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 Training Cloud Natural Language API - Analyzing AI Language in the Enterprise training are: Mastery of Python or Node.js, basics of Google Cloud Platform, advanced knowledge of NLP. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Cloud Natural Language API - Analyzing AI Language in the Enterprise training is available in in-person. The format can be adapted to your needs (inter, intra, custom).

Training Cloud Natural Language API - Analyzing ... | 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 Training Cloud Natural Language API - Analyzing AI Language in the Enterprise 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 Training Cloud Natural Language API - Analyzing AI Language in the Enterprise 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 Training Cloud Natural Language API - Analyzing AI Language in the Enterprise 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 objectives

Master Cloud Natural Language API for professional semantic analyses

Develop skills in entity and sentiment extraction in a business context

Implement custom certifying classifications with the API

Design scalable NLP pipelines connected to massive data

Optimize performance and security for production deployments

Integrate the API into business applications for productivity gains

Training program

Module 1Cloud Natural Language API Configuration: Authentication and First Advanced Calls (Google Cloud Console, API Keys, SDK)

Installation and configuration of the Google Cloud environment with activation of Cloud Natural Language API, secure authentication via service accounts and OAuth2, first API calls for batch text analysis, practical exercises on real company datasets, debugging common errors, creation of an ongoing project with logging and monitoring to validate professional skills from the first day.

Module 2Cloud Natural Language API Entity Extraction: NER Recognition and Saliency (Custom Models, Scoring)

In-depth exploration of named entity extraction with advanced types such as PERSON, ORGANIZATION, LOCATION, saliency analysis to prioritize relevant content, training of custom models via AutoML, practical cases on legal and medical texts, implementation of Python scripts for automated pipelines, production of structured JSON reports usable in business, interactive exercises to master accuracy and scale processing.

Module 3Cloud Natural Language API Sentiment Analysis: Syntax and Classification (Deep Learning, Multi-Language)

Deep dive into fine-grained sentiment analysis with magnitude and score metrics, syntactic parsing for dependency trees, custom document classification on specific domains like e-commerce or customer support, multi-language integration for 20+ languages, hands-on workshops on Twitter datasets and product reviews, development of real-time alerts, generation of dashboards with visualizations to demonstrate immediate business impact.

Module 4Coreference and Cloud Natural Language API Integration: Hybrid Pipelines (BigQuery, Pub/Sub)

Mastery of coreference resolution to link pronouns and entities in long documents, construction of end-to-end pipelines with streaming via Pub/Sub and BigQuery storage, hybridization with Vertex AI for custom models, enterprise use cases like intelligent chatbots and contract analysis, collaborative coding sessions for connected web apps, load testing and API cost optimization, deliverables including deployable source code and certifying documentation.

Module 5Cloud Natural Language API Optimization and Security: Production and Monitoring (Quotas, IAM, Costs)

Advanced strategies to optimize quotas and costs with caching and massive batching, securing via IAM policies and VPC Service Controls, monitoring with Cloud Monitoring and Logging for proactive alerts, serverless deployments on Cloud Run, review of the ongoing project with peer review, simulation of real incidents for resilience, governance plan for enterprise teams, issuance of certificates and roadmap for continuous skills development.