Training Data
Lead

70 hours of training and 2 full-time or part-timeprojects to manage complex Big Data infrastructures and master all the skills of a Data Engineer.

Data engineeringBootcamp

Why do this training?

Adapt the program to your own pace

Companies are now managing ever more complex infrastructures. Whether it's with the use of Spark, ETL processes or even DevOps, you'll learn all the tools you need to organize them.

Become a Data Engineer

The skills of the Data Engineer are increasingly in demand. He or she is able to solve a problem that has become vital: structuring all the company's own data and making it accessible to all departments.

Manage Data Infrastructure

Companies are now managing ever more complex infrastructures. Whether it's with the use of Spark, ETL processes or even DevOps, you'll learn all the tools you need to organize them.

The curriculum of the Lead training

Spark is THE Big Data framework, allowing complex computations and analysis on very large volumes of data. Being written in Scala, you will have to master it to continue your journey in Data Engineering. It is also a more suitable language in some cases than Python for Big Data infrastructure management.
We told you, Spark is THE Big Data framework. With your knowledge of the Scala language, you will be able to manage large volumes of data with Spark SQL. You will also learn how to manage streaming data for real-time analysis with Spark Streaming!
Extract - Transform - Load. In your professional missions, you will be required to collect data, pre-process it and store it in a data warehouse. Let's deepen the notions seen during the Fullstack program with all the powerful AWS services: RedShift, S3, RDS, Athena, Dynamo DB. Then you will learn how to automate all these processes with Airflow!
You will understand how all these databases are fed by having those sought after DevOps skills. You will learn how to standardize code environments, scale your application and manage your production infrastructure, with Docker and Kubernetes.
A first project will be administered to you, you will have to elaborate a processing strategy: 2.25 million lines to manage in this first guided project! In a second, more free project, you will deploy your own application and will have to manage it, with the amount of data it generates.
Big Data: Code in Scala
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Spark: manage your infrastructure
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Master the ETL process
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DevOps skills
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Data Engineering Projects
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Download the complete syllabus

Next sessions

Take your bootcamp part-time or full-time.
Keep the best training experience: in the context of the health crisis, all our training is delivered remotely.

Week End
4
Dec
19
Feb
Tous les Samedis | 10h - 18h
Tous les Samedis | 10h - 18h
5
available places
Only 2 places left!
Last place available !
Apply at
Week Day
6
Dec
17
Dec
Monday to Friday 10am - 6pm
Monday to Friday 10am - 6pm
6
available places
Only 2 places left!
Last place available !
Apply at
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Data training,
with many opportunities

Entrepreneurs, managers, employees, freelancers, the objective is to build professional opportunities for you.

Make an appointment
data engineer training with jedha bootcamp
Data Engineer

A highly technical job! The Data Engineer builds the Data infrastructures, and promotes the work of the Data Scientists by putting their models into production.

data consultant career
Machine Learning Engineer

He takes care of the last mile of data! The Machine Learning Engineer intervenes, among other things, to optimize the models so that they can be better deployed throughout the company.

DevOps

You will create applications or websites that meet the needs of your business. You will put all these environments in production and automate the data recovery processes!

Where do our alumni work after the training

After our Lead training, our alumni work as Data Engineer, Data Architect or Devops in renowned companies.

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The successes of our students

We are very proud of our student community and follow our alumni throughout their Data career to reach their professionnal goal.

Go to the blog
Project data
Optimiser son Copywriting grâce au Deep Learning
Project data
Système de recommandation : comment en créer ?
Project data
Footmatcher : Football player recommendation system

A typical day of training

10:00
Course Review
We start the day by reviewing the previous day's concepts to make sure everything is in place before we start working on new content.
10:15
Course Content
Let's start the concept of the day with the teaching team who will take you step by step. You will be able to ask all your questions and progress at your own pace. 
12:00
Practice
Apply the concepts you have just seen to simple exercises. This will allow you to see the direct application cases and to grasp the technical mechanisms.
13:30
Challenge
Once you have been able to practice the theoretical concepts on simple exercises, it's time for the Data challenges! You will work on more complex Data topics that will allow you to better understand what a Data project is. 
16:00
Office Hours
Two additional hours are allocated each day with the teaching assistants to review concepts or move forward on your project. This is a good opportunity to ask questions and review some of the theoretical concepts. 
18:00
Events
We offer immersive Data training and what better way to end your day than with a Data talk. Many topics are covered by companies that have very interesting cases such as Doctolib, Payfit or Spendesk.
10:00
4:00
6:30
9:00
Sunday
D
Tuesday
M
Monday
L
Wednesday
M
Thursday
J
Friday
V
Saturday
S
At home
Recommended review of the lessons seen during the week and further study of the exercises
Presential
New theoretical concepts are tackled in Data with practice on application cases
😴
🏫 Presential - Work in class with your teacher to see the theoretical concepts and work together on the exercises.
🏠 At home - It is advisable to work at home to deepen the lessons and go over the exercises to best prepare for the week.

