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Russell Sayers
In this course, we start with some services where the training model and raw inference is handled for you by Amazon. We'll cover services which do the heavy lifting of computer vision, data extraction and analysis, language processing, speech recognition, translation, ML model training and virtual agents. You'll think of your current solutions and see where you can improve these solutions using AI, ML or Deep Learning. All of these solutions can work with your current applications to make some improvements in your user experience or the business needs of your application.
Register for this course and see more details by visiting:
OpenCourser.com/course/asrot3/introduction
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What's inside
Learning objectives
- At the end of this course, students will be able to:
- Apply machine learning and artificial intelligence to tasks that you'd normally think you'd need a human to dounderstand the differences between machine learning, artificial intelligence and deep learninganalyze labels and images using advanced technologylearn how to host your own machine learning models with amazon sagemaker
- At the end of this course, students will be able to:
- Apply machine learning and artificial intelligence to tasks that you'd normally think you'd need a human to dounderstand the differences between machine learning, artificial intelligence and deep learninganalyze labels and images using advanced technologylearn how to host your own machine learning models with amazon sagemaker
Syllabus
Week 1:
Video :Course Introduction
Video : Week 1 Introduction
Video : Computer Vision: Amazon Rekognition
Read more
Syllabus
Week 1:
Video :Course Introduction
Video : Week 1 Introduction
Video : Computer Vision: Amazon Rekognition
Read more
Video : Exercise Introduction: Amazon Rekognition
Exercise : Amazon Rekognition
Video : Exercise Walkthrough: Amazon Rekognition
Video : Data extraction and analysis: Amazon Textract
Video : Exercise Introduction: Amazon Textract
Exercise: Amazon Textract
Video : Exercise Introduction: Amazon Comprehend
Exercise : Amazon Comprehend
Video : Exercise Walkthrough: Amazon Comprehend
Quiz : Week 1 Quiz
_Week 2: _
Video : Week 2 Introduction
Video : Speech Recognition: Amazon Transcribe
Video: Language Translation: Amazon Translate
Video: Exercise Introduction: Amazon Transcribe and Amazon Translate
Exercise: Amazon Transcribe and Amazon Translate
Video: Exercise Walkthrough: Amazon Transcribe and Amazon Translate
Video: Virtual Agents: Amazon Lex
Video: Exercise Introduction: Amazon Lex
Exercise: Amazon Lex
Video: Exercise Walkthrough: Amazon Lex
Video: Amazon SageMaker
Video: Demo: Amazon SageMaker
Quiz: Week 2 Quiz
Video : Exercise Walkthrough: Amazon TextractVideo : Language Processing: Amazon Comprehend
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Relevant to industry - applies machine learning and artificial intelligence to practical tasks
Develops a range of highly relevant skills in deep learning, computer vision, data extraction/analysis, natural language processing, and speech recognition
Industry-recognized platform - uses Amazon's suite of AI and ML services
Covers essential techniques - teaches how to use deep learning models, host ML models with Amazon SageMaker, analyze images and labels, and extract data and insights from text
Builds up complex knowledge - starts with basic computer vision and gradually introduces more advanced concepts like speech recognition, language translation, and virtual agents
Hands-on practice - includes exercises, demos, and walkthroughs to reinforce concepts
Save this course
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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 Machine Learning on AWS with these
activities:
Create a cheat sheet
Show steps
Creating a cheat sheet is a great way to organize and condense the most important information in the course.
Show steps
-
Identify the key concepts
-
Write down the key concepts
Study with a partner
Show steps
Studying with a partner can help you understand and retain the information better.
Show steps
-
Find a study partner
-
Schedule a study session
-
Review the material together
Summarize the key concepts of a lecture
Show steps
Summarizing lectures and readings will help you retain the information in the long-term.
Show steps
-
Watch or read the lecture
-
Identify the main points
-
Write a summary
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice exercises
Show steps
Practicing exercises will help you improve your skills and understanding.
Show steps
-
Find exercises
-
Complete the exercises
Complete additional tutorials
Show steps
Completing additional tutorials will help you expand your skills and knowledge.
