Certification Artificial Intelligence Architect

Overview

The "Artificial Intelligence Architect" certification, offered by Albert School, is awarded by JEDHA. It is a Level 7 certification with NSF codes 114b, 326 and 326r, and is registered in the National Directory of Professional Certifications (RNCP) under number 38777, by decision of France Compétences dated March 27, 2024.

Certification Objectives

In today's increasingly digital and interconnected world, companies across various sectors must effectively understand and utilize the data they possess. The rise of Artificial Intelligence (AI) has provided these organizations with the opportunity to convert data into valuable insights, thus enhancing decision-making, optimizing business processes, and personalizing customer experiences, among other benefits. However, successfully implementing an AI solution requires specific expertise, particularly in data architecture, data flow management, AI modeling, and deployment. Additionally, AI solutions must be implemented ethically and in compliance with current regulations, especially concerning data protection and privacy. Against this backdrop, the "Artificial Intelligence Architect" certification has been designed to meet the growing market demand for AI skills, enabling technology professionals to acquire and validate their expertise in this field.

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The certification aims to train professionals capable of designing, deploying, and managing robust, efficient, and regulation-compliant AI solutions. Candidates are assessed on essential skills for an AI architect, including data governance, where they must demonstrate the ability to develop and implement a solid data governance plan considering compliance aspects, stakeholders, and risks; data architecture, where they must design a robust architecture suited to technical and operational needs; data pipeline management, where they must establish and manage automated and efficient data pipelines; and AI solution development and deployment, where candidates must be able to create, integrate, and deploy AI solutions, including automating model retraining and setting up continuous integration and deployment pipelines.

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This certification addresses the growing market need for qualified professionals in AI, capable of driving innovation and digital transformation through ethical and effective AI use.

Competency Blocks

The academic program of the certification is organized into four main competency blocks, listed and detailed below:

• Block #1: Design and Manage Data Governance
  Design a Data Governance policy in collaboration with stakeholders to ensure compliance with current regulations and guarantee the quality, availability, security, and confidentiality of data. Work together with company stakeholders to advocate for and implement the Data Governance policy, aiming for smooth integration into the company's practices. Train and raise awareness among all employees, including those with disabilities, about the principles of Data Governance to ensure effective and inclusive implementation of the Data Governance policy. Conduct regular audits of the company's data management practices to ensure compliance with local and international regulations. Assess the risks associated with data management, particularly in terms of quality and security, to strengthen the Data Governance policy.
• Block #2: Design and Deploy Data Architectures (for AI)
  Identify architectural needs by investigating the technical, operational constraints, and existing standards, to establish a framework that meets the company's requirements. Develop a data architecture specification that incorporates technical constraints and standards to address the company's specific needs. Create logical and physical data models (entity-relationship, star schema models...) that align with the established specifications. Design database structures suited for various types of data, considering performance, security, scalability, and data volume for optimal Big Data management. Deploy virtual servers in the cloud or on-site for training Artificial Intelligence algorithms to efficiently manage a large volume of data. Enhance computing power through the design of server clusters to enable AI algorithm training, store large datasets, or handle massive traffic on an application. Implement monitoring tools to track data infrastructure performance, identify potential issues, and optimize systems for proactive management. Document the architecture specifications in a clear and accessible manner for everyone, including those with disabilities, to ease management.
• Block #3: Design and Implement Data Pipelines (for AI)
  Design a real-time data management system suitable for the company's operational constraints and standards to efficiently handle data velocity, flow volume, and data types. Establish a data pipeline through ETL/ELT processes for transferring and transforming data between different databases, using programming tools to meet the specification requirements. Automate data flows in the pipeline using specific tools or programming to optimize the performance of the data infrastructure. Monitor data flows to ensure quality and adherence to governance policies, aiming to maintain standards, security, and confidentiality in data pipelines. Develop quality control and error correction procedures in data pipelines to ensure data quality.
• Block #4: Build, Deploy, and Manage AI Solutions
  Draft a specification document for the AI solution to meet the organization's technical and economic needs, considering accessibility for individuals with disabilities. Create an AI algorithm suited to the training data and compliant with the specification document, ensuring it meets specific needs, particularly in terms of accessibility. Adapt the organization's data infrastructure by building APIs to accommodate the AI solution in production. Design continuous integration and deployment pipelines to automate the deployment process of an AI solution. Develop scripts for retraining models to automate the Machine Learning process. Manage the AI solution's performance within the infrastructure by implementing monitoring tools (such as Aporia or Evidently) to ensure it meets specification requirements in a production environment.Draft a specification document for the AI solution to meet the organization's technical and economic needs, considering accessibility for individuals with disabilities. Create an AI algorithm suited to the training data and compliant with the specification document, ensuring it meets specific needs, particularly in terms of accessibility. Adapt the organization's data infrastructure by building APIs to accommodate the AI solution in production. Design continuous integration and deployment pipelines to automate the deployment process of an AI solution. Develop scripts for retraining models to automate the Machine Learning process. Manage the AI solution's performance within the infrastructure by implementing monitoring tools (such as Aporia or Evidently) to ensure it meets specification requirements in a production environment.

