MLops, Gcp, Docker, Distributed Systems, Azure, Kubernetes, AWS, feature management, experiment tracking, machine learning systems, ML platform architecture, cloud native architectures, model training, data platforms, pipeline orchestration, data ingestion, model lifecycle management, model monitoring

data engineering , Python, Tensorflow, Deep Learning, Cloud Computing, Model Deployment

Neural network architectures, On-premises infrastructure, Deep learning frameworks, Image processing techniques, Cloud AI services, Chatbot development, Generative AI models

Machine Learning, Containers, AI EC2 Instances, MLOps best practices, Generative AI, AI Platforms, AI Services, AI Frameworks, Amazon Bedrock, SparkML

Sql, Data Cleaning, Tensorflow, Python, Nlp, Pytorch, Api Development, outlier handling, AI ML services, Deployment of GenAI applications, Prompt design, Generative AI techniques and tools, ETL methods, Big Data technologies like Spark, GenAI Fundamentals, Azure cloud platform, Agentic AI, data imputation

Large Language Models (LLMs), TensorFlow / PyTorch, Deep Learning, Neural Networks, Nlp, Python, Generative AI, Chatbot Development, AI Model Deployment, Cloud AI Services, ML Pipelines

amazon emr , data wrangling , Sql, AWS, Pytorch, Deep Learning, Python, Tensorflow, Distributed Computing, Pyspark, Machine Learning, Sagemaker

Gcp, Sql, Deep Learning, Machine Learning, MLops, AWS, Threat Intelligence, Cursor, Siem, Python, Nosql, Azure, Vulnerability Management, Claude, SOAR, Ai, GenAI, Data Lakes, Model Context Protocol, Agentic AI, GitHub Copilot