Machine Learning, security and compliance for AI solutions, AI solution architecture, GenAI LLM applications, intelligent automation, data engineering fundamentals

Apis, Machine learning concepts, Advanced prompt engineering, Google Gemini, Data Analysis, Architectural design patterns, Generative AI models

Pytorch, Python, nims, Deep Learning toolkits, Omniverse, nemo, RAPIDS

Memory Management, Python, Enterprise AI governance, AI evaluation methodologies, Prompt engineering, Autonomous AI workflows, Hallucination mitigation, Tool orchestration, Responsible AI principles, Planning strategies, Response validation, Grounding techniques

Amazon Redshift, Amazon Athena, Redshift Serverless, Iceberg tables, SQL Analytics, Athena, SageMaker Lakehouse, S3 tables, Data Lake architecture

Networking, Storage, Terraform, Kubernetes, Infrastructure as Code, data pipelines, LLMs, AI inference systems, distributed inference, scaling strategies, Cv, recommendation models, GPU-based infrastructure, container orchestration, GPU workload optimization, streaming architectures, high-performance computing, AI ML systems

Python, Pytorch, Digital Twins, AI model training, nims, RAPIDS, Omniverse, Synthetic Data Generation, Generative AI, nemo, Immersive Multimedia