By: Daniel Calbimonte | Updated: 2017-08-03 | Comments (5) | Related: More > Professional Development Certifications
Problem
In this tip we cover information you can use to learn more about Azure Machine Learning and Data Science for exam 70-774.
Solution
This time we will talk about Microsoft certification 70-774. It is about Cloud Data Science and Machine Learning. With Azure, you can connect and analyze information from Azure SQL, Azure SQL Data Warehouse or many other sources.
Who should take this exam?
This exam is oriented to DBAs, Data Scientist, Data Architects, Data Analysts, Data Developers or professional who want to learn or who want to be certified in Data Analysis.
What is a data scientist?
It is a new job for people to analyze data using scientific methods to extract knowledge from data working with relational or big data.
What Microsoft Certifications are related to this exam?
This exam is mandatory to get the MCSA in Machine Learning (Microsoft Certified Solutions Associate). You can also use is for a MCP (Microsoft Certified Professional) with this exam.
Is the exam difficult?
If you do not have previous experience with Machine Learning, Azure, R, Python, Big Data this exam is very difficult.
What is Machine Learning (ML)?
It is the ability to learn without programming. Usually ML analyzes data and solves problems using algorithms. Azure now offers Machine Learning services with very sophisticated algorithms.
Which books would you recommend for this exam?
The following may be useful:
- Python Machine Learning
- Introduction to Machine Learning with Python: A Guide for Data Scientists
- Data Science from Scratch: First Principles with Python
- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
- The Book of R: A First Course in Programming and Statistics
- Beginning SQL Server R Services: Analytics for Data Scientists
- R in Action: Data Analysis and Graphics with R
- The Art of R Programming: A Tour of Statistical Software Design
- R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics
- Advanced R (Chapman & Hall/CRC The R Series)
- R Packages: Organize, Test, Document, and Share Your Code 1st Edition
- R for Data Science: Import, Tidy, Transform, Visualize, and Model Data 1st
- Microsoft Azure Essentials Azure Machine Learning
- Microsoft Azure Machine Learning with Stock Data
- Practical Data Science with Hadoop and Spark: Designing and Building Effective Analytics at Scale (Addison-Wesley Data & Analytics)
- Mastering Azure Analytics: Architecting in the Cloud with Azure Data Lake, HDInsight, and Spark
- Big Data Analytics with Microsoft HDInsight in 24 Hours, Sams Teach Yourself
- HDInsight Essentials - Second Edition
- Processing Big Data with Azure HDInsight: Building Real-World Big Data Systems on Azure HDInsight Using the Hadoop Ecosystem
- Microsoft Big Data Solutions
- HDInsight: Microsoft’s Cloud Hadoop
Are there some courses for this exam?
Yes, the following courses can be useful:
- Data Science and Machine Learning with Python
- Regression Machine Learning with R
- Machine learning courses
- Udemy Big Data Courses
- R courses
- Python courses
- Big Data Analytics with HDInsight: Hadoop on Azure
- Implementing Big Data Analysis
- Design and Implement Big Data & Advanced Analytics Solutions
Can you provide some links to study, for this exam?
Yes, here are some useful links for each section of the exam:
Prepare Data for Analysis in Azure Machine Learning and Export from Azure Machine Learning
- Import and export data to and from Azure Machine Learning
- Import data into Azure Machine Learning Studio from various online data sources with the Import Data module
- Perform advanced analytics with Azure Machine Learning using data from an on-premises SQL Server database
- Import your training data into Azure Machine Learning Studio from various data sources
- Explore and summarize data
- Cleanse data for Azure Machine Learning
- Perform feature engineering
- Join Data
- Data Transformation / Manipulation
- Feature engineering in data science
- Feature Selection Modules
- Principal Component Analysis
- Edit Metadata
Develop Machine Learning Models
- Select an appropriate algorithm or method
- How to choose algorithms for Microsoft Azure Machine Learning
- Machine learning algorithm cheat sheet for Microsoft Azure Machine Learning Studio
- Extend your experiment with R
- Author custom R modules in Azure Machine Learning
- Execute Python machine learning scripts in Azure Machine Learning Studio
- Machine Learning / Initialize Model / Clustering
- Initialize and train appropriate models
- Validate models
Operationalize and Manage Azure Machine Learning Services
- Deploy models using Azure Machine Learning
- Deploy an Azure Machine Learning web service
- Walkthrough Step 5: Deploy the Azure Machine Learning web service
- Use Azure Machine Learning Web Service Parameters
- How to Build a Recommendation Engine using Azure Machine Learning and Azure Mobile Services
- Train Matchbox Recommender
- Publishing Guidelines and Examples
- Manage Azure Machine Learning projects and workspaces
- Azure Machine Learning - Your first experiment
- Machine learning tutorial: Create your first data science experiment in Azure Machine Learning Studio
- Create and share an Azure Machine Learning workspace
- Manage an Azure Machine Learning workspace
- Microsoft Azure Notebooks
- Cortana Intelligence and Machine Learning Blog
- Consume Azure Machine Learning models
- How to consume an Azure Machine Learning Web service
- Retrain Machine Learning models programmatically
- Azure Machine Learning frequently asked questions: Billing, capabilities, limitations, and support
- Excel Add-in for Azure Machine Learning web services
- Consuming an Azure Machine Learning Web Service from Excel
- Publishing an Azure Machine Learning service into the Azure Marketplace
- Consume exemplar Cognitive Services APIs
Use Other Services for Machine Learning
- Build and use neural networks with the Microsoft Cognitive Toolkit
- Streamline development by using existing resources
- Perform data sciences at scale by using HDInsights
- Overview of data science using Spark on Azure HDInsight
- Set up clusters in HDInsight with Hadoop, Spark, Kafka, and more
- Spark SQL Programming Guide
- Spark SQL Reference
- Introduction to Spark on HDInsight
- Map-Reduce for Machine Learning on Multicore
- Introduction to R Server and open-source R capabilities on HDInsight
- Quickstart tutorial for the R programming language for Azure Machine Learning
- Using R in Azure Machine Learning Studio
- Perform database analytics by using SQL Server R Services on Azure
- Azure SQL Server 2016 VM
- Azure VM is the best platform for SQL Server 2016
- Microsoft Azure, our first steps to migrate data
- Provision a SQL Server virtual machine in the Azure Portal
- Enabling sp_execute_external_script to run R scripts in SQL Server 2016
- Using R Code in Transact-SQL
- SQL Server R Tutorials
Next Steps
Machine learning in Azure is a very exciting new topic. It works with SQL Server, HDInsight and it is a very powerful tool. The exam is very difficult, but the topic is very interesting and new.
For more information about this exam, refer to these links:
- Exam 70-774
- Perform Cloud Data Science with Azure Machine Learning
- 774: Perform Cloud Data Science with Azure Machine Learning
- 70-774 Perform Cloud Data Science with Azure Machine Learning Certification Exam
About the author
Daniel Calbimonte is a Microsoft SQL Server MVP, Microsoft Certified Trainer and 6-time Microsoft Certified IT Professional. Daniel started his career in 2001 and has worked with SQL Server 6.0 to 2022. Daniel is a DBA as well as specializes in Business Intelligence (SSIS, SSAS, SSRS) technologies.This author pledges the content of this article is based on professional experience and not AI generated.
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Article Last Updated: 2017-08-03
