AI Engineer

Perform advanced data analysis and business predictions using data science.

Training duration
9 months full time, which is 35 hours per week. Learn more.
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A flexible online program

Imagine starting a brand-new career at any time! Can’t commit to full-time? No problem, study at your own pace.

Real-world projects

Acquire the most relevant skills by completing 13 projects based on those required in your future career.

Individual learning support

Benefit from mentoring sessions with an expert in the field.

OpenClassrooms Certification

Leave with a “Data Scientist” professional qualification.
DataAI Engineer
Diploma
Certification
OpenClassrooms Certification
Duration
Training duration
9 months full time
Duration
Hourly volume
603 hours supervised

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 prepare data 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. 

Your diploma

  • OpenClassrooms is an online training educational establishment, declared as such by the French authority ‘le rectorat de l'Académie de Paris’.
  • Once you’ve completed your training program, and subject to validating your skills, you will receive the OpenClassrooms standard diploma "Data Scientist".
DataAI Engineer
Diploma
Certification
OpenClassrooms Certification
Duration
Training duration
9 months full time
Duration
Hourly volume
603 hours supervised

A teaching method based on practical experience.

  • Acquire key skills for your future career with real-world projects.
  • Make progress with the support of an experienced professional.
  • Acquire concrete know-how and demonstrate it with a portfolio.

Detailed projects and skills

project 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.
project
13 hours supervised
Skills acquired in this project
  • Define the scope of your training
project 2

Analyse data from education systems

Strengthen your Python fundamentals for data science by analyzing data from educational systems
project
30 hours supervised
Skills acquired in this project
  • Apply descriptive statistical analyses and visually navigate through data
  • Configure the working environment necessary for data exploitation
  • Correct anomalies manually and using appropriate tools
project 3

Anticipate building consumption needs

Help a major city achieve its goal of carbon neutrality
project
30 hours supervised
Skills acquired in this project
  • 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
project 4

Automatically classify information

Build and evaluate a supervised classification model while strengthening your skills in exploratory analysis and machine learning
project
50 hours supervised
Skills acquired in this project
  • 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
project 5

Deploy a machine learning model

Deploy a machine learning model using modern tools to make the model usable in production.
project
40 hours supervised
Skills acquired in this project
  • 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
project 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.
project
60 hours supervised
Skills acquired in this project
  • Identify hyperparameters
  • Manage overfitting and underfitting with appropriate techniques
  • Monitor the quality of features
  • Optimize activation functions
project 7

Label and apply semi-supervised approaches in image processing

Your first automatic image processing! Discover deep learning for images.
project
40 hours supervised
Skills acquired in this project
  • Prepare and transform data to adapt it to the learning model.
  • Identify or create a learning model adapted to business needs and constraints
project 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.
project
50 hours supervised
Skills acquired in this project
  • Design a system for monitoring the lifecycle of the learning model
project 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.
project
60 hours supervised
Skills acquired in this project
  • 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
project 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.
project
60 hours supervised
Skills acquired in this project
  • Evaluate the performance of the infrastructure behind the learning model
project 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.
project
40 hours supervised
Skills acquired in this project
  • 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
project 12 - under construction

Design a recommendation system for data-driven agriculture

Design, develop, and deploy a recommendation system.
project
80 hours supervised
project 13 - under construction

Build your Data Scientist - Machine Learning portfolio

Present your Machine Learning Data Scientist portfolio and implement a technical project.
project
50 hours supervised

One-to-one learning support

  • Benefit from individual mentoring sessions with a professional expert in the field.
  • Progress rapidly through projects thanks to their expertise in sharing know-how.

The OpenClassrooms community

  • Count on our solid student community to give you support 24-7.
  • Share your doubts or queries with a comprehensive network of students, mentors, and graduates.

How exactly will I learn on an OpenClassrooms training program?

From choosing what to study to starting their new career, our students describe their experiences and the support they received at every step of the way.
See step-by-step experience

Pay for your training program

Monthly subscription: The flexible, customizable option

For everyone.

Benefits

  • Flexible start date and study schedule

  • Non-binding subscription: Stop at any time

  • The faster you finish, the less it costs

€1,350 per month

for an estimated duration of 9 months amounting to €12,150.

Enroll now

This training program requires an estimated time commitment of 1206 hours, including 603 hours supervised.

The total training duration consists of:

  • 603 hours supervised with projects, coached by mentors
  • 603 hours guided with courses and educational resources

The training duration can be extended in the case of part time training.
The average duration is estimated and depends on your entry level into training, the time allocated per week, your availability, your capacity, and learning pace.

Interested in this path for your company?

Get connected with an expert

Training program last updated on Mar 25, 2026