Is the training Qualiopi certified?

Yes, Learni is a Qualiopi-certified training organization. This certification guarantees the quality of our courses and enables funding through OPCO and other mechanisms.

How can I fund my training?

Our courses are eligible for OPCO funding. Learni supports you through the funding process. A personalized quote is available upon request.

What are the prerequisites for this training?

The prerequisites for the Tabnine Training - Boosting Code Productivity with AI training are: Mastery of a programming language (JavaScript, Python, Java), advanced use of IDEs like VS Code or IntelliJ. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Tabnine Training - Boosting Code Productivity with AI training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Tabnine Training - Boosting Code Productivity… | Learni

The story of Learni

Founded by passionate advocates of learning and innovation, Learni set out to make professional training accessible to everyone, everywhere in the world. Our team works in the largest cities such as Paris, Lyon, Marseille, and internationally, to support talents and organizations in their skills development.

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Methods, approaches, and teaching resources

The Tabnine Training - Boosting Code Productivity with AI training is delivered in-person or remotely (blended-learning, e-learning, virtual classroom, remote in-person). At Learni, a Qualiopi-certified training organization, each program is designed to maximize skills acquisition, regardless of the training mode chosen.

The trainer alternates between demonstrative, interrogative, and active methods (through practical exercises and/or real-world scenarios). This pedagogical approach ensures concrete and directly applicable learning in the workplace.

Teaching resources provided

To ensure the quality of the Tabnine Training - Boosting Code Productivity with AI training, Learni provides the following teaching resources:

Mac or PC computers, high-speed fiber internet, whiteboard or flipchart, video projector or interactive touchscreen (for remote sessions)
Training environments installed on workstations or accessible online
Course materials, practical exercises, and supplementary resources
Post-training access to materials and teaching resources

For in-house training at a location external to Learni, the client ensures and commits to having all necessary teaching materials (IT equipment, internet connection...) for the proper conduct of the training action in accordance with the prerequisites indicated in the communicated training program.

* contact us for remote feasibility** ratio varies depending on the training followed

Assessment methods

The assessment of skills acquired during the Tabnine Training - Boosting Code Productivity with AI training is carried out through:

During training: case studies, practical exercises, and professional scenarios
At the end of training: self-assessment questionnaire and skills evaluation by the trainer
After training: training completion certificate detailing acquired skills

Training accessibility

Learni is committed to the accessibility of its professional training programs. All our training programs are accessible to people with disabilities. Our teams are available to adapt teaching methods to your specific needs. Do not hesitate to contact us for any accommodation request.

Training access terms and deadlines

Training objectives

Master Tabnine to accelerate professional development in the enterprise

Configure custom AI models for tailored skills

Optimize code suggestions with advanced prompts and contexts

Implement Tabnine in collaborative certified workflows

Deploy Tabnine in teams for measurable productivity gains

Analyze and refine AI performance for complex projects

Integrate Tabnine with CI/CD for secure and efficient coding

Training program

Module 1Tabnine: Advanced Installation and Configuration (VS Code, IntelliJ, Custom Models)

Quick installation of Tabnine in your favorite IDEs, configuration of API keys and first tests on real projects, exploration of base versus pro models to select the optimal for enterprise use, practical exercises to customize suggestions based on your tech stack, creation of a test workspace with AI code review, production of an initial report on daily coding speed gains.

Module 2Tabnine: Advanced Prompts and Contextual Management (Multi-languages, Refactoring)

Deep dive into prompt engineering for precise and secure code generation, advanced contextual analysis on large codebases, exercises on automated refactoring of legacy code in Python or JavaScript, integration of Tabnine with Git for collaborative suggestions, concrete enterprise cases such as REST API optimization, deliverable of a refactored module 30% faster with performance metrics.

Module 3Tabnine: Custom Models and Enterprise Integrations (CI/CD, Security)

Training of Tabnine models on your private codebase for ultra-personalized suggestions, connection to DevOps tools like Jenkins or GitHub Actions, practical workshops on security audits of AI-generated code, team management with Tabnine Pro for shared workflows, simulation of agile sprints boosted by AI, production of a Tabnine-infused CI/CD pipeline with automated tests and productivity ROI report.

Module 4Tabnine: Performance Optimization and Pro Use Cases (Scalability, ROI Measurement)

In-depth analysis of Tabnine metrics to maximize suggestion acceptance to 80%, best practices for scalability in large enterprise projects, exercises on real cases like monolithic to microservices migration, ROI measurement via time saved and reduced errors, post-training action plan for production deployment, synthesis with skills certification and access to advanced resources for continuous improvement.