Microsoft Certified: Azure Data Scientist Associate (SF)
Training Provider: NTUC LEARNINGHUB PTE. LTD.
Course Reference: TGS-2026063030
S$1,300
Original: S$2,600
Save S$1,300
About This Course
This 5-day instructor-led course provides an in-depth exploration of Azure’s machine learning capabilities. Covering the end-to-end data science lifecycle, participants will learn how to prepare data, train models, deploy them at scale, and monitor their performance. Learners gain hands-on experience with Azure Machine Learning Service, Azure Machine Learning Studio, and Azure AI Foundry, covering advanced topics like automated ML, hyperparameter tuning, responsible AI, and generative AI applications.
What You'll Learn
LO1: Analyse AI application strengths and limitations, and set up core Azure Machine Learning components to support model evaluation.
LO2: Assess AI solution feasibility for products and maintenance, and use Azure Machine Learning SDK and notebooks to build and manage experiments for evaluation.
LO3: Evaluate AI applications using algorithm principles, and run AutoML tasks with MLflow tracking to compare performance and limitations.
LO4: Analyse how algorithm design impacts efficiency, and build automated pipelines with AutoML and performance tracking for data preparation, training, and deployment.
LO5:Analyse AI algorithms, register models, and use Responsible AI dashboards to evaluate effectiveness, interpretability, and fairness.
LO6: Assess AI-driven improvements in product development and operationalise solutions by registering models, deploying pre-trained models, and building Prompt Flow RAG applications.
LO2: Assess AI solution feasibility for products and maintenance, and use Azure Machine Learning SDK and notebooks to build and manage experiments for evaluation.
LO3: Evaluate AI applications using algorithm principles, and run AutoML tasks with MLflow tracking to compare performance and limitations.
LO4: Analyse how algorithm design impacts efficiency, and build automated pipelines with AutoML and performance tracking for data preparation, training, and deployment.
LO5:Analyse AI algorithms, register models, and use Responsible AI dashboards to evaluate effectiveness, interpretability, and fairness.
LO6: Assess AI-driven improvements in product development and operationalise solutions by registering models, deploying pre-trained models, and building Prompt Flow RAG applications.
Entry Requirements
• The candidate should hold a diploma and have at least 2 years of experience working in an IT-related role.
• Candidates who do not meet the above requirements will be assessed on case to case basis.
Course Details
Back to All Courses
Note: To apply for this course, visit or contact the training provider directly.
More Courses from NTUC LEARNINGHUB PTE. LTD.
• Evaluate organisational requirements and business needs for cloud solutions
• Evaluate new a...
• Evaluate organisational requirements and business needs for cloud solutions
• Evaluate new a...
• Discuss foundation concepts of cybersecurity principles.
• Explain how organizations respond ...