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Join Joe Pringle, AWS for an inside perspective on how to understand machine learning and how to put it to work in your role.
Join Joe Pringle, AWS for an inside perspective on how to understand machine learning and how to put it to work in your role.
Register for this course and see more details by visiting:
OpenCourser.com/course/vkrjbw/aws
What's inside
Syllabus
AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Focuses on giving every developer machine learning capabilities, which is the industry standard
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Save AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer 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 AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer with these
activities:
Brush Up on Machine Learning (ML) Concepts
Show steps
Reinforce your understanding of foundational ML principles, making it easier to grasp advanced course concepts.
Browse courses on
Machine Learning Fundamentals
Show steps
-
Revisit textbooks or online resources on ML basics.
-
Review key algorithms such as linear regression and decision trees.
-
Practice implementing simple ML models in a coding environment.
Attend Machine Learning Workshops
Show steps
Expand your knowledge and skills by attending specialized ML workshops conducted by industry experts.
Show steps
-
Research and identify reputable ML workshops aligned with your interests.
-
Register and attend the workshops, actively participating in discussions and exercises.
-
Connect with instructors and fellow attendees to expand your network.
Solve Practice Problems on Machine Learning Algorithms
Show steps
Sharpen your problem-solving skills and deepen your understanding of ML algorithms.
Browse courses on
ML Algorithms
Show steps
-
Find practice problems on platforms like LeetCode or Kaggle.
-
Attempt to solve the problems using the appropriate ML techniques.
-
Analyze your solutions, identify errors, and seek guidance when needed.
One other activity
Expand to see all activities and additional details
Show all four activities
Develop a Machine Learning Project Proposal
Show steps
Gain hands-on experience by planning and proposing an ML project that solves a real-world problem.
Show steps
-
Identify a problem or opportunity that can be addressed with ML.
-
Research different ML techniques and select the most appropriate ones.
-
Outline the project scope, goals, and expected outcomes.
-
Create a timeline and budget for the project.
Brush Up on Machine Learning (ML) Concepts
Show steps
Reinforce your understanding of foundational ML principles, making it easier to grasp advanced course concepts.
Browse courses on
Machine Learning Fundamentals
Show steps
Show steps
Show steps
- Revisit textbooks or online resources on ML basics.
- Review key algorithms such as linear regression and decision trees.
- Practice implementing simple ML models in a coding environment.
Attend Machine Learning Workshops
Show steps
Expand your knowledge and skills by attending specialized ML workshops conducted by industry experts.
Show steps
Show steps
Show steps
- Research and identify reputable ML workshops aligned with your interests.
- Register and attend the workshops, actively participating in discussions and exercises.
- Connect with instructors and fellow attendees to expand your network.
Solve Practice Problems on Machine Learning Algorithms
Show steps
Sharpen your problem-solving skills and deepen your understanding of ML algorithms.
Browse courses on
ML Algorithms
Show steps
Show steps
Show steps
- Find practice problems on platforms like LeetCode or Kaggle.
- Attempt to solve the problems using the appropriate ML techniques.
- Analyze your solutions, identify errors, and seek guidance when needed.
One other activity
Expand to see all activities and additional details
Show all four activities
Develop a Machine Learning Project Proposal
Show steps
Gain hands-on experience by planning and proposing an ML project that solves a real-world problem.
Show steps
Show steps
Show steps
- Identify a problem or opportunity that can be addressed with ML.
- Research different ML techniques and select the most appropriate ones.
- Outline the project scope, goals, and expected outcomes.
- Create a timeline and budget for the project.
Career center
Learners who complete AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer builds and maintains machine learning models in order to solve a variety of business problems. Machine Learning Engineers can work in a variety of industries, including finance, healthcare, and manufacturing. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Machine Learning Engineer.
Data Scientist
Data Scientist
A Data Scientist uses data to build models that can predict future outcomes. Data Scientists can work in a variety of industries, including finance, healthcare, and retail. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Data Scientist.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software applications. Software Engineers can work in a variety of industries, including finance, healthcare, and manufacturing. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Software Engineer.
Quantitative Analyst
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze financial data and make investment decisions. Quantitative Analysts can work in a variety of financial institutions, including investment banks, hedge funds, and pension funds. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Quantitative Analyst.
Business Analyst
Business Analyst
A Business Analyst uses data to understand business problems and develop solutions. Business Analysts can work in a variety of industries, including finance, healthcare, and manufacturing. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Business Analyst.
