The Implementing Cisco NX-OS Switches and Fabrics in the Data Center (DCNX) course provides detailed knowledge of the Cisco Nexus switch platform and teaches learners how to install, configure, and manage Cisco Nexus switch platforms in scalable and highly available data center environments. Through a combination of instructor-led learning and hands-on labs, participants explore Cisco Nexus product families, platform implementation and management, security, routing and forwarding, VXLAN, QoS, programmability, and storage technologies. The course also covers Fibre Channel, Fibre Channel over Ethernet (FCoE), device aliases and zoning, and N-Port ID Virtualization (NPIV) and N-Port Virtualization (NPV).

The Understanding Cisco Data Center Foundations (DCFNDU) training provides foundational knowledge and hands-on skills for configuring Cisco data center technologies, including networking, virtualization, storage area networking, and unified computing. The course introduces Cisco Nexus and Cisco NX-OS, Cisco UCS, Cisco Application Centric Infrastructure (Cisco ACI), automation, APIs, and cloud computing. Participants gain practical experience configuring Cisco NX-OS and Cisco UCS technologies. The training is designed to help prepare learners for entry-level data center roles and further Cisco data center training.

Artificial Intelligence (AI) for HR Administrators is a practical training program designed to help HR professionals understand and apply artificial intelligence and generative AI in everyday HR activities. The course covers AI fundamentals, generative AI tools, prompt design, AI-assisted HR workflows, AI agents, productivity applications, AI strategy, data privacy, security, bias, governance, and responsible human oversight. Learners gain practical experience applying AI to HR communications, meetings, information management, employee support, and other HR workflows while developing the judgment required to use AI responsibly. The course is adapted from the current AIHR Artificial Intelligence for HR curriculum, which focuses on AI fundamentals, GenAI applications, prompt design, AI strategy, AI agents, and responsible AI use in HR.

AI+ Architect Practitioner™ (AT-320) is a 5-day AI architecture certification program covering neural network fundamentals, optimization, NLP and computer vision architectures, model evaluation, AI infrastructure and deployment, responsible AI, generative AI, research-based AI design, and a capstone project. The program combines theoretical concepts with hands-on activities to help learners design, optimize, deploy, and evaluate AI architectures. AI CERTs currently lists the program as AI+ Architect Practitioner™, formerly known as AI+ Architect™.

Machine Learning Engineering on AWS is a 3-day intermediate-level course designed for machine learning professionals who want to build, deploy, orchestrate, and operationalize machine learning solutions at scale on AWS. The course provides hands-on experience with AWS services including Amazon SageMaker AI and Amazon EMR, covering data preparation, feature engineering, model training, tuning, deployment, security, MLOps, automated deployment, and model monitoring.

AI & LLMOps Mastery with Azure is a 4-day intermediate-level training program covering machine learning, AI-powered search, generative AI, and Large Language Model Operations (LLMOps) using Microsoft Azure’s AI ecosystem. The course covers Azure Machine Learning, Azure AI Search, Microsoft Foundry, Prompt Flow, Retrieval-Augmented Generation (RAG), LLM fine-tuning, model evaluation, LLMOps, monitoring, automation, CI/CD, and AI-powered chatbot development. The course combines Microsoft courseware for the first three modules with a dedicated LLMOps module and demonstrations. Participants require an Azure subscription for hands-on practice in the LLMOps module.

AI-300T00-A: Operationalize machine learning and generative AI solutions is an intermediate-level Microsoft Azure course focused on designing, implementing, and operating Machine Learning Operations (MLOps) and Generative AI Operations (GenAIOps) solutions. The course covers secure and scalable AI infrastructure, the machine learning model lifecycle using Azure Machine Learning, and the deployment, evaluation, monitoring, and optimization of generative AI applications and agents using Microsoft Foundry. Learners also work with automation, continuous integration and delivery, infrastructure as code, and observability using GitHub Actions, Azure CLI, and Bicep.