Deep Learning, MLops, Gcp, Docker, Kubernetes, Python, LangChain, Generative AI, RAG-based systems, reinforcement learning, BigQuery ML, Vertex AI, LlamaIndex

record linkage , Numpy, Nlp, Docker, XGBoost, Flask, Python, Sql, Pandas, FastAPI, embeddings, scikit-learn, fuzzy matching, Levenshtein, model evaluation, RAG fundamentals, LLM GenAI, sentence-transformers, model deployment, entity resolution, prompt engineering, Jaro-Winkler, REST API serving, vector similarity search, text embeddings

Tensorflow, Sql, Apache Spark, Pyspark, Kafka, MLops, Pytorch, Kubernetes, Python, Docker, Scala, XGBoost, LightGBM

Nlp, Docker, Python, Api Development, Sql, Deep Learning, REST, Neo4j, FastAPI, Kubernetes, Agentic AI architectures, RAG systems, Transformer architecture, Azure AI Foundry, Microservices architecture, Tool Calling mechanisms, LangChain, Generative AI, LLMOps practices, MCP Model Context Protocol, CI CD pipelines, LLM implementation, Multi-agent systems, LlamaIndex, hyperscaler offerings

Nlp, Gcp, MLops, Docker, PostgreSQL, Elasticsearch, Elk Stack, Azure, Python, AWS, Generative AI

probability , Sql, Power Bi, Python, MATLAB, Tableau, Machine Learning, R, Statistics, metrics design

Sql, Tensorflow, Pandas, Python Programming, Numpy, Pytorch, Scipy, LLMs, model deployment workflows, scikit-learn, statsmodels, vector databases, GenAI technologies, RAG, LangChain, MLOps practices, prompt engineering