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AWS
This course introduces Amazon Machine Learning and Artificial Intelligence tools that enable capabilities across frameworks and infrastructure, machine learning platforms, and API-driven services.
This course introduces Amazon Machine Learning and Artificial Intelligence tools that enable capabilities across frameworks and infrastructure, machine learning platforms, and API-driven services. To do machine learning well, you need competencies across these key layers, the right data store, security, and resources for analytics.
Register for this course and see more details by visiting:
OpenCourser.com/course/1rl28c/introduction
What's inside
Syllabus
Introduction to AWS Machine Learning Services
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores machine learning tools and services, developing learners' competencies across frameworks, infrastructure, and API-driven services
Taught by AWS, who is recognized for their expertise in cloud computing and machine learning
Develops competencies in machine learning platforms, a core skill for data scientists and machine learning engineers
Covers the key layers needed for successful machine learning, including data storage, security, and analytics resources
Examines machine learning across frameworks and infrastructure, providing a comprehensive understanding of the field
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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 Introduction to AWS Machine Learning Services with these
activities:
Guided Lessons: Machine Learning Foundations
Show steps
Review core machine learning concepts and techniques to reinforce course material.
Browse courses on
Machine Learning Basics
Show steps
-
Identify online tutorials or courses covering machine learning fundamentals.
-
Follow the lessons, taking notes and practicing examples.
Peer Study Sessions
Show steps
Discuss and solve course concepts with peers to reinforce learning.
Show steps
-
Form a study group with 2-3 classmates.
-
Set regular meeting times.
-
Review course material, discuss concepts, and solve problems together.
Course Materials Compilation
Show steps
Organize and review course materials to enhance understanding and retention.
Show steps
-
Gather all lecture notes, assignments, quizzes, and exams.
-
Organize materials logically, categorize by topic or week.
-
Annotate materials with additional notes or insights.
Two other activities
Expand to see all activities and additional details
Show all five activities
Machine Learning Algorithm Explanation Video
Show steps
Create a video explaining a machine learning algorithm to solidify comprehension.
Show steps
-
Choose an algorithm covered in the course.
-
Create a script explaining the algorithm.
-
Record and edit the video.
Hands-on Workshop: Cloud-based Machine Learning
Show steps
Attend a workshop to apply course concepts in a practical setting and enhance skills.
Show steps
-
Find and register for relevant workshops.
-
Participate in hands-on exercises and demonstrations.
-
Interact with industry experts and learn from their experiences.
Guided Lessons: Machine Learning Foundations
Show steps
Review core machine learning concepts and techniques to reinforce course material.
Browse courses on
Machine Learning Basics
Show steps
Show steps
Show steps
- Identify online tutorials or courses covering machine learning fundamentals.
- Follow the lessons, taking notes and practicing examples.
Peer Study Sessions
Show steps
Discuss and solve course concepts with peers to reinforce learning.
Show steps
Show steps
Show steps
- Form a study group with 2-3 classmates.
- Set regular meeting times.
- Review course material, discuss concepts, and solve problems together.
Course Materials Compilation
Show steps
Organize and review course materials to enhance understanding and retention.
Show steps
Show steps
Show steps
- Gather all lecture notes, assignments, quizzes, and exams.
- Organize materials logically, categorize by topic or week.
- Annotate materials with additional notes or insights.
Two other activities
Expand to see all activities and additional details
Show all five activities
Machine Learning Algorithm Explanation Video
Show steps
Create a video explaining a machine learning algorithm to solidify comprehension.
Show steps
Show steps
Show steps
- Choose an algorithm covered in the course.
- Create a script explaining the algorithm.
- Record and edit the video.
Hands-on Workshop: Cloud-based Machine Learning
Show steps
Attend a workshop to apply course concepts in a practical setting and enhance skills.
Show steps
Show steps
Show steps
- Find and register for relevant workshops.
- Participate in hands-on exercises and demonstrations.
- Interact with industry experts and learn from their experiences.
Career center
Learners who complete Introduction to AWS Machine Learning Services will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Taking this course can help put you on the right track to becoming a Machine Learning Engineer who can solve critical business problems by building, deploying, and maintaining machine learning models. Machine Learning Engineers are expected to be well-versed in cloud platforms. This course is particularly helpful as it addresses the relevant topics regarding AWS Machine Learning Services.
Data Scientist
Data Scientist
This course provides a strong foundation for Data Scientists who can mine large data sets, develop predictive models, and then present the results to stakeholders in a compelling way. The work of a Data Scientist is of increasing importance to the modern business. This course would help to provide you with some of the skills necessary to be considered for a role in this field.
Data Analyst
Data Analyst
This course helps to build a foundation for Data Analysts who communicate data trends, insights, and solutions to complex business problems. As a Data Analyst, being able to effectively communicate these insights is critical to your success, and this course can help you do so.
Business Analyst
Business Analyst
As a Business Analyst you will determine project feasibility, as well as translate business requirements into technical specifications. While this course doesn't directly teach the skills to do this work, it will help you build a foundation in machine learning, which is a technology used by many businesses to help in this area. Furthermore, completing this course can demonstrate your desire to continuously acquire new knowledge and skills, which is highly sought by employers.
