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Advanced TensorFlow Training - Optimize Deep Learning Models

Ref: UJP420
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

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Learning objectives

  • Optimize model performance with pruning and quantization
  • Implement advanced architectures like GANs and Transformers
  • Manage massive datasets via tf.data and Distributed Training
  • Deploy TensorFlow applications in production with TensorFlow Serving
  • Create end-to-end pipelines with TensorFlow Extended (TFX)
  • Master debugging and profiling for complex models
  • Produce enterprise-deployable deliverables

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 advanced TensorFlow mastery, your models consume 40% more resources, leading to explosive cloud costs up to 10k€/year wasted.

  • Project timelines double due to endless debugging, 70% deployment failures from missing optimizations.

  • Competitors outperform with 5x faster inferences, losing 25% market share.

  • Avoid skill obsolescence, basic trainings outdated against edge AI.

  • Invest 35h for 10x ROI in productivity, deploy scalable AI next week.

Allan Busi
Allan Busi

Learni Trainer · Expert

73%productivity gap
×3cost of inaction

Program

Module 1Model Optimization: Pruning, Quantization and TensorRT with TensorFlow

Dive into accelerating your TensorFlow models, practice pruning on real CNNs to reduce size by 50%, implement 8-bit quantization with hands-on exercises, test TensorRT on GPU for 10x inference gains, generate performance profiles, leave with production-ready optimized models, boost your AI projects starting tomorrow.

Module 2Advanced Architectures: GANs, RNNs and Transformers in TensorFlow

Build GANs for realistic image generation, code RNNs/LSTMs for time series with Kaggle dataset exercises, master Transformers for NLP via Hugging Face and TensorFlow, apply to real cases like machine translation, debug complex architectures, produce functional prototypes, transform ideas into innovative solutions.

Module 3Data Management: tf.data, Augmentation and Distributed Training in TensorFlow

Master massive data pipelines with tf.data to load terabytes in seconds, practice advanced image augmentation via tf.image, configure multi-GPU and TPU for distributed training, test on ImageNet benchmarks, optimize throughput x5, create reusable scripts, save hours on preprocessing and scale your trainings.

Module 4Production Deployment: TensorFlow Serving, Lite and Edge with TFLite

Deploy scalable models via TensorFlow Serving on Kubernetes, convert to TFLite for mobile/edge with Android/iOS exercises, integrate ONNX for interoperability, measure latency in real production, manage versioning and A/B testing, produce deployable REST APIs, go from prototype to reliable service in the blink of an eye.

Module 5Complete Pipelines and Projects: TFX, Profiling and TensorFlow Best Practices

Build end-to-end MLOps pipelines with TensorFlow Extended, profile with TensorBoard for bottlenecks, apply best practices on personalized capstone project, integrate monitoring and CI/CD, present enterprise-ready deliverables, consolidate skills via expert Q&A, leave certified with impactful portfolio to boost career.

Evaluation method

  • Daily practical quizzes on exercises
  • Graded final project in pairs
  • Continuous evaluation via TensorBoard

Learning method

  • 70% hands-on practice on real cases
  • 30% applied theory
  • Jupyter notebooks provided

Methods, materials and delivery

The Advanced TensorFlow Training - Optimize Deep Learning Models 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 Advanced TensorFlow Training - Optimize Deep Learning Models 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 Advanced TensorFlow Training - Optimize Deep Learning Models 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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