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This is an introductory course on artificial intelligence (AI).
Read more
This is an introductory course on artificial intelligence (AI).
Read more
This is an introductory course on artificial intelligence (AI).
This is an introductory course on artificial intelligence (AI). In the course, we discuss what AI is and why it is important, and take a brief look at machine learning and deep learning—which are subsets of AI—and describe how Amazon uses AI in its products.
Register for this course and see more details by visiting:
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What's inside
Syllabus
What is Artificial Intelligence?
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides a clear and concise introduction to important and relevant concepts in the field of artificial intelligence (AI)
Features instructors from AWS, providing learners with direct insights from industry experts
Explores the practical applications of AI in real-world products and services through the lens of Amazon
Suitable for beginners seeking a foundational understanding of AI and its components, including machine learning and deep learning
Save this course
Save What is Artificial Intelligence? 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 What is Artificial Intelligence? with these
activities:
Review math and statistics concepts
Show steps
Strengthen your foundational math and statistics skills, which are essential for understanding AI algorithms and models.
Browse courses on
Linear Algebra
Show steps
-
Review notes or textbooks on linear algebra, calculus, and probability.
-
Solve practice problems and exercises to test your understanding.
Organize your notes and materials
Show steps
Stay organized and improve your retention by compiling and reviewing your notes and course materials.
Show steps
-
Gather all your notes, assignments, and other materials.
-
Sort and organize the materials by topic or lesson.
-
Review your organized materials regularly to reinforce your learning.
Read "Artificial Intelligence: A Modern Approach"
Show steps
Reinforce your understanding of the key concepts and algorithms in AI through this comprehensive textbook.
View
Melania
on Amazon
Show steps
-
Read and take notes on each chapter.
-
Complete the end-of-chapter exercises.
-
Summarize the main ideas of each chapter.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a study group or online forum
Show steps
Engage with other learners, share insights, and get feedback on your understanding of AI.
Show steps
-
Find a study group or online forum focused on AI.
-
Participate in discussions, ask questions, and share your thoughts.
-
Review the contributions of others and learn from their perspectives.
Follow tutorials on specific AI topics
Show steps
Supplement your learning by exploring specific AI topics in more depth and following hands-on tutorials.
Show steps
-
Identify areas where you want to expand your knowledge or skills.
-
Search for online tutorials or courses that cover those topics.
-
Follow the tutorials, complete the exercises, and implement what you learn.
Practice solving machine learning and deep learning problems
Show steps
Deepen your understanding of AI algorithms by practicing them, and build your confidence in solving real-world AI problems.
Browse courses on
Machine Learning Algorithms
Show steps
-
Find online resources or platforms that provide practice problems.
-
Start solving problems regularly, increasing the difficulty as you progress.
-
Analyze your solutions and identify areas for improvement.
Write a blog post or article about AI
Show steps
Solidify your understanding of AI by explaining it to others in a written format.
Browse courses on
AI Applications
Show steps
-
Choose a specific topic within AI that you are interested in.
-
Research and gather information from credible sources.
-
Organize your thoughts and write a clear and engaging article.
Contribute to an open-source AI project
Show steps
Gain practical experience and make a meaningful contribution to the AI community by participating in open-source projects.
Show steps
-
Find an open-source AI project that aligns with your interests and skills.
-
Review the project's documentation and contribute in a meaningful way.
-
Collaborate with other contributors and learn from their expertise.
Review math and statistics concepts
Show steps
Strengthen your foundational math and statistics skills, which are essential for understanding AI algorithms and models.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Review notes or textbooks on linear algebra, calculus, and probability.
- Solve practice problems and exercises to test your understanding.
Organize your notes and materials
Show steps
Stay organized and improve your retention by compiling and reviewing your notes and course materials.
Show steps
Show steps
Show steps
- Gather all your notes, assignments, and other materials.
- Sort and organize the materials by topic or lesson.
- Review your organized materials regularly to reinforce your learning.
Read "Artificial Intelligence: A Modern Approach"
Show steps
Reinforce your understanding of the key concepts and algorithms in AI through this comprehensive textbook.
View
Melania
on Amazon
Show steps
Show steps
Show steps
- Read and take notes on each chapter.
- Complete the end-of-chapter exercises.
- Summarize the main ideas of each chapter.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Join a study group or online forum
Show steps
Engage with other learners, share insights, and get feedback on your understanding of AI.
Show steps
Show steps
Show steps
- Find a study group or online forum focused on AI.
- Participate in discussions, ask questions, and share your thoughts.
- Review the contributions of others and learn from their perspectives.
Follow tutorials on specific AI topics
Show steps
Supplement your learning by exploring specific AI topics in more depth and following hands-on tutorials.
Show steps
Show steps
Show steps
- Identify areas where you want to expand your knowledge or skills.
- Search for online tutorials or courses that cover those topics.
- Follow the tutorials, complete the exercises, and implement what you learn.
Practice solving machine learning and deep learning problems
Show steps
Deepen your understanding of AI algorithms by practicing them, and build your confidence in solving real-world AI problems.
Browse courses on
Machine Learning Algorithms
Show steps
Show steps
Show steps
- Find online resources or platforms that provide practice problems.
- Start solving problems regularly, increasing the difficulty as you progress.
