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 Amazon AI: Mastering AWS Artificial Intelligence Solutions training are: Basic knowledge of AWS Cloud and Python or JavaScript programming languages. A preliminary interview validates your eligibility.

Is the training available in person?

Yes, the Training Amazon AI: Mastering AWS Artificial Intelligence Solutions training is available in distanciel. The format can be adapted to your needs (inter, intra, custom).

Training Amazon AI: Mastering AWS Artificial… | 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 Amazon AI: Mastering AWS Artificial Intelligence Solutions 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 Amazon AI: Mastering AWS Artificial Intelligence Solutions 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 Amazon AI: Mastering AWS Artificial Intelligence Solutions 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 program

Module 1Introduction to AI on AWS and Overview of Amazon AI Services

Presentation of artificial intelligence on the AWS Cloud. Key differences between Machine Learning, Deep Learning, and traditional AI. Discovery of the AI ecosystem, managed vs. customized services. Concrete use cases of AI on Amazon (automation, text/image analysis, voice assistants, etc.). Hands-on with the AWS interface and first steps with Amazon AI Platform.

Module 2Manipulating SageMaker and Operational Machine Learning

Principles and architecture of SageMaker. Building an ML pipeline: data preparation, training, evaluation, and model deployment. Using AutoML, collaboration with Jupyter Notebooks, version management. Securing data and best practices to optimize performance and cost. Practical exercises: image classification and anomaly detection.

Module 3Ready-to-Use AI: Amazon Rekognition, Lex, Comprehend, and Polly

Presentation and hands-on with ready-to-use Amazon AI services: Rekognition (image and video analysis), Lex (voice and text chatbot), Comprehend (automatic language analysis), Polly (text-to-speech). Integration scenarios into business applications. Practical workshops: developing an assistant via Lex, document analysis with Comprehend, automated audio creation with Polly. Managing permissions, security, monitoring, and cost analysis.

Module 4Deploying and Monitoring a Complete Amazon AI Project

Designing an end-to-end AI project on AWS. Deploying models in production. Monitoring performance and managing logs via CloudWatch. Scaling strategies, optimization, and workflow automation. Security audit, data governance, and compliance with regulations (GDPR).

Module 5Case Studies and Practical Workshops

Realization of supervised mini-projects to integrate multiple Amazon AI services into a real application: recommendation engine, document management automation, intelligent customer support. Feedback, developing a roadmap to industrialize AI solutions on AWS. Q&A time and personalized coaching.