Mastère
Data Engineering Expert
En un an, devenez Data Engineer, Architecte Data, Expert Cloud ou DataOps avec un diplôme RNCP niveau 7 reconnu par l’État.
Data Engineering
Big Data
Cloud
IA GENERATIVE
Machine Learning
SQL
"They trust us".
Student satisfaction
Rate of return to employment
Obtaining certifications
Who is it for? this training?
100% financed: CPF, France Travail, Région, OPCO, ...
Training essentials
-
Target audience
-
Prerequisites
-
Admission
-
Session dates
-
Financing solutions
-
Made to measure
-
Cost & Organization
Who is this program for?
Bac+4/Bac+5 students in computer science, mathematics, statistics, MIAGE, engineering schools or M1 data/IA wishing to specialize.
Professionnels en activité (développeurs, ingénieurs systèmes, analystes BI, data analysts) voulant évoluer vers les métiers de la data engineering et du cloud.
Personnes en reconversion disposant de bases solides en programmation et bases de données.
Profils motivés par une formation en alternance, capables de lier compétences techniques (Python, SQL, cloud, pipelines, ML) et compétences transversales (gouvernance, sécurité, management de projet).
Academic prerequisites
Validated Bac+4 level (computer science, mathematics, statistics, engineering sciences, MIAGE, engineering school, M1 data/informatics)
OR 3 years' higher education with significant professional experience in IT/data (supported by a VAPP or VAE file)
Good grounding in applied mathematics: descriptive statistics, probability, linear algebra (vectors, matrices)
Technical requirements
Programming
Connaissance de Python (structures de base, boucles, fonctions, POO simple)
Familiarity with Git (versioning, branching, merge)
Bases de données
Compréhension de la logique SQL (requêtes SELECT, JOIN, GROUP BY)
Notions de modélisation relationnelle (schéma, clés, normalisation)
Systems / environments
Confort avec Linux / Bash (navigation, scripts basiques)
Ability to install environments (conda, pip, basic Docker)
Mathematics applied to data
Statistiques descriptives (moyenne, médiane, variance, corrélation)
Basic probability
Linear algebra (matrix product, vectors, simple transformations)
Admission stages
Step 1: Personalized appointment with an advisor to define your project.
Step 2: Project validation and alignment with your career objectives.
Step 3: Choice of ideal rhythm: intensive, alternating or part-time.
Step 4: Placement test & validation of prerequisites to ensure your success.
Step 5: Validation of financing with the support of our experts.
Step 6: Session planning and official launch of the adventure at DATAROCKSTARS.
Dates & registration
We launch new promotions every month.
Contact us for exact dates and a detailed calendar.
Solutions tailored to your profile
We do our utmost to identify the most suitable financing solutions for your business.
your situation.
An advisor will be happy to discuss this with you.
Personalized support
Our training courses are designed to meet your specific needs. Together, we build a course
to meet your educational objectives.
Contact our teams for personalized support.
Alternation rhythm
4 days / week in the company, 1 day / week in school.
Tuition fees
M2 One Year : 10,000 INCL. VAT
Payment can be made in a single instalment, in 3 instalments, or in 10 monthly instalments (on request).
Pre-registration
One-time application fee : 500 €
Work-study programs and internships
As part of a work-study program, the training is fully paid for by the company, and the student also receives a monthly salary.
-
Target audience
-
Prerequisites
-
Admission
-
Certification
-
Session dates
-
Financing solutions
-
Made to measure
-
Cost & Organization
Who is this program for?
Bac+4/Bac+5 students in computer science, mathematics, statistics, MIAGE, engineering schools or M1 data/IA wishing to specialize.
Professionnels en activité (développeurs, ingénieurs systèmes, analystes BI, data analysts) voulant évoluer vers les métiers de la data engineering et du cloud.
Personnes en reconversion disposant de bases solides en programmation et bases de données.
Profils motivés par une formation en alternance, capables de lier compétences techniques (Python, SQL, cloud, pipelines, ML) et compétences transversales (gouvernance, sécurité, management de projet).
