Algorithms, Kafka, Hipaa, Tensorflow, React, Pytorch, Docker, data structures, Python, AWS, Hadoop, Node.js, Django, Gcp, Hl7, Spark, Azure, Kubernetes, Airflow, software engineering best practices, scikit-learn, generative AI technologies, FHIR, Vector Databases, LLM’s, RAG architectures, transfer learning, prompt engineering, healthcare data standards

data engineering , Machine Learning, Sql, Deep Learning, Tensorflow, MLops, Pytorch, Data Analytics, Python, Computer Vision, GenAI, CNNs, Transformer-based architectures

Sql, Nosql, Tensorflow, Azure ML, Numpy, Pandas, Pytorch, Docker, XGBoost, Spark, Kubernetes, Python, R², scikit-learn, LightGBM, RMSE, MAE, AWS SageMaker, Google Vertex AI

Python, LangChain, vector search, LLMs, FAISS, RAG, Transformers, Pinecone

Machine Learning, Natural Language Processing, Pytorch, Python, Tensorflow, Deep Learning, Agentic AI, LLMs, HuggingFace

ECS, Kubernetes, Python, pgvector, RAG systems, Qdrant, Vector databases, Fast API, LangGraph, SageMaker, ECR, AWS stack, Conversational AI, DSPy, ML systems, Amazon Bedrock

Databases, Java, Apis, Kafka, Hana, Distributed Systems, Postgres, Python, Go, GRPC, CI CD pipelines, AI ML frameworks

Numpy, Pandas, Pytorch, Docker, Python, AWS, Airflow, agentic design patterns, scikit-learn, ML data libraries, MLflow, prompt design, LLM core concepts