Exam Review: Designing and Implementing a Data Science Solution on Azure (DP-100)

48mAdvanced2022-04-06

Authors

Henrica Makulu

Data Scientist, Trainer, Mentor, TechWomen 2022 Emerging Leader

Course details

Passing the Microsoft DP-100 exam certifies you as an Azure Data Scientist Associate, which could come in handy at your current job, but also make you more competitive if you’re looking for a new one. In this course, data scientist Henrica Makulu shows you what it takes to tackle the DP-100 Designing and Implementing a Data Science Solution on Azure certification exam.

Get an overview of each domain of the exam and the basic concepts you need to know before you take it. Learn about the specific tasks that align with the exam’s technical objectives, such as creating and managing resources for machine learning, running experiments and training models, and deploying and operationalizing responsible machine learning solutions. Develop your skills along the way using Azure Machine Learning and Azure Databricks, gathering insights and study tips from Henrica to make sure you’re ready on the day of the exam.

Skills covered

Database DevelopmentDatabase ManagementAzureNetwork AdministrationCloud PlatformsCert PrepNetwork and System AdministrationCloud ComputingMicrosoftSoftware Development

Concepts

0. Introduction

01 - Tips for the Azure DP-100 exam
02 - DP-100 overview
03 - What you should know

1. Creating Machine Learning Models

04 - Create machine learning models - Domain overview
05 - Data exploration and analysis using Python
06 - What are machine learning models
07 - Understanding the types of machine learning models
08 - Machine learning model training and evaluation

2. Using Visual Tools to Create Machine Learning Models with Azure Machine Learning

09 - ML model creation with visual tools - Domain overview
10 - Understanding automated machine learning
11 - Understanding Azure Machine Learning designer
12 - Train and evaluate models with Azure Machine Learning designer

3. Building and Operating Machine Learning Solutions with Azure Machine Learning

13 - ML solutions with Azure Machine Learning - Domain overview
14 - Introduction to the Azure Machine Learning SDK
15 - Working with data in Azure Machine Learning
16 - Training a machine learning model
17 - Machine learning at scale
18 - Understanding hyperparameters
19 - Understanding privacy and ethics in Azure Machine Learning
20 - Understanding model predictions
21 - Monitoring and security in Azure Machine Learning

4. Building and Operating Machine Learning Solutions with Azure Databricks

22 - ML solutions with Azure Databricks - Domain overview
23 - Introduction to Azure Databricks
24 - Preparing and working with data
25 - Training, managing, and deploying models in Azure Databricks
26 - Tracking experiments in Azure Databricks
27 - Tuning hyperparameters in Azure Databricks
28 - Distributed deep learning

Conclusion

29 - Additional resources for DP-100 preparation
30 - Tips for exam day