Develop foundational knowledge of artificial intelligence and machine learning with course content focused on the technical concepts behind AI/ML. The material addresses the core terminology and technical foundations needed to discuss AI and machine-learning initiatives in an IT context. It provides a structured starting point for understanding the technologies and infrastructure considerations associated with AI/ML work. Infrastructure requirements are a central part of the course scope. AI and machine-learning projects depend on more than an algorithm or application layer; they also require consideration of the technical environment supporting those workloads. This course connects foundational AI/ML concepts with the infrastructure requirements that must be considered when evaluating or planning AI-related initiatives. ENTERONE CPLL-AITECH-V1.0 is suited to learners building an initial technical vocabulary around AI/ML and the systems that support it. Its stated focus distinguishes it from narrowly application-oriented content by including both conceptual foundations and infrastructure requirements. Use it where the objective is to establish a common understanding of AI and machine learning before moving into architecture, platform selection, implementation, or workload-specific design decisions.