Training TensorFlow - Deploying ML Models in the Enterprise

$3,465

  • 3 days
  • Onsite
  • 10 people max.
Ref: XTN195
10 people max.
$3,465
In-company rate: from $6,290 for the whole team
On-site and certification exam on quote
3 days
Onsite

Don't let this gap widen

Why this program matters

  • Companies that ignore TensorFlow lose competitiveness in the AI market.

  • According to recent studies, 67 % of ML projects fail due to insufficient skills in modern frameworks.

  • Professionals without these skills see their careers stagnate amid rising demand.

  • Not taking this training leaves them permanently behind in an expanding sector.

Allan BUSI, Learni trainer · AI expert
Allan BUSI

Learni trainer · AI expert

73%productivity gap
×3cost of inaction
Flag of the United StatesBuilt for US teams
Payment by wire transferEnhanced confidentialityPerfect for companies with 50 to 500 employeesScheduling to fit any time zone

Trusted by — schools, companies and industrial groups

41,183 programs · 25 countries

  • Aptar
  • ArcelorMittal
  • Equans
  • EDF
  • Ubisoft
  • Microsoft
  • Atos

Every program built with a dedicated engineer

  • OpenAI
  • Anthropic
  • Mistral AI
  • NVIDIA
  • Google
  • Amazon Web Services
  • Microsoft Dynamics 365
  • Salesforce
  • ServiceNow
  • SAP
  • Oracle
  • Cisco
  • Fortinet
  • Palo Alto Networks
  • Aruba
  • VMware
  • Red Hat
  • Databricks
  • Snowflake
  • OVHcloud
  • Notion
  • AMD
  • Apple

Companies: Aptar, ArcelorMittal, Equans, EDF, Ubisoft, Microsoft and Atos.

TensorFlow training objectives

  • Master the basics of TensorFlow for professional projects
  • Develop solid skills in creating ML models
  • Design pipelines tailored to business needs
  • Implement certified machine learning solutions
  • Optimize model performance in a real-world context
  • Configure TensorFlow environments for production

Program

TensorFlow curriculum: 3 modules over 3 days

Module 1 : Theme: Discovering TensorFlow (Colab environment, tensors, first models)

This day allows participants to get started with TensorFlow in a professional setting. Learners explore the Colab environment, manipulate tensors, and build a first simple model. Practical exercises on real datasets reinforce the acquired knowledge. The trainer guides each step to ensure smooth and level-appropriate progression.

Module 2 : Theme: Advanced Modeling with TensorFlow (neural networks, training, evaluation)

Participants deepen their understanding of building neural networks with TensorFlow. They train models on real business cases and evaluate performance. Optimization methods are applied directly in the workshops. This session combines theory and practice to consolidate machine learning skills.

Module 3 : Theme: MLOps and TensorFlow Deployment (serving, monitoring, continuous integration)

The final day covers MLOps practices with TensorFlow. Learners deploy models to production, configure monitoring, and briefly compare with PyTorch. Concrete deliverables such as a complete pipeline are created. Emphasis is placed on enterprise application and certification of acquired skills.

How TensorFlow skills are assessed

  • Interactive quizzes after each module
  • Final group project with presentation
  • Certificate of competencies issued at the end of the training

How the TensorFlow course is taught

  • Practical workshops on Colab
  • Real business case studies
  • Personalized feedback from the trainer
  • Online resources for review

TensorFlow training: access and practical arrangements

The Training TensorFlow - Deploying ML Models in the Enterprise 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 TensorFlow - Deploying ML Models 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 TensorFlow - Deploying ML Models 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

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 TensorFlow 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.

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.

A child walking to school with a backpack
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
Enroll and offer a kit
FAQ

TensorFlow: frequently asked questions

Which tools are used in TensorFlow training?+
Hands-on work runs on colab environment, tensors, first models, neural networks, training and evaluation. Those tools come from the TensorFlow program itself, delivered on site over 3 days, so participants practise on the stack they will use at work.
What can participants do after TensorFlow training?+
They can master the basics of TensorFlow for professional projects, develop solid skills in creating ML models and design pipelines tailored to business needs. Those are the stated objectives of the TensorFlow program at Beginner level, checked by the end-of-session assessment.
What does the TensorFlow program cover, day by day?+
Day 1: Theme: Discovering TensorFlow (Colab environment, tensors, first models). Day 2: Theme: Advanced Modeling with TensorFlow (neural networks, training, evaluation). Day 3: Theme: MLOps and TensorFlow Deployment (serving, monitoring, continuous integration). The TensorFlow program runs over 3 days, delivered on site.
How is TensorFlow training assessed?+
Assessment relies on interactive quizzes after each module, final group project with presentation and certificate of competencies issued at the end of the training. Learni issues a completion certificate together with the individual assessment report at the end of the TensorFlow program, which an L&D team can file as evidence.
How much does TensorFlow training cost per participant?+
TensorFlow training costs $3,465 per participant. For an in-company team, the flat rate starts at $6,290 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 TensorFlow training take?+
3 days, 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 TensorFlow 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 TensorFlow training?+
Basic knowledge of Python and simple statistical concepts.
Is a certificate issued after TensorFlow 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 TensorFlow 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 TensorFlow learning path.

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