Data Lead

Data Engineer Training

105 hours of complete training to learn the skills of a Data Engineer, perfect those of a Machine Learning Engineer and acquire a solid foundation in Reinforcement Learning. You can take advantage of this training on a part-time or full-time basis, in person or remotely.

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Build your future in data

Get the skills of a dataexpert

A Programme That Adapts to Your Pace

The programme is hyper-practically oriented and built by data professionals. You will be able to follow it full time or part time to adapt your training to your schedule. Also, flexibility being a major element of your future life in Tech, you will keep the possibility to follow the training in face-to-face or distance learning.

2.25 million rows of data: what you can handle

Learn how to manage very large data infrastructures through the implementation of advanced projects. But managing these volumes is not the only thing! You will learn how to manage data from various sources: CRM, website analytics, networks, Internet etc.

Promote the AI models you have created

The phase at which many data projects fall by the wayside: the production phase. Because once your model is created, it will be useless if it does not benefit your customers, partners or collaborators. With the Fullstack training, you will have a very good basis in deployment, and you will be able to go further in this skill, which is highly sought after by recruiters.

The dual skills that companies are looking for

For a long time, companies hired mostly Data Analysts and Data Scientists. Their objectives were to perform relevant analyses from the generated data, but also to perform modeling, predictions, and recommendations in an automated way in order to guide the final decisions.

As the volume of data generated has increased in recent years, the needs of companies have also evolved. Data Engineers and Machine Learning Engineers have emerged. Their role will be to maintain a robust data infrastructure, no matter how big or small, but also to ensure that the results of the AI models built by the Data Scientists are made available to the right stakeholders. New areas we train our students in with the Lead training.

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Jedha bootcamp data lead programme

The Data Lead trainingcurriculum

Learn how to deploy AI applications developed on your computer to all types of deployment servers with your mastery of Docker and Kubernetes. Your applications will be accessible to everyone, whether you have 100 users per month or 10,000 users per minute. Then learn how to increase the computational speed of your AI model with Ray, a distributed Machine Learning Framework. Because now that your application is deployed and robust for all its users (Docker and Kubernetes), you will surely want to scale the Machine Learning or Deep Learning model that is hosted on it in the long run. Complexifying your Machine Learning model will have a direct impact on the power you will need, and the Ray Framework will train your model by allocating computational tasks to different computers instead of just one.
Acquire state-of-the-art expertise in Docker and Kubernetes, two skills that are highly sought after by recruiters, by putting them into practice on rare and surprising use cases (video games, robotics): Reinforcement Learning! To do this, you will dive into the Open AI Gym library, allowing you to create your own development environment, 100% customizable to your needs. As Reinforcement Learning models also require more power and computing speed, you will then learn about the Open Source RLib library.
Now that your application is built, a lot of data will be created. You will then have to build a real pipeline allowing you to collect all the data generated so that you can analyze it afterwards. You will then understand the concept of ELT process (compared to ETL) and then apply this new process with Airbyte. Then, what happens when you have data to analyze coming in continuously? Here you will master the concept of Streaming Data with Kafka. Then we will enter another use of the data pipeline: Graph Data Science. You will understand with Neo4j's technology how to create a whole data network, very much used for recommendation systems: it is about creating a particular connection between 2 similar products or users for example.
Now that you have deployed your application with Docker and Kubernetes, dug into these technologies thanks to Reinforcement Learning and built a pipeline allowing you to retrieve the generated data, you are still not going to leave your application without monitoring and improvement! Thanks to Airflow, you will learn how to automate this Data pipeline so that it respects a certain number of actions: this isworkflow automation. You will learn to improve your model so that it performs according to your expectations! This is the whole objective of ML Monitoring, the mechanisms of which you will learn thanks to a tool that lives up to its name: Evidently AI. You will find in this teaching of ML Monitoring good practices very rarely taught and yet extremely beneficial for any Tech professional.
Big Data: Code in Scala
Module 1
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Spark: manage your infrastructure
Module 2
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Master the ETL process
Module 3
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DevOps skills
Module 4
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Your Data Engineering project
Module 5
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Download the Full Syllabus

Next Sessions

First London courses (online or in-class) launching 2022!

