Démarrez à tout moment votre nouvelle carrière ! Disponible à temps partiel ? Pas de problème, étudiez à votre rythme.
Des projets professionnalisants
Apprenez les compétences clés de votre futur métier en validant 13 projets tirés de cas concrets d’entreprise.
Un accompagnement personnalisé
Bénéficiez de sessions de mentorat avec un expert du métier.
Certification OpenClassrooms
Décrochez une certification professionnelle « Data Scientist».
DataAI Engineer
Certification
Certification OpenClassrooms
Période de formation
9 mois à temps plein
Durée en alternance
18 mois
Durée de la formation
603 heures supervisées
Become an AI Engineer
Perform advanced data analysis and business predictions using data science Companies produce a colossal amount of data. Being able to analyse and leverage this data is crucial and represents an undeniable competitive advantage.
Translate a business need into a data science problem and solve it using your algorithms For example, you will make predictions to improve your company's sales or develop artificial intelligence for mobile applications. Working closely with business teams, you will carry out a data project, from data collection to the production of your algorithms.
Design predictive and autonomous models Machine learning data scientists specialise in training and deploying machine learning models. As part of a data team, you will be responsible for creating algorithms and designing self-learning programmes. For example, you will develop recommendation engines or text and image classification systems using deep learning algorithms.
What are the responsibilities of an AI Engineer?
Collect and preparedata with Python for analysis.
Explore and analyse data to understand trends and performance of a business or product.
Perform classifications using deep learning algorithms.
Develop predictive models to identify new trends and opportunities.
Deploy data models to automate business processes and improve their efficiency.
Communicate results to specialists or novices through visualisations.
Participate in the organisation and management of a data science or AI project.
A teaching method based on practical experience.
Your career and employment opportunities after completing this program
Market salaries for the position of AI engineer:
Beginner: $45,000 to $65,000 USD gross per year
Senior: $65,000 to $90,000 USD gross per year
Salary may vary depending on seniority, industry and company size, responsibilities (managerial or budgetary), and location.
You can move into other data-related roles, such as consultant, after a few years of experience or by continuing your studies in this field.
Who Is Eligible to Enroll?
To get started on this training, you need to have the following prerequisites:
Bachelor's degree in Data Science, Data Analytics, Computer Science, Statistics, Mathematics, Engineering, or related field
OR
One or more of the following professional certifications or equivalent/higher-level certifications: • Microsoft Azure AI Fundamentals (AI-900) • Microsoft Azure Data Fundamentals (DP-900) • Microsoft Certified: Azure Data Scientist Associate (DP-100) • AWS Certified Cloud Practitioner • Google Cloud Digital Leader
OR
Completion of all three of the following courses: • Learn Python Basics for Data Analysis • Perform an Initial Data Analysis • Use Python Libraries for Data Science
Language: a good level of English (for non-native speakers, a CEFR level of B2, an IELTS band score of 6.5, or a TOEFL score of 80 is recommended).
Equipment: access to a computer (PC or Mac), headphones, a webcam, and a stable internet connection.
At least 16GB of RAM and 100GB of free storage space available on your computer.
Administrator rights to your computer in order to install required programs.
Information About Degrees
OpenClassrooms is a higher education institution, accredited by the WASC Senior College & University Commission (WSCUC).
Upon completion of this program, eligible students will be awarded an Associate level degree in the Computer Support area of study. OpenClassrooms is eligible to issue degrees in the following states.
Certification OpenClassrooms
OpenClassrooms est un établissement privé d’enseignement à distance déclaré au rectorat de l’Académie de Paris.
À l’issue de votre formation, sous réserve de validation de vos compétences, vous obtiendrez le diplôme d’établissement OpenClassrooms « Data Scientist ».
Votre diplôme
OpenClassrooms est un établissement privé d’enseignement à distance déclaré au rectorat de l’Académie de Paris.
À l’issue de votre formation, sous réserve de validation de vos compétences, vous obtiendrez le diplôme d’établissement OpenClassrooms « Data Scientist ».
DataAI Engineer
Certification
Certification OpenClassrooms
Période de formation
9 mois à temps plein
Durée en alternance
18 mois
Durée de la formation
603 heures supervisées
Une pédagogie basée sur la pratique
Obtenez des compétences clés en validant des projets professionnalisants.
Progressez à l'aide d'un expert du métier.
Gagnez un véritable savoir-faire ainsi qu’un portfolio pour le démontrer.
Les projets et compétences en détail
projet 1
Start your AI Engineer training
Discover what it means to be a Machine Learning Data Scientist. In this first project, you will define your goals and study program.