‍Prerequisites

We seek curious and determined minds.
To join our program, you must hold a Level 6 degree or RNCP title, or 180 ECTS credits. Submit your application and convince us in a motivational interview.

More specifically, entry prerequisites are:

• The candidate must hold a Level 6 degree or RNCP title, or 180 ECTS credits.
• A candidate without the aforementioned degree or title, but with over two years of relevant professional experience, may be admitted. In such cases, a request must be sent to the certifier, who has the authority to approve the application.

Admission is based on application, tests, and a motivational interview.

Jobs / Sectors Targeted by the Certification

The "Artificial Intelligence Architect" certification proves to be relevant and applicable across a wide range of industries, aligning with the pervasive and cross-cutting nature of data and artificial intelligence. Here is a non-exhaustive list of sectors and employment contexts where this certification would be particularly advantageous:

• Information and Communications Technology (ICT): Within IT departments or serving technology consulting firms, AI is used to optimize systems and networks, automate repetitive tasks, enhance security, and improve the quality of services offered to users.
• Healthcare: Whether in hospitals, research labs, or biotech companies, AI helps improve diagnostics, predict diseases, personalize treatments, optimize healthcare facility management, and accelerate medical research.
• Finance: In banks, insurance companies, and fintech firms, AI is a valuable tool for fraud detection, process automation for compliance, risk management, personalization of financial services, and algorithmic trading.
• Retail and e-commerce: Within distribution and online commerce companies, AI helps optimize supply chains, improve product recommendations, personalize customer experiences, and predict sales trends.
• Manufacturing: In factories and industrial companies, AI aids in predictive maintenance, production optimization, process automation, and product quality improvement.
• Transportation and Logistics: For transportation companies and logistics providers, AI is used to optimize routes, improve fleet management, automate warehouses, and contribute to the development of autonomous vehicles.
• Public and Government Services: In the public administration context, AI can assist in improving citizen services, optimizing resource management, automating administrative processes, and analyzing data for better political decision-making.

Type of accessible jobs include :

• Artificial Intelligence Architect
• Data Architect
• Data Engineer
• Machine Learning Engineer
• MLOps Engineer
• AI Consultant
• Chief Data Officer (CDO)

Evaluation Methods

We measure your success through various evaluations modalities, that include :

• Written and oral assessments with various expected deliverables
• Professional scenario leading to both a written and oral evaluation, with different deliverables expected
• Evaluation conditions are adjusted to meet the specific needs of individuals with disabilities if necessary

This is how we ensure that you are ready to face tomorrow’s challenges.

Start your journey

Are you ready to apply for the AI Architect Certification and develop your skills? Just send an email to admission@albertschool.com including your CV and a motivational letter to express your interest. If your application is successful, you will be invited for an online interview to complete the process.