Une formation enseignée par des experts

Alain Demenet
Alain Demenet
Developer
@ Jedha
Machine Learning Engineer ET développeur, Alain a bien plus d'une corde à son arc. Il est notamment le créateur officiel de la plateforme JULIE sur laquelle vous trouverez tous vos contenus de cours, et bien plus !
[...]
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Alain Demenet
Alain attended Ecole 42. Since 2016, he has been evolving in the Data Science sector, with an expertise in Deep Learning and development. He quickly took the touch of teaching, in different training organizations as a Lead Instructor. He joined the QuantCube team where he worked on satellite image processing missions, then launched his own activity on Machine Learning Engineering projects. He is now the developer of JULIE, our e-learning platform!
Benoît Courty
Benoît Courty
Senior Data Scientist
@ National Assembly
Il est parmi nos maîtres Jedha Machine Learning Engineers ! Une des riches réalisations de Benoît : avoir crée une infrastructure Data capable remplir les 80 000 places du stade de France en 15 minutes !
[...]
Read more
Benoît Courty
No less than 4 years as Software Engineer @ TF1, 5 years as Web & Mobile project manager @ FNAC Spectacle, 2 years at France TV to implement the recommendation system of their web application, Benoît has just as many hats from which he will give you very interesting feedbacks. To continue on the most impressive projects, he is now Senior Data Scientist at the French National Assembly, where he works in the study of the impacts of bills.
Laurent Morelli
Laurent Morelli
Co-founder
@ Timelight
Laurent est aussi bon manager qu’il n’est bon technicien ! Enseignant autant sur la partie Data Science que sur le Data Engineering, Laurent vous donnera de précieux conseils sur la direction à prendre dans vos projets, le tout dans le but de vous faire gagner en autonomie.
[...]
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Laurent Morelli
Laurent is as good a manager as he is a technician. He worked for more than 3 years at Matters Startup Studio, a company developing web applications. As Head of AI, he developed the whole Data department on various issues. He then created 2 companies. The first one, Paprika, helping startups with Machine Learning methods and the second one, Timelight in March 2019. Timelight is a tool helping companies in their analysis of temporal data: precious advice to ask Laurent!

Training costs

Payment up to 7 times without charge
Possibility of financing by its CPF
Possibility of catching up on courses
Access to our online platform JULIE
Access to our content for life
Career Coaching & Mentoring Sessions
Access to our events for life
See funding opportunities
formation data analyse
Essentials  
1 295 €
formation data scientist
Fullstack
5 595 €
Formation Data Engineering Jedha
Lead  
1 995 €
formation data analyse
Essentials  
1 295 €
formation data scientist
Fullstack
5 595 €
Apply at
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The most recognized data training

Avec une note moyenne de 4.97/5, Jedha se place en première place au classement des formations Data en France. Au-delà de la note, ceci est le reflet de notre volonté d'apporter un savoir en phase avec les besoins des étudiants et des entreprises.

C'est une vraie fierté de pouvoir accompagner nos étudiants dans la réalisation de leurs projets professionnels, de les rendre autonomes en Data et les voir apporter de la valeur aux entreprises dans lesquelles ils travaillent.

Leur formation a pu les ouvrir à de nouveaux horizons, que ce soit pour monter leur startup dans l'IA ou pour lancer leur carrière dans la Data.

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4.97/5
#1 France
Overall
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Curriculum
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Nous répondons à toutes vos questions

1. Quels sont les pré-requis pour intégrer cette formation ?

2. Quel est le profil type de vos élèves ?

3. Quels sont les débouchés professionnels que je pourrai remplir à la fin de cette formation ?

4. A quel niveau expertise est-on amené pendant la formation Fullstack ?

5. Quel accompagnement carrière fournissez-vous aux élèves ?

6. La formation est-elle dispensée en présentiel ou à distance ?

7. Combien de temps avant le début de la session peut-on s'inscrire ?

Is this training made for me?

I have advanced skills in Data
or I am coming out of the Fullstack program

I want to control
the entire
data pipeline

I make an appointment with the admissions team to find out everything!

Bootcamp data engineering jedha