Mirantis Launches New Training Courses on AI Agents and AI Infrastructure
Mirantis Launches as organizations accelerate the adoption of artificial intelligence, the need for employees with practical AI skills is growing across both technical and business functions. Addressing this demand, Mirantis has introduced two new training courses designed to help organizations understand, build and operate AI technologies.
The new programs focus on two different areas of the AI technology stack. AI-DEV 100: Agentic Workflow Workshop teaches participants how to use AI agents and build agentic workflows without requiring programming skills. AI-INFRA 100: AI Infrastructure focuses on the infrastructure required to deploy and operate GPU-based systems for AI workloads.
Together, the courses are designed to provide organizations with training options for both non-technical professionals exploring AI agents and technical teams responsible for deploying and managing the infrastructure that powers AI applications.
Building Practical Skills for AI Agents
The AI-DEV 100 course is designed for professionals who already understand how to interact with AI models but may not have software development or programming experience.
The four-module course does not require any prerequisites and combines instruction with a hands-on laboratory. Participants work through the process of creating a functional agentic workflow, giving them practical experience with how AI agents can be used to complete tasks and coordinate workflows.
Unlike traditional developer-focused AI courses, AI-DEV 100 is designed to make agentic technology accessible to people working in non-engineering roles. Participants do not need to write code to complete the course.
This approach reflects the expanding role of AI agents across business functions. As organizations experiment with AI-powered workflows, employees in areas such as operations, marketing, sales, finance and other business functions may increasingly interact with or manage AI-driven processes.
By providing a practical introduction to agentic workflows, the course aims to help organizations broaden AI literacy beyond their engineering and data science teams.
Training for AI Infrastructure
While AI-DEV 100 focuses on the application side of AI, AI-INFRA 100 addresses the infrastructure required to run AI workloads.
The four-module course is designed for technical professionals and begins with an introduction to the fundamental differences between traditional IT infrastructure and infrastructure designed for GPU and AI workloads.
AI applications can place substantially different demands on infrastructure compared with conventional enterprise workloads. Organizations deploying AI systems need to consider GPU resources, specialized networking, cluster architecture, workload management and other infrastructure requirements.
AI-INFRA 100 provides a foundation for understanding these differences before moving into more advanced technical topics.
The later modules cover areas including cluster provisioning and cluster networking, with hands-on labs designed to give participants practical experience working with AI infrastructure.
This makes the course particularly relevant for IT professionals, infrastructure engineers, cloud teams and other technical specialists who need to understand how to deploy and operate infrastructure capable of supporting AI workloads.
Addressing Different AI Skill Requirements
The introduction of the two courses reflects the range of skills organizations need as AI adoption expands.
Not every employee involved in an AI initiative needs to become a software engineer. Business teams may need to understand how to use AI agents and incorporate them into workflows, while technical teams need deeper expertise in the infrastructure supporting those applications.
Mirantis has structured its new training programs around these distinct requirements.
“AI technology has come on so quickly that there is a lot of learning and collaboration needed,” said Dom Wilde, senior vice president and general manager of the enterprise AI cloud business at Mirantis. “That is what we’re addressing with these training courses intended for very different audiences.”
The two-course approach gives organizations the option to develop AI skills across multiple levels, from employees learning how to work with AI agents to technical teams responsible for the underlying infrastructure.
Combining Instruction With Hands-On Experience
Hands-on training is a central element of both programs.
AI-DEV 100 includes a practical laboratory in which participants build an agentic workflow, allowing them to apply concepts introduced during the course.
AI-INFRA 100 similarly incorporates hands-on labs as participants progress into technical subjects such as cluster provisioning and networking.
This practical approach is intended to bridge the gap between theoretical knowledge and real-world implementation. Rather than simply introducing AI concepts, the courses give participants opportunities to work directly with workflows and infrastructure scenarios.
For organizations deploying AI at scale, practical experience can be particularly important because successful implementation often requires collaboration between business users, developers, infrastructure teams and IT operations.
Extending Mirantis’ Training Expertise
The new AI courses build on Mirantis’ existing training portfolio.
For more than a decade, the company has provided instructor-led and self-paced training programs covering technologies and practices such as cloud-native operations, containers, Kubernetes and OpenStack.
That experience has traditionally focused on helping technology professionals develop practical skills for modern cloud-native environments. The introduction of AI-focused courses extends this training strategy into emerging areas of AI agents and AI infrastructure.
As enterprises move from experimenting with AI to deploying production workloads, organizations need employees who understand not only AI applications but also the infrastructure, operations and workflows required to support them.
Mirantis’ new courses are designed to address both sides of that challenge.
Supporting the AI Skills Pipeline
The rapid evolution of AI technologies has created a skills gap for many organizations. New AI models, agentic workflows and specialized infrastructure are developing quickly, making continuous training increasingly important.
For business professionals, understanding how to use AI agents can help them identify opportunities to automate or improve workflows. For technical teams, understanding GPU infrastructure and AI-specific networking can help them prepare systems capable of supporting increasingly demanding workloads.
By offering separate courses for these audiences, Mirantis aims to help organizations develop a broader AI skills base rather than limiting training to specialized AI engineers.
The courses can also support collaboration between technical and non-technical teams by giving participants a clearer understanding of the roles different technologies play within an AI environment.
Preparing Organizations for the Next Stage of AI
The introduction of AI-DEV 100 and AI-INFRA 100 comes as organizations increasingly move toward deploying AI systems in production.
AI agents are emerging as a way to automate multi-step tasks and workflows, while GPU infrastructure is becoming a critical component of AI computing. As these technologies develop together, organizations will need employees who understand both how AI can be applied and how the underlying systems can be deployed and operated.
Mirantis’ new training programs address these requirements from two complementary perspectives.
AI-DEV 100 provides an accessible introduction to agentic workflows for professionals without programming experience, while AI-INFRA 100 gives technical teams a foundation for working with GPU and AI infrastructure.
Together, the courses expand Mirantis’ training portfolio into key areas of the AI technology stack and provide organizations with practical learning opportunities as they build their AI capabilities.
With its longstanding focus on cloud-native technologies and hands-on education, Mirantis is extending that expertise to help businesses and technology professionals prepare for an increasingly AI-driven computing environment.
About Mirantis
Mirantis provides infrastructure technology designed to support scalable GPU cloud environments and enterprise AI workloads. Its full-stack AI infrastructure portfolio is intended to simplify operations across the AI lifecycle, from physical infrastructure through AI model deployment.
Through k0rdent AI and strategic partnerships, Mirantis helps organizations manage GPU resources, improve utilization, support multi-tenant environments, orchestrate workloads and automate infrastructure operations.
The company serves global enterprises including Adobe, Ericsson, Inmarsat, MetLife, PayPal and Societe Generale.
The new AI training courses extend Mirantis’ focus on helping organizations build the skills needed to develop, deploy and operate modern AI systems.
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