Paris
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Part-time
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Apr
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Aug
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3
Jul
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Jul
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Part-time
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Apr
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Aug
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Full Time
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Apr
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Part-time
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Apr
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Full Time
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Apr
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Full Time
3
Jul
24
Jul
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Oops! No bootcamp is planned in Paris soon, contact us for more information.
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Part-time
1
Apr
5
Aug
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Every Saturday | 10am - 6pm
3
available places
Only 2 places left!
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Full Time
24
Apr
16
May
Monday to Friday 10am - 6pm
Monday to Friday 10am - 6pm
5
available places
Only 2 places left!
Last place available !
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Full Time
3
Jul
24
Jul
Monday to Friday 10am - 6pm
Monday to Friday 10am - 6pm
9
available places
Only 2 places left!
Last place available !
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🇫🇷
Part-time
1
Apr
5
Aug
Every Saturday | 10am - 6pm
Every Saturday | 10am - 6pm
3
available places
Only 2 places left!
Last place available !
Apply
🗣 
🇫🇷
Full Time
24
Apr
16
May
Monday to Friday 10am - 6pm
Monday to Friday 10am - 6pm
5
available places
Only 2 places left!
Last place available !
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🗣 
🇫🇷
Full Time
3
Jul
24
Jul
Monday to Friday 10am - 6pm
Monday to Friday 10am - 6pm
9
available places
Only 2 places left!
Last place available !
Apply
🗣 
🇫🇷
Part-time
1
Apr
5
Aug
Every Saturday | 10am - 6pm
Every Saturday | 10am - 6pm
3
available places
Only 2 places left!
Last place available !
Apply
🗣 
🇫🇷
Full Time
24
Apr
16
May
Monday to Friday 10am - 6pm
Monday to Friday 10am - 6pm
5
available places
Only 2 places left!
Last place available !
Apply
🗣 
🇫🇷
Full Time
3
Jul
24
Jul
Monday to Friday 10am - 6pm
Monday to Friday 10am - 6pm
9
available places
Only 2 places left!
Last place available !
Apply
🗣 
🇫🇷
Part-time
1
Apr
5
Aug
Every Saturday | 10am - 6pm
Every Saturday | 10am - 6pm
3
available places
Only 2 places left!
Last place available !
Apply
🗣 
🇫🇷
Full Time
24
Apr
16
May
Monday to Friday 10am - 6pm
Monday to Friday 10am - 6pm
5
available places
Only 2 places left!
Last place available !
Apply
🗣 
🇫🇷
Full Time
3
Jul
24
Jul
Monday to Friday 10am - 6pm
Monday to Friday 10am - 6pm
9
available places
Only 2 places left!
Last place available !
Apply

How to join the community?

Do you want to become a Data Engineer? Follow this admissions process. You will need to meet the pre-requisites to join the course. After applying or requesting the syllabus of our courses, you can meet with our admissions team to discuss your career aspirations and learn more about the world of data.
Professor Jedha in his classroom

Apply or request the syllabus here

Make an appointment with our admissions team

Discuss your ambitions and objectives together before finalising your registration

Download the Complete Syllabus

Data training to obtain an expert level

The Tech field is evolving at lightning speed. In this context, you will always need to be ahead of the game in terms of technology. The technologies we teach in the Lead training are the ones most used by the major companies in the Tech world, both in terms of tools and methods.

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People at Jedha campus

A diversity of backgrounds

Our Lead alumni? Some of them were already data professionals or had just completed the Data Fullstack training and wanted to obtain a differentiating expertise, while others were particularly interested in Data Engineering, Machine Learning Engineering or DevOps.

I am a Data Analyst or Data Scientist and I would like to evolve even more in Data

I don't have a Tech background, but I want to evolve in the Data Engineering world.

Two of the main technologies taught: Docker and Kubernetes. What is the difference?

