Microsoft Certified: Azure Data Scientist Associate (DP-100)

At Firebrand, we were awarded the Microsoft Solutions Partner for Data & AI (Azure) badge in recognition of our expertise in delivering quality solutions in this specialised business area.

Gain the skills you need to become a Microsoft Azure Data Scientist Associate in just 3 days. You'll learn how best to develop, evaluate, manage and deploy models that solve business problems with Azure technology.

Improve on your data modelling, feature engineering skills, and learn how to apply Azure's machine learning methods to manipulate and analyse key data for your business.

You'll learn the official curriculum fast as you're taught by Microsoft Certified Trainers. Firebrand's unique Lecture | Lab | Review methodology means you'll practice everything you learn in a distraction-free environment, and return to the office certified.

On this Microsoft Azure Data Scientist Associate course, you will learn how to:

• Quantify the business problem
• Execute Exploratory Data Analysis (EDA)
• Perform feature extraction and selection with the use of various algorithms
• Develop and evaluate models based on algorithmic approaches

You will be prepared for and sit exam DP-100 at the Firebrand Training Centre during the course. This is covered by your Certification Guarantee - pass first time or train again free.

If you're interested in developing your skills as an Azure Data Scientist Associate, then this course is ideal for you.

Course DP-100T01-A: Designing and Implementing a Data Science Solution on Azure

• Module 1: Introduction to Azure Machine Learning
• Lab: Creating an Azure Machine Learning Workspace
• Lab: Working with Azure Machine Learning Tools

• Module 2: No-Code Machine Learning with Designer
• Lab: Creating a Training Pipeline with the Azure ML Designer
• Lab: Deploying a Service with the Azure ML Designer

• Module 3: Running Experiments and Training Models
• Lab: Running Experiments
• Lab: Training and Registering Models

• Module 4: Working with Data
• Lab: Working with Datastores
• Lab: Working with Datasets

• Module 5: Compute Contexts
• Lab: Working with Environments
• Lab: Working with Compute Targets

• Module 6: Orchestrating Operations with Pipelines
• Lab: Creating a Pipeline
• Lab: Publishing a Pipeline

• Module 7: Deploying and Consuming Models
• Lab: Creating a Real-time Inferencing Service
• Lab: Creating a Batch Inferencing Service

• Module 8: Training Optimal Models
• Lab: Tuning Hyperparameters
• Lab: Using Automated Machine Learning

• Module 9: Interpreting Models
• Lab: Reviewing Automated Machine Learning Explanations
• Lab: Interpreting Models

• Module 10: Monitoring Models
• Lab: Monitoring a Model with Application Insights
• Lab: Monitoring Data Drift

Before attending this course, you should have technical knowledge equivalent to:

• Azure Fundamentals certification

As part of your accelerated course, you'll sit the following exam at the Firebrand Training centre, covered by your Certification Guarantee:

• Designing and Implementing a Data Science Solution on Azure
• Exam code: DP-100
• Domains:
1. Set up an Azure Machine Learning workspace (30-35%)
2. Run experience and train models (25-30%)
3. Optimise and manage models (25-25%)
4. Deploy and consume models (20-25%)