Establish the technical groundwork for AI and machine-learning initiatives by covering core AI/ML concepts alongside the infrastructure requirements that support them. ENTERONE AITECH addresses the connection between AI/ML workloads and the technical environment needed to plan for those workloads, giving teams a common vocabulary for architecture conversations. The course fits early-stage AI/ML planning, when infrastructure, platform and technical stakeholders need to evaluate requirements before selecting or deploying supporting technology. It is relevant to teams assessing how AI/ML work affects their existing environment and to technical leaders building an informed starting point for future architecture discussions. AITECH focuses on foundations rather than a single hardware platform or product implementation. Its combination of AI/ML concepts and infrastructure requirements distinguishes it as a course for connecting workload understanding with practical technical planning. Use it to orient architects, infrastructure personnel and other technical contributors around the considerations that shape AI/ML readiness.