Operations Research Analyst
Operations Research Analyst
Operations Research Analyst apply analytical methods to help organizations improve their efficiency. This course can help you prepare for this career by teaching you foundational skills in machine learning which is widely used by Operations Research Analysts.
DevOps Engineer
DevOps Engineer
A DevOps Engineer uses automation to bridge gaps between development and operations teams, which results in faster product releases. Knowledge of machine learning can be very helpful in DevOps, and this course can help you obtain that knowledge.
Software Engineer
Software Engineer
Software Engineers design, develop, test, deploy, and maintain software systems. Machine learning is becoming ubiquitous in software, and this course may be helpful for a software engineer interested in working with machine learning.
Cloud Architect
Cloud Architect
Cloud Architects are responsible for designing, building, and managing cloud computing systems. They must keep up with new technologies in order to do this effectively. This course will help you to stay up-to-date with the latest developments in AWS cloud computing.
Data Engineer
Data Engineer
Data Engineers build and maintain the infrastructure and tools that are used to store and process data, including machine learning models. This course may be useful for laying the foundation for a career in this field.
Full-Stack Developer
Full-Stack Developer
Full Stack Developers work on both the front-end and back-end of web applications. These Developers often specialize in one or the other, but the full-stack developer works on both. Machine learning can be used in both the front-end and back-end, however, it is most often used in the back-end. This course can help you to enter the field of Full-Stack Development by giving you a solid foundation in AWS.
Web Developer
Web Developer
Web Developers design and develop websites and web applications. Machine learning is becoming increasingly used in this field. This course can help you enter the field of Web Development by giving you a good foundation in machine learning.
Front-End Developer
Front-End Developer
Front-End Developers are responsible for the user interface and user experience of web applications. Machine learning is becoming increasingly used in this field to improve the user experience. This course can help you enter the field of Front-End Development by giving you a strong foundation in machine learning.
Back-End Developer
Back-End Developer
Back-End Developers are responsible for the logic and functionality of web applications. Machine learning is becoming increasingly used in this field to improve the performance and efficiency of web applications. This course can help you enter the field of Back-End Development by giving you a solid foundation in machine learning.
Database Administrator
Database Administrator
Database Administrators are responsible for the maintenance and performance of databases. Machine learning is becoming increasingly used in this field to improve the performance and efficiency of databases. This course can help you enter the field of Database Administration by giving you a strong foundation in machine learning.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists create visual representations of data to help people understand it better. Machine learning is becoming increasingly used in this field to create more interactive and informative visualizations. This course can help you enter the field of Data Visualization by giving you a solid foundation in machine learning.
For more career information including salaries, visit:
OpenCourser.com/course/1rl28c/introduction
Reading list
We've selected 11 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
Introduction to AWS Machine Learning Services.
Offers a comprehensive overview of machine learning concepts and their application in AWS, providing a foundation for leveraging AWS Machine Learning Services effectively.
While this book focuses on machine learning techniques using Python libraries, it provides valuable insights into machine learning fundamentals, which can enhance understanding of AWS Machine Learning Services.
Offers a practical introduction to deep learning concepts and techniques, providing a foundation for understanding how deep learning is integrated into AWS Machine Learning Services.
Provides an accessible introduction to machine learning using Python, making it a valuable resource for understanding the fundamentals underlying AWS Machine Learning Services.
Offers a hands-on approach to data science, covering essential concepts and techniques from scratch, complementing the practical aspects of AWS Machine Learning Services.
Provides a comprehensive overview of statistical learning methods, offering a deeper understanding of the statistical foundations underlying AWS Machine Learning Services.
Provides a solid foundation in reinforcement learning concepts and algorithms, enhancing understanding of how reinforcement learning is integrated into AWS Machine Learning Services.
Save
Offers a comprehensive overview of computer vision techniques, providing a deeper understanding of how computer vision is utilized in AWS Machine Learning Services.
Provides a comprehensive guide to natural language processing using Python, enhancing understanding of how natural language processing is integrated into AWS Machine Learning Services.
Offers a comprehensive overview of speech and language processing concepts and techniques, providing a deeper understanding of how these concepts are applied in AWS Machine Learning Services.
Offers a practical guide to deep learning for computer vision, enhancing understanding of how deep learning is utilized in AWS Machine Learning Services for computer vision tasks.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/1rl28c/introduction
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Time
6 hours
Level
Introductory
Via
Pluralsight
Instructor
AWS
Language
English
Good to know
Explores machine learning tools and services, developing learners' competencies across frameworks, infrastructure, and API-driven services
Taught by AWS, who is recognized for their expertise in cloud computing and machine learning
Develops competencies in machine learning platforms, a core skill for data scientists and machine learning engineers
Covers the key layers needed for successful machine learning, including data storage, security, and analytics resources
Examines machine learning across frameworks and infrastructure, providing a comprehensive understanding of the field
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