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Matt Maybeno,
Bradford Tuckfield,
Soham Chatterjee,
Charles Landau,
and
Joseph Nicolls
Enhance your skills in Machine Learning Workflows with our comprehensive course. Gain expertise in how to create general machine learning workflows on AWS.
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- Machine learning fluency
- AWS familiarity
- API proficiency
- Basic Python
- Jupyter notebooks
Read more
Enhance your skills in Machine Learning Workflows with our comprehensive course. Gain expertise in how to create general machine learning workflows on AWS.
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- Machine learning fluency
- AWS familiarity
- API proficiency
- Basic Python
- Jupyter notebooks
Read more
Enhance your skills in Machine Learning Workflows with our comprehensive course. Gain expertise in how to create general machine learning workflows on AWS.
Prerequisite details
To optimize your success in this program, we've created a list of prerequisites and recommendations to help you prepare for the curriculum. Prior to enrolling, you should have the following knowledge:
- Machine learning fluency
- AWS familiarity
- API proficiency
- Basic Python
- Jupyter notebooks
You will also need to be able to communicate fluently and professionally in written and spoken English.
Register for this course and see more details by visiting:
OpenCourser.com/course/m0or9d/developing
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What's inside
Syllabus
This lesson gives an introduction to the course, including prerequisites, final project, stakeholders, and tools & environment.
This lesson will go over SageMaker essential services such as training jobs, endpoints, batch transforms, and processing jobs.
Read more
Syllabus
This lesson gives an introduction to the course, including prerequisites, final project, stakeholders, and tools & environment.
This lesson will go over SageMaker essential services such as training jobs, endpoints, batch transforms, and processing jobs.
Read more
This lesson will discuss machine learning workflows and AWS tools such as Lambda, Step Function for building a workflow.
This lesson will go over monitoring a machine learning workflow and some useful services within AWS to help you monitoring the healthy of data and machine learning models.
In the project, you will build and ship an image classification model with AWS SageMaker for Scones Unlimited, a scone-delivery-focused logistic company.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines machine learning workflows and tools, which is a rapidly growing field with high industry demand
Builds a strong foundation for beginners by providing a comprehensive overview of machine learning concepts and tools
Strengthens an existing foundation for intermediate learners by delving deeper into machine learning algorithms and techniques
Develops professional skills in machine learning workflows, which are in high demand across various industries
Covers unique perspectives and ideas in machine learning workflows, which can add color to other topics and subjects
Requires prior knowledge of machine learning, AWS, API proficiency, basic Python, and Jupyter notebooks
Save this course
Save Developing your First ML Workflow 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 Developing your First ML Workflow with these
activities:
Review AWS fundamentals
Show steps
Refresh your knowledge of AWS services and concepts to prepare for the course's focus on AWS-based machine learning workflows.
Browse courses on
AWS
Show steps
-
Review AWS documentation and tutorials.
-
Attend an AWS webinar or workshop.
-
Take an online AWS certification course.
Refresh Python programming skills
Show steps
Review the basics of Python to strengthen your foundational understanding before starting the course.
Browse courses on
Python
Show steps
-
Take an online Python tutorial or course.
-
Review Python documentation and resources.
-
Solve practice problems and coding challenges.
Follow AWS SageMaker tutorials
Show steps
Familiarize yourself with AWS SageMaker by following guided tutorials to gain hands-on experience with the platform.
Browse courses on
AWS SageMaker
Show steps
-
Complete the AWS SageMaker Getting Started tutorial.
-
Explore AWS SageMaker documentation and sample notebooks.
-
Follow AWS SageMaker blog posts and tutorials.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Participate in online forums and discussion groups
Show steps
Connect with other students and practitioners to exchange knowledge, ask questions, and gain different perspectives on course topics.
Show steps
-
Join the course discussion forum.
-
Participate in online Q&A platforms related to the course.
-
Attend virtual meetups or webinars.
Build a small-scale machine learning workflow
Show steps
Test your understanding by building a miniature machine learning workflow using AWS SageMaker to gain practical experience.
