data engineering , Ml, Data Governance, Data Architecture, MLops, Generative AI, Cloud-native architectures, Ai, Edge AI

snowflake , Machine Learning, Sklearn, Greenplum, Netezza, Pandas, Pytorch, Gcp, MLops, Spark, Microsoft Azure, Python, AWS, LangChain, Airflow, Generative AI, Feature Store, Teradata, Model Explainability, Model Deployment, E data, dbt, Observability

snowflake , Machine Learning, Sklearn, Greenplum, Netezza, Pandas, Gcp, Pytorch, MLops, Spark, Microsoft Azure, Python, AWS, LangChain, Airflow, Generative AI, Feature Store, Teradata, Model Explainability, Model Deployment, dbt, Observability

Ml, Spark, Kafka, data pipelines, event-driven systems, Ai, Fraud Analytics, anomaly detection, Flink

Ml, Spark, Kafka, Cybersecurity, Ai, Fraud Analytics, anomaly detection, Flink

Coupa, Microsoft 365, Typescript, MLops, Microservices, Enterprise Integration, Workday, SAP, AWS, Oracle, Python, Servicenow, Apis, Ariba, Microsoft Azure, Google Cloud Platform, LLMs, Cloud-native Platforms, GenAI, LLMOps, Event-driven Patterns, Automation Platforms, AI ML Solution Architecture, RAG, Salesforce, Workflow Orchestration, Document Management Platforms, Agentic AI, Dynamics, Enterprise SaaS

Java, Unix, Github, Sql, Jenkins, Technical Documentation, Bitbucket, Gitlab, Linux Shell Scripting, Python, Aldon, Data Mapping, Process Mapping, CI CD pipelines

probabilistic models , Tensorflow, Deep Learning, Numpy, Pandas, MLops, Pytorch, Python, Scikit-learn, reinforcement learning, classical statistical methods, XAI methodologies

Sql, Pytorch, Java, Nosql, Python, Kubernetes, Tensorflow, Docker, MLflow, KServe, R, Scikit-learn

Data Science, Ai, AI Frameworks, Programming Basics