Academic prerequisites
Validated Bac+4 level (computer science, mathematics, statistics, engineering sciences, MIAGE, engineering school, M1 data/informatics)
OR 3 years' higher education with significant professional experience in IT/data (supported by a VAPP or VAE file)
Good grounding in applied mathematics: descriptive statistics, probability, linear algebra (vectors, matrices)
Technical requirements
Programming
Connaissance de Python (structures de base, boucles, fonctions, POO simple)
Familiarity with Git (versioning, branching, merge)
Bases de données
Compréhension de la logique SQL (requêtes SELECT, JOIN, GROUP BY)
Notions de modélisation relationnelle (schéma, clés, normalisation)
Systems / environments
Confort avec Linux / Bash (navigation, scripts basiques)
Ability to install environments (conda, pip, basic Docker)
Mathematics applied to data
Statistiques descriptives (moyenne, médiane, variance, corrélation)
Basic probability
Linear algebra (matrix product, vectors, simple transformations)
Admission stages
Step 1: Personalized appointment with an advisor to define your project.
Step 2: Project validation and alignment with your career objectives.
Step 3: Choice of ideal rhythm: intensive, alternating or part-time.
Step 4: Placement test & validation of prerequisites to ensure your success.
Step 5: Validation of financing with the support of our experts.
Step 6: Session planning and official launch of the adventure at DATAROCKSTARS.
Alternating with DATAROCKSTARS & Efrei
State-recognized diploma - level 7 (Bac+5)delivered by Efrei, a leading digital engineering school
experts.
A professionally-oriented sandwich course: 75 % in the company, 25 % in training
A complete course covering
Data engineering & Big Data (pipelines, Spark, Kafka, Airflow)
Cloud & gouvernance (AWS, GCP, Azure, RGPD, sécurité)
Machine Learning & IA avancée (ML, Deep Learning, IA générative)
Data management & strategy
Dates & registration
We launch new promotions every month.
Contact us for exact dates and a detailed calendar.
Solutions tailored to your profile
We do our utmost to identify the most suitable financing solutions for your business.
your situation.
An advisor will be happy to discuss this with you.
Personalized support
Our training courses are designed to meet your specific needs. Together, we build a course
to meet your educational objectives.
Contact our teams for personalized support.
Alternation rhythm
4 days / week in the company, 1 day / week in school.
Tuition fees
M2 One Year : 10,000 INCL. VAT
Payment can be made in a single instalment, in 3 instalments, or in 10 monthly instalments (on request).
Pre-registration
One-time application fee : 500 €
Work-study programs and internships
As part of a work-study program, the training is fully paid for by the company, and the student also receives a monthly salary.
Detailed program training
Module 1: Python fundamentals, Algorithms & relational databases (S1-S2)
Python avancé, POO, Git, Bash
Data cleaning (Numpy, Pandas)
SQL / PostgreSQL (modèle relationnel, vues, contraintes)
Projet école : Analyse exploratoire d’un dataset (Kaggle / Open Data)
Application entreprise : manipuler, nettoyer et interroger les données du SI existant
Module 2: Exploratory Analysis, Statistics & Visualization (S2-S3)
Statistiques de base, corrélation, inférence
Advanced pandas (groupby, merge, pivot)
Visualisation : Matplotlib, Seaborn, GeoPandas
Dashboard interactif avec Streamlit
School project : Dashboard exploratoire + rapport data storytelling
Application entreprise : reporting métier, dashboards décisionnels
Module 3: Supervised & Predictive Machine Learning (S4-S5)
Regression (linear, Ridge, Lasso)
Classification (k-NN, Logistic Regression, Arbres de décision, XGBoost)
Assessment : cross-validation, overfitting, métriques
Feature engineering & pipelines ML (Scikit-Learn)
School project: Participation in a Kaggle challenge (Titanic, real estate...)