13 heures supervisées
Compétences acquises dans ce projet
Define the scope of your training
projet 2
Analyse data from education systems
Strengthen your Python fundamentals for data science by analyzing data from educational systems
30 heures supervisées
Compétences acquises dans ce projet
Apply descriptive statistical analyses and visually navigate through data
Configure the working environment necessary for data exploitation
Correct anomalies manually and using appropriate tools
projet 3
Anticipate building consumption needs
Help a major city achieve its goal of carbon neutrality
30 heures supervisées
Compétences acquises dans ce projet
Apply descriptive statistical analyses and visually navigate data
Automate the cleaning process using Python
Choose an algorithm suited to the objectives
Configure the working environment
Define the training procedure and train the model with the datasets
Prepare the datasets to put the variables on a common scale
projet 4
Automatically classify information
Build and evaluate a supervised classification model while strengthening your skills in exploratory analysis and machine learning
50 heures supervisées
Compétences acquises dans ce projet
Configure the working environment necessary for data exploitation
Evaluate the machine learning model
Implement a cleaning process to improve data quality
Prepare and transform data to adapt it to the learning model.
Train a machine learning model
projet 5
Deploy a machine learning model
Deploy a machine learning model using modern tools to make the model usable in production.
40 heures supervisées
Compétences acquises dans ce projet
Define and formalize data processing and storage workflows
Establish and run a DBMS testing process
Implement an authentication system for data security
Model an infrastructure compatible with the IT system
Set up and configure a DBMS and extraction tool
Set up the work environment
Structure data architecture and design the databases
projet 6
Get started with MLOps (part 1/2)
Dive into a binary classification problem applied to banking data. Discover how to manage the lifecycle of a machine learning model. Model your data using a model versioning tool: MLflow.
60 heures supervisées
Compétences acquises dans ce projet
Identify hyperparameters
Manage overfitting and underfitting with appropriate techniques
Monitor the quality of features
Optimize activation functions
projet 7
Label and apply semi-supervised approaches in image processing
Your first automatic image processing! Discover deep learning for images.
40 heures supervisées
Compétences acquises dans ce projet
Prepare and transform data to adapt it to the learning model.
Identify or create a learning model adapted to business needs and constraints
projet 8
Confirm your MLOps skills (Part 2/2)
Within a financial company, you will develop a dashboard to explain credit approvals. You will deploy your model in the cloud. You will design your own API and automate deployment, then study the model drift.
50 heures supervisées
Compétences acquises dans ce projet
Design a system for monitoring the lifecycle of the learning model
projet 9
Design and deploy a RAG system
Build a functional Retrieval-Augmented Generation system based on LangChain and the Mistral model, supported by a Faiss vector base.
60 heures supervisées
Compétences acquises dans ce projet
Identify or create a learning model adapted to business constraints and needs
Expose results to departments/business units via an API
Create test processes
Identify and configure a compatible API and integrate it to allow access to results
projet 10
Assess the performance of an LLM
Ensure an effective, consistent, and reproducible RAG system capable of providing accurate answers by leveraging a structured document base.
60 heures supervisées
Compétences acquises dans ce projet
Evaluate the performance of the infrastructure behind the learning model
projet 11
Frame an AI project
In a few days, the COMEX meeting will take place to approve your company’s product roadmap. You will outline the project to convince senior management that your product has strong potential.
40 heures supervisées
Compétences acquises dans ce projet
Conduct actions and discussions between the data project stakeholders
Create a prototype of the solution to confirm its technical feasibility
Define and plan the modalities for implementing and monitoring the data project
Identify and disseminate new opportunities, solutions, or practices in the data field
Identify and evaluate the risks
Present the data project and explain the choices made to demonstrate its relevance
projet 12 - en construction
Design a recommendation system for data-driven agriculture
Design, develop, and deploy a recommendation system.
80 heures supervisées
projet 13 - en construction
Build your Data Scientist - Machine Learning portfolio
Present your Machine Learning Data Scientist portfolio and implement a technical project.
50 heures supervisées
Un accompagnement individuel & privilégié
Bénéficiez de sessions individuelles avec un expert professionnel du métier.
Progressez rapidement dans vos projets grâce à son excellence dans le partage de son savoir-faire.
La communauté OpenClassrooms
Comptez sur une communauté soudée d’étudiants prête à vous aider 24h/24, 7j/7.
Partagez vos questions et vos doutes avec des centaines d'étudiants, de mentors et de diplômés sur un réseau social privé.
Comment se déroule un parcours OpenClassrooms ?
Du choix de leur formation au premier jour de leur nouvelle carrière, nos étudiants racontent leur expérience et l'accompagnement qu'ils ont reçu, étape par étape.
Cette formation nécessite un investissement en temps estimé à 1206 heures dont 603 heures supervisées.
Détails sur la durée de la formation
La durée totale de la formation se compose de :
603 heures de formation supervisée avec des projets, encadrés par des mentors
603 heures de formation guidée avec des cours et des ressources pédagogiques
La période de formation peut être rallongée en cas de formation à temps partiel. La durée est estimée et dépend de votre niveau d'entrée en formation, de votre disponibilité, du temps alloué par semaine, de votre capacité et rythme d'apprentissage.
Ce parcours vous intéresse pour votre entreprise ?