Start with AI awareness, implementation readiness, AWS corporate training, Databricks enablement, or AWS data engineering depending on the team objective.
Explore cohort-based training in AWS, Databricks, Generative AI, AI, Machine Learning, and Data Engineering for engineering, data, platform, and leadership teams.
Start with awareness, build practitioner capability, and equip managers to lead adoption. Then expand into role-based AWS, Databricks, and data engineering tracks.
A focused GenAI awareness program built for BFSI teams. Covers Generative AI, RAG, Agentic AI, and prompt engineering using real banking, insurance, and lending examples. Designed for both technical and non-technical stakeholders.
Hands-on implementation readiness for engineering, data, and AI teams. Bridges theory and execution with advanced case studies covering model deployment, evaluation, monitoring, and production AI workflows.
Lead AI adoption without being technical. Equips managers, department heads, and L&D leaders with the vocabulary, governance frameworks, vendor evaluation tools, and a 90-day team adoption roadmap.
All programs are instructor-led, role-based, cohort-based, and available with optional assessments and virtual proctoring.
Cloud fundamentals, solutions architecture, DevOps, data, analytics, and ML on AWS. Delivered by an AWS Authorized Instructor Champion.
Lakehouse architecture, pipeline orchestration, streaming, governance, and role-based data platform enablement.
GenAI fundamentals, Amazon Bedrock, SageMaker, RAG architecture, agentic patterns, and prompt engineering.
ML pipeline design, model training and evaluation, deployment, monitoring, and MLOps for enterprise teams.
Pipeline design, batch and streaming patterns, orchestration tooling, and data platform architecture.
Use the catalog when the team needs practical upskilling tied to execution, certification, migration, or measurable readiness.
Best for organizations adopting AWS, modernizing delivery, or expanding AI and data platform capabilities.
Best for Databricks adoption, data engineering acceleration, pipeline design, governance, and ML workflow enablement.
Best for AI awareness, role-based upskilling, internal readiness measurement, and stakeholder visibility with optional assessments.
Start with a pilot cohort, a focused workshop, or a proctored readiness assessment to validate fit before expanding.
Choose the track, align the cohort, then add assessments and optional proctoring for measurable skill validation.
Start with AI awareness, implementation readiness, AWS corporate training, Databricks enablement, or AWS data engineering depending on the team objective.
Align the cohort by role, technical depth, team size, and whether the program should run virtually, onsite, or as a multi-session engagement.
Use pre/post assessments and virtual proctoring when you need readiness visibility, certification support, or stronger stakeholder reporting.
Tell us your team, topic, and timeline. We will recommend the right cohort plan, assessment path, and next step.