Training areas
Programs across the enterprise cloud, data, and AI stack.
Each service can run as a standalone workshop, a cohort-based upskilling program, or a blended rollout with labs and assessment support.
AWS Corporate Training
Architecting on AWS, DevOps Engineering, Security Engineering, Data Engineering, Developing on AWS, SysOps, and Amazon SageMaker. Role-mapped for architects, developers, DevOps engineers, security teams, and data teams.
AWS Training Programs
Databricks Training
Databricks Lakehouse Fundamentals, Data Engineering with Databricks, Apache Spark Programming, MLflow, MLOps, Generative AI on Databricks, and Databricks SQL.
Databricks Programs
Generative AI Training
AI awareness for all employees, practitioner programs for technical cohorts, and manager tracks covering GenAI fundamentals, RAG architecture, agentic AI, LLMOps, and responsible AI.
GenAI Programs
Machine Learning Training
Applied machine learning for enterprise teams, including ML foundations, model evaluation, feature engineering, production workflows, and adjacent engineering roles.
View Catalog
Data Engineering Training
Lakehouse architecture, Delta Lake pipelines, Apache Spark, orchestration, streaming data, governance, and data quality engineering for modern enterprise data platforms.
Data Engineering Programs
Labs as a Service
Pay-per-lab guided cloud sandboxes for AWS, Databricks, GenAI, ML, and Data Engineering. Use labs after training, during onboarding, or as standalone skill validation.
Explore Labs
Virtual Proctoring
Browser-based integrity monitoring, tab tracking, image capture review, violation reporting, and controlled remote assessments after training programs.
See Proctoring