Designing and Implementing a Data Science Solution on Azure (DP 100)

This masterclass gives you a high-impact look at how data scientists can operate machine-learning solutions at cloud scale using Azure services. You’ll see how to manage data ingestion and preparation, train and deploy models, monitor them in production   all with hands-on insights borrowed from the DP-100 course. The underlying course is built for data scientists with Python and ML framework experience, and this session will help you bridge to that next capability. (Torque IT)

Why Attend:

• Learn how to provision an Azure Machine Learning workspace and manage ML assets (data, compute, models)  core skills for modern data science. (Torque IT)
• Understand experiments, pipelines, model deployment, batch & real-time inferencing the end-to-end lifecycle of ML in Azure. (Torque IT)
• Gain exposure to responsible ML practices: fairness, interpretability, data drift monitoring   something many professionals overlook. (Torque IT)
• Perfect for: Data Science Engineers, Data Engineers, Power BI Analysts who want to level-up with ML capabilities.

Key Outcomes / What You’ll Walk Away With:

• A clear blueprint for how to build and deploy ML solutions in Azure.
• Insight into how Azure ML workflows differ from traditional on-prem setups.
• Practical take-aways you can apply right away (even if you don’t yet take the full DP-100 course).
• Understanding of how this session maps to the full course/exam path.

Call to Action (CTA):
Register now for free to secure your place in this 90-minute masterclass and start advancing your data & AI skill-set.