Browse courses on
Computer Vision
Show steps
-
Find a tutorial
-
Complete the tutorial
Analyze images of your own
Show steps
Images can be found all around us. Analyze your own images to solidify your understanding of Amazon Rekognition.
Browse courses on
Computer Vision
Show steps
-
Take pictures of various objects
-
Upload the pictures to Amazon Rekognition
-
Analyze the results
Attend an industry event
Show steps
Attending industry events can help you connect with other professionals and learn about the latest trends.
Show steps
-
Find an industry event
-
Attend the event
-
Network with other professionals
Volunteer at an organization
Show steps
Volunteering at an organization can help you gain practical experience and build your resume.
Show steps
-
Complete the volunteer training
-
Volunteer your time
-
Find a volunteer opportunity
-
Apply for the volunteer position
Create a cheat sheet
Show steps
Creating a cheat sheet is a great way to organize and condense the most important information in the course.
Show steps
Show steps
Show steps
- Identify the key concepts
- Write down the key concepts
Study with a partner
Show steps
Studying with a partner can help you understand and retain the information better.
Show steps
Show steps
Show steps
- Find a study partner
- Schedule a study session
- Review the material together
Summarize the key concepts of a lecture
Show steps
Summarizing lectures and readings will help you retain the information in the long-term.
Show steps
Show steps
Show steps
- Watch or read the lecture
- Identify the main points
- Write a summary
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice exercises
Show steps
Practicing exercises will help you improve your skills and understanding.
Show steps
Show steps
Show steps
- Find exercises
- Complete the exercises
Complete additional tutorials
Show steps
Completing additional tutorials will help you expand your skills and knowledge.
Browse courses on
Computer Vision
Show steps
Show steps
Show steps
- Find a tutorial
- Complete the tutorial
Analyze images of your own
Show steps
Images can be found all around us. Analyze your own images to solidify your understanding of Amazon Rekognition.
Browse courses on
Computer Vision
Show steps
Show steps
Show steps
- Take pictures of various objects
- Upload the pictures to Amazon Rekognition
- Analyze the results
Attend an industry event
Show steps
Attending industry events can help you connect with other professionals and learn about the latest trends.
Show steps
Show steps
Show steps
- Find an industry event
- Attend the event
- Network with other professionals
Volunteer at an organization
Show steps
Volunteering at an organization can help you gain practical experience and build your resume.
Show steps
Show steps
Show steps
- Complete the volunteer training
- Volunteer your time
- Find a volunteer opportunity
- Apply for the volunteer position
Career center
Learners who complete Introduction to Machine Learning on AWS will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers construct, test, and deploy machine learning models, which are algorithms that learn from data and make predictions. This course introduces fundamental machine learning concepts and provides hands-on experience with Amazon Web Services (AWS) machine learning services. By completing this course, you will gain the foundational knowledge and skills necessary to pursue a career as a Machine Learning Engineer.
Data Scientist
Data Scientist
Data Scientists apply machine learning and other statistical techniques to solve business problems. This course provides an introduction to machine learning and artificial intelligence, and covers a range of AWS machine learning services. By completing this course, you will build a foundation in machine learning that will prepare you for a career as a Data Scientist.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software systems. This course provides an introduction to machine learning and artificial intelligence, and covers a range of AWS machine learning services. By completing this course, you will gain the skills and knowledge necessary to incorporate machine learning into your software development projects.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. This course provides an introduction to machine learning and artificial intelligence, and covers a range of AWS machine learning services. By completing this course, you will gain the knowledge and skills necessary to understand how machine learning can be used to improve products.
Business Analyst
Business Analyst
Business Analysts help organizations improve their performance by identifying and solving business problems. This course provides an introduction to machine learning and artificial intelligence, and covers a range of AWS machine learning services. By completing this course, you will gain the skills and knowledge necessary to use machine learning to solve business problems.
Cloud Architect
Cloud Architect
Cloud Architects design and implement cloud computing solutions. This course provides an introduction to machine learning and artificial intelligence, and covers a range of AWS machine learning services. By completing this course, you will gain the knowledge and skills necessary to build cloud-based machine learning solutions.
