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Erick Galinkin,
Noah Gift,
Soham Chatterjee,
and
Alfredo Deza
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...
Read more
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...
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/l5sqbi/machine
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What's inside
Syllabus
This is a welcome lesson. In this lesson, you will get an overview of the course
In this lesson, you will learn about how to authorize operations for machine learning and deploy machine learning models to Azure.
Read more
Syllabus
This is a welcome lesson. In this lesson, you will get an overview of the course
In this lesson, you will learn about how to authorize operations for machine learning and deploy machine learning models to Azure.
Read more
In this lesson, you will learn about how to consume deployed service and load-test the endpoint.
In this lesson, you will learn how to create a batch inference pipeline, publish a pipeline and consume the pipeline endpoint.
In this project, you will continue to work with the Bank Marketing dataset. You will use Azure to configure a cloud-based machine learning production model, deploy it, and consume it.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores real-world machine learning operations, which is standard in the industry
Taught by Erick Galinkin, Noah Gift, Soham Chatterjee, Alfredo Deza, who are recognized for their work in machine learning
Develops skills for deploying models, enabling Application Insights, identifying problems in logs, and harnessing the power of Azure’s Pipelines, which are core skills for DevOps engineers
Explores Azure’s Pipelines, which is highly relevant to DevOps engineers
Builds a strong foundation for beginners in machine learning operationalization
It requires learners to come in with some background knowledge in machine learning
Offered through Udacity, which has a strong reputation for online education
Examines key concepts of machine learning operationalization, which is a rapidly growing industry trend
Save this course
Save Machine Learning Operations to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Machine Learning Operations with these
activities:
Refresh Azure ARM Template knowledge
Show steps
Understand ARM Templates before starting the course will allow you to setup your infrastructure more quickly and easily.
Browse courses on
Azure Resource Manager
Show steps
-
Read the Azure ARM Template documentation
-
Review existing ARM Templates
-
Create a simple ARM Template
Create a study guide
Show steps
Creating a study guide will help you organize and review the key concepts covered in the course.
Show steps
-
Review the course syllabus and identify key topics
-
Gather notes, assignments, and other materials
-
Summarize and organize the information
-
Review the study guide regularly
Join a study group or online forum
Show steps
Joining a study group or online forum can provide you with opportunities to discuss the course material with other students and get help from experts.
Show steps
-
Search for study groups or online forums related to the course
-
Introduce yourself and ask questions
-
Participate in discussions and share your knowledge
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve practice problems
Show steps
Solving practice problems will help you improve your understanding of the concepts covered in the course and prepare you for the exams.
Show steps
-
Find practice problems online or in textbooks
-
Solve the problems on your own
-
Check your answers and identify areas where you need more practice
Develop a machine learning operations plan
Show steps
Creating a machine learning operations plan will help you ensure that your models are deployed and managed effectively.
Show steps
-
Identify the goals and objectives of your machine learning project
-
Define the metrics and KPIs that will be used to measure the success of your project
-
Develop a plan for deploying and managing your models
-
Identify the resources and tools that you will need to implement your plan
-
Create a timeline for implementing your plan
Create a presentation or tutorial on a topic covered in the course
Show steps
Creating a presentation or tutorial will help you deepen your understanding of the topic and share your knowledge with others.
Show steps
-
Choose a topic that you are interested in and that you have a good understanding of
-
Research the topic and gather information
-
Create a presentation or tutorial that is clear, concise, and engaging
-
Share your presentation or tutorial with others
Build a machine learning application
Show steps
Building a machine learning application will allow you to apply the skills you learn in the course to a real-world problem.
Show steps
-
Identify a problem that you want to solve with machine learning
-
Gather data and prepare it for training
-
Train and evaluate a machine learning model
-
Deploy your model and monitor its performance
Refresh Azure ARM Template knowledge
Show steps
Understand ARM Templates before starting the course will allow you to setup your infrastructure more quickly and easily.
Browse courses on
Azure Resource Manager
Show steps
Show steps
Show steps
- Read the Azure ARM Template documentation
- Review existing ARM Templates
- Create a simple ARM Template
Create a study guide
Show steps
Creating a study guide will help you organize and review the key concepts covered in the course.