Application entreprise : implementation of an initial predictive model (internal POC)
Module 4: Advanced AI & Deep Learning (S6-S7)
Tableaux et matrices
Computer vision (YOLOv5 simple)
Clustering & réduction dimensionnelle (k-means, PCA)
ML in production : MLFlow, versioning models
Introduction to generative AI applied to data
School project : Dashboard ML + restitution résultats
Application entreprise : prototype de ML appliqué à un cas métier (ex. prédiction, classification clients, détection anomalies)
Module 5: Data Engineering & Big Data (S8-S9)
REST API (Flask)
Bases NoSQL : MongoDB
Ingestion : Airbyte, dbt
Traitement distribué batch & stream (Spark, Kafka)
Orchestration : Airflow
CI/CD + containerization (Docker, GitLab CI/CD)
Monitoring (Prometheus, Grafana)
School project : complete pipeline (batch + streaming, including monitoring)
Application entreprise : data pipeline industrialization
Module 6: Cloud & Data Governance (S10)
Fondamentaux Cloud (AWS, GCP, Azure)
Stockage cloud (S3, BigQuery, Glue)
IAM & security (roles, access, encryption)
Governance : MDM, data quality, catalog
SRGPD & anonymisation
School project : mise en place d’un pipeline data cloud sécurisé
Application entreprise : intégrer données locales & cloud, définir des règles de gouvernance
Module 7: Data strategy, governance & project management (S11)
Data strategy and business alignment
Project methodologies : Agile, Scrum, DataOps
Inclusive data team management
Data security & compliance
Data / Green IT performance KPIs
Managerial case studies
Application entreprise : management of an internal data mini-project
Module 8: Project & Final presentation (S12)
Cross-functional project integrating : stockage, pipeline, cloud, ML/IA, gouvernance & sécurité
Preparing for the RNCP jury : written report + oral presentation
Final presentation to a professional jury
Application entreprise : the "red thread" project is ideally the project entrusted by the company (valued in the final dissertation)
Detailed program training
Module 1: Python fundamentals, Algorithms & relational databases (S1-S2)
Python avancé, POO, Git, Bash
Data cleaning (Numpy, Pandas)
SQL / PostgreSQL (modèle relationnel, vues, contraintes)
Projet école : Analyse exploratoire d’un dataset (Kaggle / Open Data)
Application entreprise : manipuler, nettoyer et interroger les données du SI existant
Module 2: Exploratory Analysis, Statistics & Visualization (S2-S3)
Statistiques de base, corrélation, inférence
Advanced pandas (groupby, merge, pivot)
Visualisation : Matplotlib, Seaborn, GeoPandas
Dashboard interactif avec Streamlit
School project : Dashboard exploratoire + rapport data storytelling
Application entreprise : reporting métier, dashboards décisionnels
Module 3: Supervised & Predictive Machine Learning (S4-S5)
Regression (linear, Ridge, Lasso)
Classification (k-NN, Logistic Regression, Arbres de décision, XGBoost)
Assessment : cross-validation, overfitting, métriques
Feature engineering & pipelines ML (Scikit-Learn)
School project: Participation in a Kaggle challenge (Titanic, real estate...)