What our students thought of their training

The richness of our community is one of Jedha's strengths! You will have the pleasure of exchanging with people with very different backgrounds. In this third Data course, our students were able to gain even more expertise in the field of Data, here is what they thought.

From the concepts of DevOps or Data Engineering to their implementation on more complex ETL projects, I came out of the course with the necessary skills to implement more complex data projects in production.

Delphine Jean - From Marketing Manager to Data Consultant

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Very, very dense training, and very enriching! Our teacher Samuel was always available and attentive throughout the course.

Lucas Guivier - Data Engineering Consultant @ L'Oréal

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We were accompanied with passion and enthusiasm: Laurent is very competent technically to approach complex subjects, but also, very pedagogical to teach them well. Excellent training to learn about Data Engineering.

Arturo Guizar - CTO @ Datalo.co, Data Consulting

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Chat with our team

Training in line with the needs of companies

Jedha's training is meant to be multi-faceted. That is why our alumni work in all types of positions in data.

In particular, they work as Data Analysts, Data Scientists, Machine Learning Engineers, Data Engineers and Cybersecurity Analysts.

The sectors of activity are very diverse, ranging from start-ups to large groups. The main difference of our alumni is their ability to translate needs into Data problems, to adapt quickly to technological changes and to communicate effectively with teams.

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People at jedha campus

What are the opportunities after the Data Lead training?

The Data Lead training will allow you to reach a high level of expertise. In this sense, a number of new technical professions are made accessible to you after completing the program.

You will most often find jobs such as Data Engineer, Machine Learning Engineer, or ML Ops. But what exactly are these jobs?

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Data Engineer

A highly technical job! The Data Engineer's job is to build Data infrastructures, and to promote the work of Data Scientists by putting their models into production.

Machine Learning Engineer

He takes care of the last mile of data! The Machine Learning Engineer works on the optimisation of Artificial Intelligence models so that they can be better deployed throughout the company.

DevOps

The DevOps profession will allow you to create applications or websites that meet the needs of your business. You will put all these environments into production and automate the data recovery processes!

ML Ops

Maintaining Machine Learning models in production in a reliable and solid manner is the job of the ML Ops. At the crossroads of the worlds of Data Science and Data Engineering, he/she takes over from the Machine Learning Engineer in the Data pipeline, once the models have been well deployed.

Data Engineer Certificate

Certification of the Data Lead course
RNCP Level 6 - Bac+3/4

Our Data Lead course is an integral part of our "Data Science Designer-Developer" diploma and allows you to validate its block n°6 in "Data Infrastructure Management".

How does this certification work? By enrolling in our Data Lead course, you will have the opportunity to take our Data certification. At the end of your programme, you will present your lead project to a panel of judges and will be able to prove your skills to all your future recruiters by having applied the tools taught.

This certification also allows you to benefit from your CPF credits to finance the training in its entirety or in part.

Discover our courses!
Book a call with Admissions Team
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Training Costs

  • Payment in up to 10 monthly installments
  • Access to courses & events for life
  • Possibility of making up missed classes
  • Access to our online platform
  • State-recognised certification
Make an Appointment
Training fee Schedule
🇫🇷 France
Essentials
1 495 €
Most popular
Fullstack
Most popular
6 995 €
Lead
2 995 €
Essentials
£1,995
Most popular
Fullstack
Most popular
£6,595
Lead
£2,695

A typical day in a Data Lead

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 our teaching team who will take you step by step through the content. You will be able to ask questions and progress at your own pace. 
12:00
Practice
Apply the concepts you have just explored to simple exercises. This will allow you to see the direct application cases and to grasp the technical mechanisms.
13:30
Challenges
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 explored by companies with very interesting stories such as Doctolib, Payfit or Spendesk.
10:00
16:30
18:00
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
Tutorial
Revision of the contents seen last week and we explore the new concepts of the day
😴
🏫 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.

What our students do after the course

After our Lead training, our alumni work as Data Engineers, Machine Learning Engineers, or Data Architecture Consultants in renowned companies. 

