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Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production

Course created on July 27, 2026Updated on October 5, 2026

On quote$5,775

5 days
Onsite
8 people max.

Request a quote See the program

Ref: SNA412

8 people max.

On quote$5,775

In-company rate: on quotefrom $10,395 for the whole team

On-site and certification exam on quote

5 days

Onsite

Don't let this gap widen

Why this program matters

Without mastering reinforcement learning at scale with Ray RLlib, 70% of industrial projects fail in production, creating critical instabilities and unexpected downtimes.
This costs an average of 250 000 € per failure due to wasted resources and extended debugging time of 3 to 6 months.
Your team and company lose competitiveness to agile competitors, risking eroded market share and missed opportunities in automated optimization.
Every quarter without expertise exposes you to cumulative losses of millions in operational inefficiencies.

Trusted by — schools, companies and industrial groups

25,719 programs · 25 countries

Every program built with a dedicated engineer

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

Learning objectives

Understand the theoretical foundations of reinforcement learning (RL)
Install and configure the Ray and RLlib ecosystem in different environments
Experiment with RLlib's main APIs to train, evaluate, and deploy RL agents
Customize RL environments and models for bespoke use cases
Master scaling and handling large data volumes with Ray
Industrialize your RL pipelines for production

Program

Module 1Fundamentals of Reinforcement Learning and Getting Started with Ray

Review of RL concepts (agents, policies, rewards, environment). Presentation of Ray: architecture, installation, cluster notions and distributed resources. First steps with Ray RLlib. Handling standard environments (OpenAI Gym).

Module 2In-Depth Exploration of RLlib and Agent Training

Exploration of supported algorithms (DQN, PPO, A3C, etc.). Use of RLlib APIs to train agents. Configuration management and hyperparameter search. Visualization and monitoring of experiments with TensorBoard and Ray Tune.

Module 3Customization of Environments and Policies

Creating custom environments. Developing custom policies. Handling advanced models (custom neural networks, multi-agents, hierarchical agents).

Module 4Scalability, Optimization, and Deployment

Parallelization and large-scale distribution strategies. Resource optimization with Ray. Performance issue resolution. Backup/restoration techniques and deploying RL agents in production.

Module 5Industrialization, Practical Cases, and Perspectives

Workshop on a complete application case (industrial simulation, robotics, finance, etc.). Best practices for managing logs, checkpoints, and monitoring in production. Discussion on perspectives and limitations of industrial RL with Ray RLlib.

Evaluation method

Multiple-choice quizzes at the end of each day
Practical hands-on exercise: continuous project
Group debrief on solving a real-world case

Learning method

Structured theoretical lectures
Live demonstrations in a Python notebook
Series of applied exercises after each module
Collaborative work on a team mini-project
Access to a ready-to-use example code repository

Methods, materials and delivery

The Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation 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: Mastering Reinforcement Learning with Ray RLlib: From Initiation 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: Mastering Reinforcement Learning with Ray RLlib: From Initiation 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.

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

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.

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

Frequently asked questions

What can participants do after Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production training?+

They can understand the theoretical foundations of reinforcement learning (RL), install and configure the Ray and RLlib ecosystem in different environments and experiment with RLlib's main APIs to train, evaluate, and deploy RL agents. Those are the stated objectives of the Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production program at Advanced level, checked by the end-of-session assessment.

What does the Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production program cover, day by day?+

Day 1: Fundamentals of Reinforcement Learning and Getting Started with Ray. Day 2: In-Depth Exploration of RLlib and Agent Training. Day 3: Customization of Environments and Policies. Day 4: Scalability, Optimization, and Deployment. Day 5: Industrialization, Practical Cases, and Perspectives. The Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production program runs over 5 days, delivered on site.

How is Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production training assessed?+

Assessment relies on multiple-choice quizzes at the end of each day, practical hands-on exercise: continuous project and group debrief on solving a real-world case. Learni issues a completion certificate together with the individual assessment report at the end of the Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production program, which an L&D team can file as evidence.

How much does Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production training cost per participant?+

Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production training is priced on quote. The amount depends on headcount, format and how far the syllabus is tailored to your team. A detailed quote is sent within one business day, and team pricing covers the whole group from the second participant.

How long does Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production training take?+

5 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 Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production 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 Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production training?+

Intermediate knowledge in Python and machine learning. Basic notions in reinforcement learning recommended.

Is a certificate issued after Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production 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 Training: Mastering Reinforcement Learning with Ray RLlib: From Initiation to Production 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.

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