Show steps
Show steps
Show steps
- Review the course syllabus and identify key topics
- Gather notes, assignments, and other materials
- Summarize and organize the information
- Review the study guide regularly
Join a study group or online forum
Show steps
Joining a study group or online forum can provide you with opportunities to discuss the course material with other students and get help from experts.
Show steps
Show steps
Show steps
- Search for study groups or online forums related to the course
- Introduce yourself and ask questions
- Participate in discussions and share your knowledge
Four other activities
Expand to see all activities and additional details
Show all seven activities
Solve practice problems
Show steps
Solving practice problems will help you improve your understanding of the concepts covered in the course and prepare you for the exams.
Show steps
Show steps
Show steps
- Find practice problems online or in textbooks
- Solve the problems on your own
- Check your answers and identify areas where you need more practice
Develop a machine learning operations plan
Show steps
Creating a machine learning operations plan will help you ensure that your models are deployed and managed effectively.
Show steps
Show steps
Show steps
- Identify the goals and objectives of your machine learning project
- Define the metrics and KPIs that will be used to measure the success of your project
- Develop a plan for deploying and managing your models
- Identify the resources and tools that you will need to implement your plan
- Create a timeline for implementing your plan
Create a presentation or tutorial on a topic covered in the course
Show steps
Creating a presentation or tutorial will help you deepen your understanding of the topic and share your knowledge with others.
Show steps
Show steps
Show steps
- Choose a topic that you are interested in and that you have a good understanding of
- Research the topic and gather information
- Create a presentation or tutorial that is clear, concise, and engaging
- Share your presentation or tutorial with others
Build a machine learning application
Show steps
Building a machine learning application will allow you to apply the skills you learn in the course to a real-world problem.
Show steps
Show steps
Show steps
- Identify a problem that you want to solve with machine learning
- Gather data and prepare it for training
- Train and evaluate a machine learning model
- Deploy your model and monitor its performance
Career center
Learners who complete Machine Learning Operations will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use their knowledge of machine learning and data analysis to extract insights from data. This course will help you to build the skills and knowledge necessary to become a successful Data Scientist. You will learn about 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. This course will also help you to prepare for a career as a Data Scientist by providing you with hands-on experience in deploying and consuming machine learning models.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and implement machine learning models to solve real-world problems. This course can help you build the skills and knowledge necessary to become a successful Machine Learning Engineer. You will learn about 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. This course will also help you to prepare for a career as a Machine Learning Engineer by providing you with hands-on experience in deploying and consuming machine learning models.
Cloud Engineer
Cloud Engineer
Cloud Engineers design, build, and manage cloud computing systems. This course can help you build the skills and knowledge necessary to become a successful Cloud Engineer. You will learn about 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. This course will also help you to prepare for a career as a Cloud Engineer by providing you with hands-on experience in deploying and consuming machine learning models.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course can help you build the skills and knowledge necessary to become a successful Software Engineer. You will learn about 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. This course will also help you to prepare for a career as a Software Engineer by providing you with hands-on experience in deploying and consuming machine learning models.
DevOps Engineer
DevOps Engineer
DevOps Engineers work to bridge the gap between development and operations teams. This course can help you build the skills and knowledge necessary to become a successful DevOps Engineer. You will learn about 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. This course will also help you to prepare for a career as a DevOps Engineer by providing you with hands-on experience in deploying and consuming machine learning models.
Data Analyst
Data Analyst
Data Analysts use their knowledge of data analysis to extract insights from data. This course can help you build the skills and knowledge necessary to become a successful Data Analyst. You will learn about 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. This course will also help you to prepare for a career as a Data Analyst by providing you with hands-on experience in deploying and consuming machine learning models.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business and technology to improve business processes. This course can help you build the skills and knowledge necessary to become a successful Business Analyst. You will learn about 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. This course will also help you to prepare for a career as a Business Analyst by providing you with hands-on experience in deploying and consuming machine learning models.
Systems Analyst
Systems Analyst
Systems Analysts design and implement computer systems. This course can help you build the skills and knowledge necessary to become a successful Systems Analyst. You will learn about 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. This course will also help you to prepare for a career as a Systems Analyst by providing you with hands-on experience in deploying and consuming machine learning models.