Jedha student
portrait jean paul paoli
portrait chiara
portrait bonnie naccache
portrait antoine guerrini
portrait augustin lauvencourt
Jedha student
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jedha student
jedha student
portrait camille destombes
Jedha student
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Jedha masters of excellence

Vulgarisation - expertise - Very proud of our alumni, we accompany them in the realisation of their Data Science project
and help them to reach their professional goals.very proud of our alumni, we accompany them in the realisation of their Data Science project and help them to reach their professional goals.

Guillaume Manderscheid
Guillaume Manderscheid
Data Scientist / Data Engineer Freelance
 @
Beyond being a fine popularizer, Guillaume is marked by his passion for Tech. Having first worked for important structures in the energy sector (notably at ENGIE), he flew to San Francisco where he worked as a Data Scientist / Data Engineer.
[...]
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Guillaume Manderscheid
In San Francisco, he worked not only on modelling, but also on deployment. It was at this point that he made a shift to Data Engineering by joining Strateos as a Data Engineer. When he came back to Paris, he rediscovered his passion for teaching and delivered courses on each of our 3 Data programs.
Read Less
Habib Herbi
Habib Herbi
Big Data Cloud Engineer
 @
Société Générale
All the skills taught in the Lead training, Habib uses them in his daily work at Société Générale! The perfect opportunity to ask him for advice on these technologies.
[...]
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Habib Herbi
All the skills taught in the Lead training, Habib uses them in his daily work at Société Générale! Habib has been working on data infrastructures since 2016. After a university career and his first professional experience in Algeria, Habib worked successively at IRCAM, Kimia Lab, BioTech Kimia in the health field. He then worked for almost 3 years at Devoteam where he contributed greatly to the construction of Data pipelines. Since September 2019, Habib has been working for Société Générale where he manages the entire Big Data stack, from ETL process management to optimization.
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Laurent Morelli
Laurent Morelli
Co-founder
 @
Timelight
Laurent is as good a manager as he is a technician! Laurent teaches Data Science as well as Data Engineering and will give you precious advice on the direction to take in your projects, all with the aim of making you more autonomous.
[...]
Read More
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!
Read Less
Discover the whole Jedha Masters team

Data Engineering expertise through practice

We are very proud of our student community and follow our alumni throughout their careers and delight in their successes.

gamer playstation
Portait Aurelie Mutschler
Marie Pierre
Paris Campus
Sharing job offers or freelance missions, events or Data & Cybersecurity news, Discord is THE communication channel of the Jedha community. Sharing job offers or freelance missions, events or Data & Cybersecurity news, Discord is THE communication channel of the Jedha community.
gamer playstation
Portait Aurelie Mutschler
Marie Pierre
Paris Campus
Sharing job offers or freelance missions, events or Data & Cybersecurity news, Discord is THE communication channel of the Jedha community. Sharing job offers or freelance missions, events or Data & Cybersecurity news, Discord is THE communication channel of the Jedha community.
gamer playstation
Portait Aurelie Mutschler
Marie Pierre
Paris Campus
Sharing job offers or freelance missions, events or Data & Cybersecurity news, Discord is THE communication channel of the Jedha community. Sharing job offers or freelance missions, events or Data & Cybersecurity news, Discord is THE communication channel of the Jedha community.

Your questions about the Data Lead training

What are the pre-requisites to join the Lead course?

Are 105 hours of training sufficient to master Data Engineering skills?

How much work do I have to do during this course?

Can I apply for Data Engineer positions after the Data Lead training?

How do you justify these choices of tools and language? AWS? Scala and not Python?

What are the objectives of the training?

Download the Complete Syllabus

I would like to make my admission

If you are interested in the Lead course, both in its curriculum and in the way it is taught, we invite you to contact our admissions team, who will be able to advise you in the best possible way, in line with your background and professional aspirations.

I have a solid background in Data or I have completed the Fullstack training

I want to obtain technical skills that are all the more differentiating

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

Professor Jedha in his classroom