What Is AI+ Developer?

Overview

AI+ Developer is a AI CERTs credential. Develop AI-powered applications with practical coding and integration skills. This PathKey™ guide summarizes the domains, format, cost signals, eligibility, and renewal pattern so you can decide before you book. Accumentum is an Army CA and Air Force COOL Approved Vendor. We teach preparation for the AI CERTs exam. AI CERTs sets exam content, fees, and policies.

Accumentum is an Army CA and Air Force COOL Approved Vendor. We teach preparation for the AI CERTs exam. AI CERTs sets exam content, fees, and policies.

Who it is for

• Programmers looking to expand their skills in building and deploying AI-driven applications within the AI+ Developer ecosystem.
• Professionals seeking to deepen their expertise in developing AI and machine learning models for data-driven solutions.
• Technical specialists aiming to understand AI development processes and integrate AI solutions into organizational systems.

Exam domains

Weights follow the official outline.

1. 01

   Introduction to AI and Machine Learning Development

   Overview of artificial intelligence, machine learning, and generative AI for developers, Understanding the role of AI in software development and solution architecture, and Key differences between traditional programming and AI-driven development.

2. 02

   AI+ Developer Ecosystem Overview

   Exploration of the AI+ Developer infrastructure and development services, Overview of APIs, SDKs, and tools for building AI applications, and Understanding integration of AI models with development workflows.

3. 03

   Practical AI Development Use Cases

   Identifying development scenarios suitable for AI-driven solutions, Examples of AI applications in areas like automation, predictive analytics, and natural language processing, and Techniques for mapping project requirements to AI+ Developer capabilities.

4. 04

   Foundation Models for AI Development

   Introduction to foundation models and their role in AI application development, Design considerations for selecting, fine-tuning, and deploying foundation models, and Understanding model optimization for performance and scalability in development.

5. 05

   Responsible AI Development Practices

   Principles of ethical AI development, focusing on fairness, transparency, and accountability, Strategies for mitigating bias in AI models during development and deployment, and Implementing responsible AI guidelines within development workflows.

6. 06

   Security in AI+ Developer Solutions

   Best practices for securing AI models and data in development environments, Techniques for protecting sensitive data used in AI model training and inference, and Understanding encryption, access control, and secure coding in AI+ Developer.

7. 07

   Governance and Compliance in AI Development

   Key governance frameworks for managing AI development projects, Understanding regulatory standards impacting AI solutions (e.g., GDPR, CCPA), and Tools for monitoring and auditing AI+ Developer solutions for compliance.

8. 08

   Data Management for AI Development

   Best practices for sourcing, preparing, and managing data for AI model development, Building and optimizing data pipelines within the AI+ Developer ecosystem, and Techniques for ensuring data quality and relevance for AI training workflows.

9. 09

   Deploying AI Solutions in AI+ Developer

   Step-by-step process for deploying AI models in the AI+ Developer environment, Configuring development resources for optimal performance and scalability, and Monitoring and managing deployed AI models for accuracy and reliability.

10. 10

    Preparing for the AI+ Developer (AIDEV) Certification

    Overview of the AI CERTs AI+ Developer (AIDEV) certification exam structure and objectives, Key topics and competencies tested in the certification exam, and Practice scenarios and coding exercises to reinforce course concepts.

Exam format and cost

Questions

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Duration

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Format

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Passing score

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Cost

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Delivery

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Languages

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Experience and eligibility

Familiarity with at least oneprogramming language (e.g., Python, Java, or similar) to understand AI development workflows. Basic knowledge of artificial intelligence or machine learning concepts, though no advanced experience is required.

Renewal

Renewal rules for AI+ Developer are set by AI CERTs. Many credentials use a multi-year cycle with continuing education, a renewal fee, or a newer exam. Confirm the current cycle on the vendor site.

Roles this credential fits

• This foundational course is designed for individuals who work with or aim to develop AI technologies, such as software developers, data scientists, and IT professionals. It covers essential topics like fundamental AI concepts, practical development use cases, and the ethical implementation of AI within development environments. Participants will explore the AI+ Developer ecosystem, learning how to identify opportunities for building AI applications, understand design considerations for foundation models, and recognize the importance of responsible AI practices. The course also includes modules on security, compliance, and governance for AI-driven development solutions, ensuring learners are well-prepared for the AI CERTs AI+ Developer (AIDev) certification exam. By the end of the training, participants will possess the knowledge to develop AI solutions for business innovation and understand the impact of AI on development-driven organizational strategies.
• AI Development
• Teams standardizing on this credential for hiring or compliance

Official sources

• AI CERTs

Always confirm fees, dates, and eligibility on the vendor site before you register. Vendors change outlines and prices without notice.