Algorithms, Hadoop, Kafka, Node.js, Tensorflow, Django, React, Gcp, Pytorch, Docker, Spark, data structures, Azure, Kubernetes, Python, AWS, Airflow, scikit-learn, transfer learning, generative AI technologies, prompt engineering, Vector Databases, RAG architectures

Git, Docker, Python, data pipelines, Linux-based systems, AWS ML GenAI services, RAG, LLM-based architectures, ML GenAI models

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

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

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

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

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