Data Science | Batangas State University, The National Engineering University

42 Hours

Hybrid

Overview

Dive into Data Science by exploring the synergy of statistics, machine learning, and data visualization. This course is tailored for Azure Data Scientists, emphasizing the intricacies of Azure Machine Learning. From data assessment and model training to Responsible AI principles and deployment, the curriculum offers comprehensive insights. Participants should have a foundational understanding of data science concepts. Practical training in Azure storage, Python SDK (v2), and MLflow ensures readiness for real-world Azure-based data science tasks.

Total hours

Total: 42 Hours

Sync Hands-on/Lecture: 22 Hours
Async Learning: 10 Hours
Assessment: 10 hours

Course outline

Module 1: Understand data science for machine learning
Module 2: Design a machine learning solution
Module 3: Explore the Azure Machine Learning workspace
Module 4: Make data available in Azure Machine Learning
Module 5: Work with compute in Azure Machine Learning
Module 6: Automate machine learning model selection with Azure Machine Learning
Module 7: Use notebooks for experimentation in Azure Machine Learning
Module 8: Train models with scripts in Azure Machine Learning
Module 9: Optimize model training in Azure Machine Learning
Module 10: Manage and review models in Azure Machine Learning
Module 11: Deploy and consume models with Azure Machine Learning
Module 12: Design a machine learning operations (MLOps) solution
Module 13: Certification

What you'll learn

Manage Azure Machine Learning resources and assets using tools like Python SDK (v2).
Build and operate pipelines using the no-code designer in Azure Machine Learning studio.
Evaluate featurization techniques and algorithms with Automated Machine Learning.
Implement MLOps for model monitoring, tracking, and retraining using MLflow.