Project Manager
Project Manager
Project Managers plan, execute, and control projects. This course can help you build the skills and knowledge necessary to become a successful Project Manager. You will learn about 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. This course will also help you to prepare for a career as a Project Manager by providing you with hands-on experience in deploying and consuming machine learning models.
Product Manager
Product Manager
Product Managers work to develop and manage products. This course can help you build the skills and knowledge necessary to become a successful Product Manager. You will learn about 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. This course will also help you to prepare for a career as a Product Manager by providing you with hands-on experience in deploying and consuming machine learning models.
Security Analyst
Security Analyst
Security Analysts protect computer systems from security threats. This course can help you build the skills and knowledge necessary to become a successful Security Analyst. You will learn about 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. This course will also help you to prepare for a career as a Security Analyst by providing you with hands-on experience in deploying and consuming machine learning models.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. This course can help you build the skills and knowledge necessary to become a successful Database Administrator. You will learn about 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. This course will also help you to prepare for a career as a Database Administrator by providing you with hands-on experience in deploying and consuming machine learning models.
Network Administrator
Network Administrator
Network Administrators manage and maintain computer networks. This course can help you build the skills and knowledge necessary to become a successful Network Administrator. You will learn about 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. This course will also help you to prepare for a career as a Network Administrator by providing you with hands-on experience in deploying and consuming machine learning models.
Technical Writer
Technical Writer
Technical Writers create and maintain technical documentation. This course can help you build the skills and knowledge necessary to become a successful Technical Writer. You will learn about 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. This course will also help you to prepare for a career as a Technical Writer by providing you with hands-on experience in deploying and consuming machine learning models.
IT Manager
IT Manager
IT Managers manage and oversee IT operations. This course may be useful for those who want to become an IT Manager, as it can help you build the skills and knowledge necessary to manage and oversee machine learning operations.
For more career information including salaries, visit:
OpenCourser.com/course/l5sqbi/machine
Reading list
We've selected eight books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Machine Learning Operations.
Provides a comprehensive overview of machine learning from a probabilistic perspective. It covers topics such as Bayesian inference, graphical models, and reinforcement learning.
Provides a comprehensive overview of pattern recognition and machine learning. It covers topics such as supervised and unsupervised learning, feature selection, and model evaluation.
Save
Provides a comprehensive overview of deep learning. It covers topics such as deep neural networks, convolutional neural networks, and recurrent neural networks.
This authoritative resource provides a thorough exploration of deep learning concepts and techniques, using Python as the primary programming language. While it may not directly align with the course's focus on MLOps, it serves as a valuable reference for those interested in the underlying principles of deep learning models.
Provides a comprehensive overview of reinforcement learning. It covers topics such as Markov decision processes, value functions, and reinforcement learning algorithms.
This classic textbook offers a comprehensive overview of machine learning algorithms and their mathematical foundations. It provides a solid theoretical background for those seeking a deeper understanding of ML techniques, but may be less relevant for the practical aspects covered in this course.
This introductory guide provides a gentle introduction to machine learning using the R programming language. While it may not be as relevant to those using Azure, it offers a good starting point for those new to ML concepts.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/l5sqbi/machine
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Time
40320 hours
Level
Intermediate
Via
Udacity
Instructors
Erick Galinkin
Noah Gift
Soham Chatterjee
Alfredo Deza
Language
English
Good to know
Explores real-world machine learning operations, which is standard in the industry
Taught by Erick Galinkin, Noah Gift, Soham Chatterjee, Alfredo Deza, who are recognized for their work in machine learning
Develops skills for deploying models, enabling Application Insights, identifying problems in logs, and harnessing the power of Azure’s Pipelines, which are core skills for DevOps engineers
Explores Azure’s Pipelines, which is highly relevant to DevOps engineers
Builds a strong foundation for beginners in machine learning operationalization
It requires learners to come in with some background knowledge in machine learning
Offered through Udacity, which has a strong reputation for online education
Examines key concepts of machine learning operationalization, which is a rapidly growing industry trend
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