Show steps
-
Define a problem statement and gather data.
-
Train a machine learning model using SageMaker.
-
Deploy the model as an endpoint.
Attend a machine learning workshop
Show steps
Enhance your learning by attending a workshop focused on practical machine learning applications and techniques, potentially using AWS services.
Browse courses on
Machine Learning
Show steps
-
Research and identify relevant workshops.
-
Register for the workshop and prepare accordingly.
-
Attend the workshop and actively participate.
Participate in a machine learning hackathon
Show steps
Challenge yourself and showcase your skills by participating in a hackathon that involves building machine learning solutions, potentially using AWS.
Browse courses on
Machine Learning
Show steps
-
Find and register for a machine learning hackathon.
-
Form a team or work individually.
-
Develop and submit a machine learning solution.
Review AWS fundamentals
Show steps
Refresh your knowledge of AWS services and concepts to prepare for the course's focus on AWS-based machine learning workflows.
Browse courses on
AWS
Show steps
Show steps
Show steps
- Review AWS documentation and tutorials.
- Attend an AWS webinar or workshop.
- Take an online AWS certification course.
Refresh Python programming skills
Show steps
Review the basics of Python to strengthen your foundational understanding before starting the course.
Browse courses on
Python
Show steps
Show steps
Show steps
- Take an online Python tutorial or course.
- Review Python documentation and resources.
- Solve practice problems and coding challenges.
Follow AWS SageMaker tutorials
Show steps
Familiarize yourself with AWS SageMaker by following guided tutorials to gain hands-on experience with the platform.
Browse courses on
AWS SageMaker
Show steps
Show steps
Show steps
- Complete the AWS SageMaker Getting Started tutorial.
- Explore AWS SageMaker documentation and sample notebooks.
- Follow AWS SageMaker blog posts and tutorials.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Participate in online forums and discussion groups
Show steps
Connect with other students and practitioners to exchange knowledge, ask questions, and gain different perspectives on course topics.
Show steps
Show steps
Show steps
- Join the course discussion forum.
- Participate in online Q&A platforms related to the course.
- Attend virtual meetups or webinars.
Build a small-scale machine learning workflow
Show steps
Test your understanding by building a miniature machine learning workflow using AWS SageMaker to gain practical experience.
Show steps
Show steps
Show steps
- Define a problem statement and gather data.
- Train a machine learning model using SageMaker.
- Deploy the model as an endpoint.
Attend a machine learning workshop
Show steps
Enhance your learning by attending a workshop focused on practical machine learning applications and techniques, potentially using AWS services.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Research and identify relevant workshops.
- Register for the workshop and prepare accordingly.
- Attend the workshop and actively participate.
Participate in a machine learning hackathon
Show steps
Challenge yourself and showcase your skills by participating in a hackathon that involves building machine learning solutions, potentially using AWS.
Browse courses on
Machine Learning
Show steps
Show steps
Show steps
- Find and register for a machine learning hackathon.
- Form a team or work individually.
- Develop and submit a machine learning solution.
Career center
Learners who complete Developing your First ML Workflow will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models to solve business problems. This course can help aspiring Machine Learning Engineers build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to succeed in this field. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for Machine Learning Engineers.
Data Scientist
Data Scientist
Data Scientists use machine learning and other techniques to extract insights from data. This course can help aspiring Data Scientists build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to succeed in this field. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for Data Scientists.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course can help aspiring Software Engineers build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to incorporate machine learning into their software systems. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for Software Engineers working with machine learning.
DevOps Engineer
DevOps Engineer
DevOps Engineers ensure that software systems are deployed and maintained efficiently and reliably. This course can help aspiring DevOps Engineers build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to manage and monitor machine learning systems. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for DevOps Engineers working with machine learning.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products and features. This course can help aspiring Product Managers build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to incorporate machine learning into their products. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for Product Managers working with machine learning.
Business Analyst
Business Analyst
Business Analysts help businesses identify and solve problems. This course can help aspiring Business Analysts build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to use machine learning to solve business problems. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for Business Analysts working with machine learning.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to help businesses make informed decisions. This course can help aspiring Data Analysts build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to use machine learning to analyze data. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for Data Analysts working with machine learning.