Data Analyst
Data Analyst
Data Analysts collect, analyze, and interpret data to help organizations make informed decisions. This course provides an introduction to machine learning and artificial intelligence, and covers a range of AWS machine learning services. By completing this course, you will gain the skills and knowledge necessary to use machine learning to analyze data.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze financial data. This course provides an introduction to machine learning and artificial intelligence, and covers a range of AWS machine learning services. By completing this course, you will gain the skills and knowledge necessary to use machine learning to analyze financial data.
Machine Learning Researcher
Machine Learning Researcher
Machine Learning Researchers develop new machine learning algorithms and techniques. This course provides an introduction to machine learning and artificial intelligence, and covers a range of AWS machine learning services. By completing this course, you will gain the foundational knowledge and skills necessary to pursue a career as a Machine Learning Researcher.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers design, develop, and maintain AI systems. This course provides an introduction to machine learning and artificial intelligence, and covers a range of AWS machine learning services. By completing this course, you will gain the foundational knowledge and skills necessary to pursue a career as an Artificial Intelligence Engineer.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers develop and maintain computer vision systems. This course covers Amazon Rekognition, a computer vision service that can identify objects, faces, and scenes in images. By completing this course, you will gain the skills and knowledge necessary to develop computer vision applications.
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers develop and maintain natural language processing systems. This course covers Amazon Comprehend, a natural language processing service that can analyze text and extract key information. By completing this course, you will gain the skills and knowledge necessary to develop natural language processing applications.
Speech Recognition Engineer
Speech Recognition Engineer
Speech Recognition Engineers develop and maintain speech recognition systems. This course covers Amazon Transcribe, a speech recognition service that can convert speech to text. By completing this course, you will gain the skills and knowledge necessary to develop speech recognition applications.
Machine Learning Developer
Machine Learning Developer
Machine Learning Developers develop and maintain machine learning applications. This course provides an introduction to machine learning and artificial intelligence, and covers a range of AWS machine learning services. By completing this course, you will gain the skills and knowledge necessary to develop machine learning applications.
Data Engineer
Data Engineer
Data Engineers design and build data pipelines. This course provides an introduction to machine learning and artificial intelligence, and covers a range of AWS machine learning services. By completing this course, you will gain the skills and knowledge necessary to build data pipelines for machine learning applications.
For more career information including salaries, visit:
OpenCourser.com/course/asrot3/introduction
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
Introduction to Machine Learning on AWS.
Covers machine learning algorithms, including linear regression, logistic regression, and decision trees. Provides a theoretical foundation for machine learning.
Provides a comprehensive overview of machine learning, including supervised learning, unsupervised learning, and reinforcement learning. Offers a high-level perspective on machine learning.
Covers machine learning algorithms, including neural networks, support vector machines, and ensemble methods. Provides a practical guide to machine learning.
Save
Covers deep learning concepts and techniques, including neural networks, convolutional neural networks, and recurrent neural networks. Provides a theoretical foundation for deep learning.
Provides a gentle introduction to machine learning, with a focus on the practical aspects of machine learning. Offers a hands-on approach to machine learning.
Covers speech and language processing concepts and techniques, including speech recognition, natural language processing, and speech synthesis. Provides a theoretical foundation for speech and language processing.
Covers data science concepts and techniques, including data analysis, machine learning, and data visualization. Provides a practical guide to data science.
Covers deep learning concepts, including neural networks, convolutional neural networks, and recurrent neural networks. Provides a theoretical foundation for deep learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/asrot3/introduction
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Effort
2 to 4 hours per week for 2 weeks
Level
Introductory
Via
edX
Institution
Amazon Web Services
Instructor
Russell Sayers
Language
English
Transcript
English
Good to know
Relevant to industry - applies machine learning and artificial intelligence to practical tasks
Develops a range of highly relevant skills in deep learning, computer vision, data extraction/analysis, natural language processing, and speech recognition
Industry-recognized platform - uses Amazon's suite of AI and ML services
Covers essential techniques - teaches how to use deep learning models, host ML models with Amazon SageMaker, analyze images and labels, and extract data and insights from text
Builds up complex knowledge - starts with basic computer vision and gradually introduces more advanced concepts like speech recognition, language translation, and virtual agents
Hands-on practice - includes exercises, demos, and walkthroughs to reinforce concepts
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