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

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

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

Apis, Google Cloud Platform, Microservices, Enterprise Integration, Typescript, MLops, Terraform, Microsoft Azure, Kubernetes, Python, Azure DevOps, AWS, LLMOps, automation platforms, GitLab CI, GitHub Actions, RAG, event-driven architecture, observability

technology governance , Enterprise Architecture, Machine Learning, Generative AI, Agentic AI, Ai

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

Data Science, Ai, AI Frameworks, Programming Basics