Application entreprise : implementation of an initial predictive model (internal POC)
Module 4: Advanced AI & Deep Learning (S6-S7)
Tableaux et matrices
Computer vision (YOLOv5 simple)
Clustering & réduction dimensionnelle (k-means, PCA)
ML in production : MLFlow, versioning models
Introduction to generative AI applied to data
School project : Dashboard ML + restitution résultats
Application entreprise : prototype de ML appliqué à un cas métier (ex. prédiction, classification clients, détection anomalies)
Module 5: Data Engineering & Big Data (S8-S9)
REST API (Flask)
Bases NoSQL : MongoDB
Ingestion : Airbyte, dbt
Traitement distribué batch & stream (Spark, Kafka)
Orchestration : Airflow
CI/CD + containerization (Docker, GitLab CI/CD)
Monitoring (Prometheus, Grafana)
School project : complete pipeline (batch + streaming, including monitoring)
Application entreprise : data pipeline industrialization
Module 6: Cloud & Data Governance (S10)
Fondamentaux Cloud (AWS, GCP, Azure)
Stockage cloud (S3, BigQuery, Glue)
IAM & security (roles, access, encryption)
Governance : MDM, data quality, catalog
SRGPD & anonymisation
School project : mise en place d’un pipeline data cloud sécurisé
Application entreprise : intégrer données locales & cloud, définir des règles de gouvernance
Module 7: Data strategy, governance & project management (S11)
Data strategy and business alignment
Project methodologies : Agile, Scrum, DataOps
Inclusive data team management
Data security & compliance
Data / Green IT performance KPIs
Managerial case studies
Application entreprise : management of an internal data mini-project
Module 8: Project & Final presentation (S12)
Cross-functional project integrating : stockage, pipeline, cloud, ML/IA, gouvernance & sécurité
Preparing for the RNCP jury : written report + oral presentation
Final presentation to a professional jury
Application entreprise : the "red thread" project is ideally the project entrusted by the company (valued in the final dissertation)
Pedagogical innovation for your success
Le monde évolue vite : vos formations doivent s’adapter à vos contraintes, à votre rythme et aux nouvelles façons d’apprendre. Chez nous, l’innovation pédagogique est au cœur de chaque parcours : pratique, flexible et personnalisée pour garantir une montée en compétence immédiate et durable.
THE AI integrated into your training programme
Peu importe la formation choisie, nous avons repensé toute notre ingénierie pédagogique pour y intégrer l’intelligence artificielle.
Dans vos projets fil rouge, les modules et les sessions d’accompagnement, vous apprendrez à utiliser l’IA pour innover, analyser et automatiser, tout en cultivant les bons réflexes et la réflexion éthique.
-
Working with AI in your projects
-
Discover advanced tools for your domain
-
Being ready for the market of the future
-
Boost your skills and become an augmented student
A development platform all-in-one
The complete route Datarockstars
Forgez votre succès avec la data science : Plongez dans notre formation pour développer des compétences essentielles et recherchées.
Cette formation est certifiante est délivre un diplôme d’état : Certification RNCP de niveau 6 (équivalent à un BAC+3/4 sur le marché du travail)
Discovery & Integration
L’aventure démarre par une immersion dans l’univers de la data, de l’IA et de la cybersécurité. Nos apprenants découvrent les métiers, renforcent leurs bases techniques et prennent en main les outils indispensables pour réussir.
Training & Projects
The course culminates in a "red thread" project presented to a professional jury. This stage officially validates the skills acquired and crowns the course with a DataRockstars certification recognized on the market.
Certification
At the end of the course, a final project is presented to a jury to validate skills and obtain Datarock Stars certification.
Professional integration
We don't just train you in a profession, we accompany you all the way to employment. Personalized coaching, job dating, access to our network of partner companies: everything is done to speed up your recruitment.
Network & Community
With DataRockstars, training is just the beginning. You become part of an active community of alumni and professionals. Participate in exclusive events, masterclasses, hackathons, afterworks... You're now part of a close-knit family that shares the same values and opens doors throughout your career.
Data & AI professions that await you tomorrow!
A panorama of the most sought-after professions in the Data & AI sector
-
AI Engineer
-
Data Scientist
-
Data Analyst
-
Data Engineer
-
MLOps Engineer
-
Data Architect
-
Data Product Manager
-
Data Steward (Governance)
-
NLP Engineer (LLMs)
-
Computer Vision Engineer
-
Database Administrator (DBA)
-
Chief Data Officer (CDO)
Launch your career and find
a job!
Testimonials from our students
Why choose our training?
At DATAROCKSTARS, the satisfaction of our learners is our greatest success. Thanks to innovative teaching methods, tailor-made support and concrete projects, our students develop solid skills that are directly applicable in the job market.
Make an appointment now!
- Call our experts
Simple, effective and free of charge, if you need to find out if this training is right for you, our experts are here to help.
Do you have any questions?
Our teaching experts are here to answer your questions, so don't hesitate to apply!