Real-world projects from industry experts
With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.
Strengthen your machine learning skills and build practical experience by training, validating, and evaluating models using Azure Machine Learning.
At 5-10 hrs/week
Get access to classroom immediately on enrollment
In this program, students will enhance their skills by building and deploying sophisticated machine learning solutions using popular open source tools and frameworks, and gain practical experience running complex machine learning tasks using the built-in Azure labs accessible inside the Udacity classroom.
Prior experience with Python, Machine Learning, and Statistics
Machine learning is a critical business operation for many organizations. Learn how to configure machine learning pipelines in Azure, identify use cases for Automated Machine Learning, and use the Azure ML SDK to design, create, and manage machine learning pipelines in Azure.
This course covers a lot of the key concepts of operationalizing machine learning, from selecting the appropriate targets for deploying models, to enabling Application Insights, identifying problems in logs, and harnessing the power of Azure’s Pipelines. All these concepts are part of core DevOps pillars that will allow you to demonstrate solid skills for shipping machine learning models into production.
The program capstone gives you the opportunity to use the knowledge you have obtained from this Nanodegree program to solve an interesting problem. You will have to use Azure’s Automated ML and HyperDrive to solve a task. Finally, you will have to deploy the model as a webservice and test the model endpoint.
With real-world projects and immersive content built in partnership with top-tier companies, you’ll master the tech skills companies want.
On demand help. Receive instant help with your learning directly in the classroom. Stay on track and get unstuck.
You’ll have access to Github portfolio review and LinkedIn profile optimization to help you advance your career and land a high-paying role.
Tailor a learning plan that fits your busy life. Learn at your own pace and reach your personal goals on the schedule that works best for you.
We provide services customized for your needs at every step of your learning journey to ensure your success.
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Noah Gift teaches and consults at top universities and companies globally, including Duke and Northwestern. His areas of expertise are Machine Learning, MLOps, A.I., Data Science, and Cloud Architecture. Noah has authored several bestselling books, including <em>Python for DevOps</em>.
Alfredo Deza is a passionate software engineer, avid open source developer, Vim plugin author, photographer, and former Olympic athlete. He has rebuilt company infrastructure, designed shared storage, and replaced complex build systems, always in search of efficient and resilient environments.
Erick Galinkin is a hacker and computer scientist, leading research at the intersection of security and artificial intelligence at Rapid7. He has spoken at numerous industry and academic conferences on topics ranging from malware development to game theory in security.
Soham is an Intel® Software Innovator and a former Deep Learning Researcher at Saama Technologies. He is currently a Masters by Research student at NTU, Singapore. His research is on Edge Computing, IoT and Neuromorphic Hardware.
Strengthen your machine learning skills and gain practical experience by training, validating, and evaluating machine learning models for Microsoft Azure.
On average, successful students take 3 months to complete this program.
Businesses everywhere are mobilizing to create and implement the AI strategies that will transform industries in coming years, and they need engineers to do it. Data from LinkedIn indicates that AI specialists are among the most sought after roles that companies are looking for, with a 74 percent annual growth rate in hiring over the last four years. To stay in-demand at companies on the cutting edge of technology, engineers should prioritize developing their machine learning skill set.
The Machine Learning Engineer for Microsoft Azure Nanodegree Program, built in collaboration with Microsoft, offers you the chance to build the practitioner-level skills that companies across industries need. In the program, you’ll strengthen your machine learning skills by training, validating, and evaluating models using Azure Machine Learning, and complete a series of three real-world projects to add to your portfolio.
Students in the program will learn about machine learning algorithms and crucial deployment techniques, and will be equipped to fill roles at companies seeking machine learning engineers and AI specialists. These skills can also be applied in roles at companies that are looking for data scientists to introduce machine learning techniques into their organization.
The Machine Learning Engineer for Microsoft Azure Nanodegree program is geared towards people who are interested in building and deploying a machine learning product or application. The program is a good fit for...
There is no application. This Nanodegree program accepts everyone, regardless of experience and specific background.
A well-prepared learner will meet the following prerequisites:
To prepare, we recommend the Introduction to Machine Learning and AI Programming with Python programs, to build your comfortability with ML concepts and using python in an AI context.
The Machine Learning Engineer for Microsoft Azure Nanodegree program is comprised of content and curriculum to support three (3) projects. We estimate that students can complete the program in three (3) months working 5-10 hours per week.
Each project will be reviewed by the Udacity reviewer network. Feedback will be provided and if you do not pass the project, you will be asked to resubmit the project until it passes.
Access to this Nanodegree program runs for the length of time specified above. If you do not graduate within that time period, you will continue learning with month-to-month payments. See the Terms of Use and FAQs for other policies regarding the terms of access to our Nanodegree programs.
Please see the Udacity Program FAQs for policies on enrollment in our programs.
For this program, you will need a desktop or laptop computer running recent versions of Windows, Mac OS X, or Linux, and an unmetered broadband Internet connection. There are no additional hardware or software requirements for this program, other than those outlined on Udacity's general Technology Requirements page.