Cloud Architect
Cloud Architect
Cloud Architects design and manage cloud computing systems. This course can help aspiring Cloud Architects build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to incorporate machine learning into their cloud architectures. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for Cloud Architects working with machine learning.
Systems Engineer
Systems Engineer
Systems Engineers design, implement, and maintain computer systems. This course can help aspiring Systems Engineers build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to incorporate machine learning into their systems. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for Systems Engineers working with machine learning.
Network Engineer
Network Engineer
Network Engineers design, implement, and maintain computer networks. This course can help aspiring Network Engineers build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to incorporate machine learning into their networks. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for Network Engineers working with machine learning.
Security Engineer
Security Engineer
Security Engineers design, implement, and maintain computer security systems. This course can help aspiring Security Engineers build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to incorporate machine learning into their security systems. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for Security Engineers working with machine learning.
Database Administrator
Database Administrator
Database Administrators design, implement, and maintain database systems. This course can help aspiring Database Administrators build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to incorporate machine learning into their database systems. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for Database Administrators working with machine learning.
IT Manager
IT Manager
IT Managers plan, implement, and manage IT systems. This course can help aspiring IT Managers build a foundation in machine learning workflows on AWS. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to incorporate machine learning into their IT systems. The course also covers topics such as monitoring and troubleshooting machine learning models, which are essential skills for IT Managers working with machine learning.
Project Manager
Project Manager
Project Managers plan, implement, and manage projects. This course may be useful for aspiring Project Managers who want to learn how to incorporate machine learning into their projects. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to use machine learning to solve project-related problems.
Technical Writer
Technical Writer
Technical Writers create and maintain technical documentation. This course may be useful for aspiring Technical Writers who want to learn how to write about machine learning. By learning how to create, train, and deploy machine learning models, students will gain the skills necessary to write clear and concise documentation about machine learning concepts.
For more career information including salaries, visit:
OpenCourser.com/course/m0or9d/developing
Reading list
We've selected seven 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
Developing your First ML Workflow.
Provides a comprehensive introduction to Deep Learning using Python. It covers the fundamental concepts of Deep Learning, such as neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive introduction to Deep Learning using Python. It covers the fundamental concepts of Deep Learning, such as neural networks, convolutional neural networks, and recurrent neural networks.
Provides a hands-on introduction to Machine Learning using Scikit-Learn, Keras, and TensorFlow. It covers the fundamental concepts of Machine Learning, such as data preprocessing, model selection, and model evaluation.
Provides a comprehensive introduction to Machine Learning using R. It covers the fundamental concepts of Machine Learning, such as data preprocessing, model selection, and model evaluation.
Provides a comprehensive introduction to Machine Learning using Python. It covers the fundamental concepts of Machine Learning, such as data preprocessing, model selection, and model evaluation.
Provides a gentle introduction to Artificial Intelligence. It covers the fundamental concepts of Artificial Intelligence, such as machine learning, natural language processing, and computer vision.
Provides a gentle introduction to Machine Learning. It covers the fundamental concepts of Machine Learning, such as data preprocessing, model selection, and model evaluation.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/m0or9d/developing
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Effort
4 weeks
Level
Intermediate
Via
Udacity
Instructors
Matt Maybeno
Bradford Tuckfield
Soham Chatterjee
Charles Landau
Joseph Nicolls
Language
English
Good to know
Examines machine learning workflows and tools, which is a rapidly growing field with high industry demand
Builds a strong foundation for beginners by providing a comprehensive overview of machine learning concepts and tools
Strengthens an existing foundation for intermediate learners by delving deeper into machine learning algorithms and techniques
Develops professional skills in machine learning workflows, which are in high demand across various industries
Covers unique perspectives and ideas in machine learning workflows, which can add color to other topics and subjects
Requires prior knowledge of machine learning, AWS, API proficiency, basic Python, and Jupyter notebooks
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