Specialise in azure to unlock strategic responsibilities within the Cloud Infrastructure and DevOps Engineer pathway. Develop practical mastery through Datastat bootcamps and workshops.
Critical capability for the role with dedicated resources.
Connect skill learning to career progression outcomes.
Blended delivery with flexible scheduling windows.
Enrol in immersive programmes that translate azure expertise into measurable results for your team.

Training Course on Cloud Artificial Intelligence Platforms (AWS, Azure, GCP) provides a deep dive into the leading cloud AI ecosystems Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) ? equipping participants with the essential knowledge and practical skills to leverage their cutting-edge AI services
Training Course on Cloud Artificial Intelligence Platforms (AWS, Azure, GCP) provides a deep dive into the leading cloud AI ecosystems Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) ? equipping participants with the essential knowledge and practical skills to leverage their cutting-edge AI services
Datastat blends expert mentorship, project simulations, and certification support to accelerate azure proficiency.

Training Course on Cloud Data Platforms for Data Scientists (Unified Course) is meticulously designed to bridge the gap between theoretical knowledge and practical application, focusing on real-world case studies and hands-on labs
Training Course on Cloud Data Platforms for Data Scientists (Unified Course) is meticulously designed to bridge the gap between theoretical knowledge and practical application, focusing on real-world case studies and hands-on labs

Training Course on Cost Optimization in MLOps: Managing cloud infrastructure and compute costs for ML workloads delves deep into the intersection of MLOps best practices and cloud financial management. Participants will gain actionable insights into identifying cost inefficiencies, implementing governance policies, and adopting a FinOps for ML mindset.
Training Course on Cost Optimization in MLOps: Managing cloud infrastructure and compute costs for ML workloads delves deep into the intersection of MLOps best practices and cloud financial management. Participants will gain actionable insights into identifying cost inefficiencies, implementing governance policies, and adopting a FinOps for ML mindset.