Certifications

Retrieval Augmented Generation (RAG)

DeepLearning.AI

Covers the design, implementation, and evaluation of RAG systems using semantic and keyword retrieval, vector databases, prompt augmentation, monitoring, and production trade-offs.

• Natural Language Processing
• Prompt Engineering
• Generative AI
• Large Language Models
• System Monitoring
• Semantic Web
• Query Languages
• Application Security

Natural Language Processing Specialization

DeepLearning.AI

Builds NLP systems with classification, vector-space, probabilistic, sequence, and attention models for sentiment analysis, translation, named-entity recognition, summarization, and question answering.

• Feature Engineering
• Text Mining
• TensorFlow
• Natural Language Processing
• Probability & Statistics
• Markov Models

Fundamentals of MCP

Hugging Face

Introduces the Model Context Protocol, its architecture and communication model, and the clients, servers, SDKs, and capabilities used to connect AI systems with external tools and data.

Extract, Transform and Load Data in Power BI

Microsoft

Develops practical ETL skills in Power BI: configuring data sources, cleaning and transforming data with Power Query, profiling anomalies, and validating data integrity.

• Data Integration
• Extract, Transform, Load (ETL)
• Microsoft Power BI

Build, Train and Deploy ML Models with Keras on Google Cloud

Google Cloud

Covers TensorFlow input pipelines, data preprocessing, neural-network design with the Keras Sequential and Functional APIs, and scalable model training and deployment with Vertex AI.

• Google Cloud Platform
• Machine Learning
• Machine Learning Operations (MLOps)
• Deep Learning
• Keras
• TensorFlow

BigQuery Fundamentals for Teradata Professionals

Google Cloud

Covers BigQuery architecture, resource provisioning, IAM, data ingestion, schema design, and optimized SQL querying while comparing the platform with Teradata.

• Google Cloud Platform
• Big Data
• Extract, Transform, Load (ETL)
• SQL

Google Cloud Fundamentals: Core Infrastructure

Google Cloud

Introduces Google Cloud resource management, IAM, virtual machines and networking, storage options, containers with Kubernetes, and application deployment services.

• Google Cloud Platform
• Kubernetes
• Cloud Storage
• Virtual Machines
• Prompt Engineering

MOOC SecNumacadémie — 4 modules

ANSSI — Agence nationale de la sécurité des systèmes d'information

Completed the four-module SecNumacadémie curriculum covering the information-security landscape, authentication security, Internet security, and workstation protection and secure remote work.

• Cybersecurity Awareness
• Authentication Security
• Internet Security
• Endpoint Security
• Secure Remote Work

L'atelier RGPD — Modules 1–5

CNIL

Completed five modules covering GDPR key concepts, data-protection principles, stakeholder responsibilities, the role of the DPO and compliance tools, and data protection for local authorities.

• GDPR
• Data Protection
• Privacy Compliance
• Data Governance

AI For Everyone

DeepLearning.AI

Explores essential AI terminology, capabilities and limitations, how to identify suitable AI projects, collaborate with technical teams, shape an AI strategy, and address ethical considerations.

• Machine Learning
• Deep Learning
• Data Ethics
• Data Science

FIDLE 2022/2023 — Introduction to Deep Learning

CNRS · Université Grenoble Alpes · MIAI

FIDLE is a free and open French-language introduction to deep learning, combining foundational concepts with advanced architectures. The complete 2022/2023 video curriculum was followed offline; attendance certificates cover live sequences 13–18 on GANs, diffusion models, AI law and ethics, training optimization, hardware acceleration, and deep reinforcement learning.

• Sequence 13 — Generative Adversarial Networks (GANs) · 9 March 2023 · 2 hours
• Sequence 14 — Diffusion models and text-to-image · 16 March 2023 · 2 hours
• Sequence 15 — AI, law, society, and ethics · 23 March 2023 · 2 hours
• Sequence 16 — Faster and more efficient learning: training optimization · 30 March 2023 · 2 hours
• Sequence 17 — Hardware acceleration · 6 April 2023 · 3 hours
• Sequence 18 — Exploration and exploitation in deep reinforcement learning · 20 April 2023 · 3 hours

• Deep Learning
• Generative Adversarial Networks
• Diffusion Models
• Responsible AI
• Model Optimization
• Hardware Acceleration
• Deep Reinforcement Learning