- Analyze your solutions and identify areas for improvement.
Write a blog post or article about AI
Show steps
Solidify your understanding of AI by explaining it to others in a written format.
Browse courses on
AI Applications
Show steps
Show steps
Show steps
- Choose a specific topic within AI that you are interested in.
- Research and gather information from credible sources.
- Organize your thoughts and write a clear and engaging article.
Contribute to an open-source AI project
Show steps
Gain practical experience and make a meaningful contribution to the AI community by participating in open-source projects.
Show steps
Show steps
Show steps
- Find an open-source AI project that aligns with your interests and skills.
- Review the project's documentation and contribute in a meaningful way.
- Collaborate with other contributors and learn from their expertise.
Career center
Learners who complete What is Artificial Intelligence? will develop knowledge and skills
that may be useful to these careers:
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematics and statistics to solve complex financial problems. This course will help teach Quantitative Analysts about how to use artificial intelligence to solve these problems in new ways.
Actuary
Actuary
Actuaries use mathematics to assess risk and uncertainty. This course will help teach Actuaries how to use artificial intelligence to analyze data and make better predictions about the future. It may also help those who wish to pivot to this career, as it discusses how to implement artificial intelligence in different business contexts.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use advanced analytical techniques to help businesses make better decisions. This course will help teach Operations Research Analysts how to use artificial intelligence to conduct more robust and powerful analyses.
Software Engineer
Software Engineer
Software Engineers are behind some of your favorite technologies. They are the ones who design, develop, deploy, and maintain software applications. This course will help teach Software Engineers about the implementation of artificial intelligence within the software development lifecycle.
Financial Analyst
Financial Analyst
Financial Analysts use data to make investment recommendations. This course will help teach Financial Analysts about how to use artificial intelligence to gather and analyze data. It may also help those who wish to pivot to this career, as it discusses how to implement artificial intelligence in different business contexts.
Risk Analyst
Risk Analyst
Risk Analysts identify and assess risks faced by businesses. This course can help teach Risk Analysts about how to leverage the power of artificial intelligence to analyze data and make predictions about potential risks and vulnerabilities.
Data Scientist
Data Scientist
Data Scientists have to be able to collect, analyze, interpret, and present large amounts of data. This course helps teach Data Scientists about the inner workings of artificial intelligence, so they can use it to power their models.
Business Analyst
Business Analyst
Business Analysts use data to help businesses make better decisions. This course will help teach Business Analysts about how to use artificial intelligence to analyze data and make better recommendations.
Deep Learning Engineer
Deep Learning Engineer
Deep Learning Engineers build and maintain deep learning models. This course may be useful for Deep Learning Engineers, as it discusses how to implement artificial intelligence in different business contexts.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and maintain machine learning models. This course may be useful for Machine Learning Engineers, as it discusses how to implement artificial intelligence in different business contexts.
Data Engineer
Data Engineer
Data Engineers build and maintain data pipelines. This course may be useful for Data Engineers, as it discusses how to implement artificial intelligence in different business contexts.
Robotics Engineer
Robotics Engineer
Robotics Engineers build and maintain robots. This course may be useful for Robotics Engineers, as it discusses how to implement artificial intelligence in different business contexts.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers build and maintain computer vision systems. This course may be useful for Computer Vision Engineers, as it discusses how to implement artificial intelligence in different business contexts.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
Artificial Intelligence Engineers build and maintain artificial intelligence systems. This course may be useful for Artificial Intelligence Engineers, as it discusses how to implement artificial intelligence in different business contexts.
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers build and maintain natural language processing systems. This course may be useful for Natural Language Processing Engineers, as it discusses how to implement artificial intelligence in different business contexts.
For more career information including salaries, visit:
OpenCourser.com/course/3ofc01/what
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
What is Artificial Intelligence?.
Save
Comprehensive textbook on deep learning, which provides a detailed overview of the field. It covers a wide range of topics, including neural networks, convolutional neural networks, and recurrent neural networks.
Provides a comprehensive overview of statistical learning, which fundamental component of artificial intelligence. It is particularly useful for students and researchers who want to learn about the underlying principles of statistical learning.
Provides a comprehensive overview of deep learning using Python. It is particularly useful for programmers who want to learn about deep learning and how to use it in their own projects.
Provides a comprehensive overview of machine learning for beginners. It is particularly useful for anyone who wants to learn about machine learning and how it can be used in their own projects.
Provides a comprehensive overview of natural language processing for beginners. It is particularly useful for anyone who wants to learn about natural language processing and how it can be used in their own projects.
Provides a comprehensive overview of machine learning using Python. It is particularly useful for programmers who want to learn about machine learning and how to use it in their own projects.
Practical guide to natural language processing, which provides a clear explanation of the underlying concepts and algorithms. It is particularly useful for beginners who want to learn about natural language processing and its applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/3ofc01/what
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Time
19 hours
Level
Introductory
Via
Pluralsight
Instructor
AWS
Language
English
Good to know
Provides a clear and concise introduction to important and relevant concepts in the field of artificial intelligence (AI)
Features instructors from AWS, providing learners with direct insights from industry experts
Explores the practical applications of AI in real-world products and services through the lens of Amazon
Suitable for beginners seeking a foundational understanding of AI and its components, including machine learning and deep learning
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