Systems Architects: To understand the integration of LLM systems into broader IT environments.; Network Architects: To optimize network configurations for high-speed LLM training and inferencing.; Storage Architects: To manage the storage and retrieval of large-scale datasets used in LLM systems.; AI Infrastructure Architects: To build robust and scalable AI platforms optimized for LLM workloads.; Data Scientists: To prepare high-quality datasets and fine-tune LLMs for specific use cases.; Machine Learning Engineers: To deploy and optimize LLMs for real-world applications with low latency and high throughput.
IT Training
DCLLM - Implementing and Operating LLM Inferencing Systems with Cisco and NVIDIA Data Center Technologies
Offered by StorSoft through its training partners, the Cisco DCLLM - Implementing and Operating LLM Inferencing Systems with Cisco and NVIDIA Data Center Technologies course develops practical, mission-ready information technology skills. It targets practitioners who already work in the area and need deeper, applied depth. Delivery is available in virtual classroom live and classroom live formats, typically over 5 days. Relevant background is recommended before enrollment.
Cisco
Before you enroll
Prerequisites and certification path.
Delivered through StorSoft
Schedule this course for your team.
StorSoft coordinates delivery through its authorized training partners, including Global Knowledge, and can align scheduling, delivery mode, and cohort size to your program. Course facts are maintained from partner catalogs; confirm current pricing and dates when you submit a request.