team / on-site group package is shown on the course page. A detailed quote is sent within one business day.
How long is the Training App Engine 2026 - Deploying Your ML Models to Production training?+
The training lasts 4 journées, available live online (US time zones) or on-site at your offices.
How is this training paid for?+
Most US teams pay directly through their company (L&D or training budget). We invoice in US dollars and accept bank transfer (ACH/wire) or card, with volume pricing for teams. A purchase order is welcome.
Are there any prerequisites?+
Basic knowledge of Python and simple use of notebooks to run code
Is a certificate delivered at the end?+
Yes. A Learni completion certificate is issued, along with the individual evaluation report.
Does Learni provide the equipment?+
No. A computer and stable internet connection are required for the participant. Learni provides the educational platform, the trainer and all course materials.
On-site & remote

This training across cities

Available on-site and remotely. Pick your city to see the local training center.

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