Product Manager
Product Manager
A Product Manager manages the development and launch of new products. Product Managers can work in a variety of industries, including technology, healthcare, and retail. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Product Manager.
Data Engineer
Data Engineer
A Data Engineer designs and builds data pipelines to collect, store, and process data. Data Engineers can work in a variety of industries, including finance, healthcare, and manufacturing. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Data Engineer.
Actuary
Actuary
An Actuary uses mathematical and statistical models to assess risk and uncertainty. Actuaries can work in a variety of industries, including insurance, finance, and healthcare. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Actuary.
Market Researcher
Market Researcher
A Market Researcher conducts research to understand market trends and customer needs. Market Researchers can work in a variety of industries, including technology, healthcare, and retail. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Market Researcher.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
An Artificial Intelligence Engineer designs and builds artificial intelligence systems. Artificial Intelligence Engineers can work in a variety of industries, including technology, healthcare, and manufacturing. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Artificial Intelligence Engineer.
Machine Learning Researcher
Machine Learning Researcher
A Machine Learning Researcher conducts research to develop new machine learning algorithms and techniques. Machine Learning Researchers can work in a variety of settings, including academia, industry, and government. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Machine Learning Researcher.
Operations Research Analyst
Operations Research Analyst
An Operations Research Analyst uses mathematical and statistical models to solve business problems. Operations Research Analysts can work in a variety of industries, including finance, healthcare, and manufacturing. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Operations Research Analyst.
Statistician
Statistician
A Statistician collects, analyzes, and interprets data. Statisticians can work in a variety of industries, including finance, healthcare, and manufacturing. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Statistician.
Data Analyst
Data Analyst
A Data Analyst analyzes data to identify trends and patterns. Data Analysts can work in a variety of industries, including finance, healthcare, and manufacturing. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Data Analyst.
Financial Analyst
Financial Analyst
A Financial Analyst analyzes financial data to make investment decisions. Financial Analysts can work in a variety of financial institutions, including investment banks, hedge funds, and pension funds. The AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer course can help you build a foundation in machine learning and develop the skills you need to become a successful Financial Analyst.
For more career information including salaries, visit:
OpenCourser.com/course/vkrjbw/aws
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
AWS Machine Learning: Putting Machine Learning in the Hands of Every Developer.
Practical guide to machine learning with Python. It covers a wide range of topics, from data preprocessing to model evaluation. It is written in a clear and concise style, and it is packed with practical examples and exercises.
Gentle introduction to machine learning. It covers the basics of machine learning, such as supervised learning, unsupervised learning, and model evaluation. It is written in a clear and concise style, and it is packed with practical examples and exercises.
Provides a more theoretical treatment of machine learning. It covers topics such as probability theory, Bayesian inference, and optimization. It is written in a clear and concise style, and it is packed with practical examples and exercises.
Save
Comprehensive overview of deep learning. It covers a wide range of topics, from the basics of deep learning to advanced topics such as generative adversarial networks. It is written in a clear and concise style, and it is packed with practical examples and exercises.
Comprehensive overview of natural language processing with Python. It covers a wide range of topics, from the basics of natural language processing to advanced topics such as machine translation. It is written in a clear and concise style, and it is packed with practical examples and exercises.
Save
Comprehensive overview of computer vision. It covers a wide range of topics, from the basics of computer vision to advanced topics such as object recognition and image segmentation. It is written in a clear and concise style, and it is packed with practical examples and exercises.
Comprehensive overview of reinforcement learning. It covers a wide range of topics, from the basics of reinforcement learning to advanced topics such as deep reinforcement learning. It is written in a clear and concise style, and it is packed with practical examples and exercises.
Comprehensive overview of machine learning with R. It covers a wide range of topics, from the basics of machine learning to advanced topics such as deep learning. It is written in a clear and concise style, and it is packed with practical examples and exercises.
Comprehensive overview of machine learning in action. It covers a wide range of topics, from the basics of machine learning to advanced topics such as deep learning. It is written in a clear and concise style, and it is packed with practical examples and exercises.
Comprehensive overview of machine learning with Java. It covers a wide range of topics, from the basics of machine learning to advanced topics such as deep learning. It is written in a clear and concise style, and it is packed with practical examples and exercises.
Comprehensive overview of machine learning for Android developers. It covers a wide range of topics, from the basics of machine learning to advanced topics such as deep learning. It is written in a clear and concise style, and it is packed with practical examples and exercises.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/vkrjbw/aws
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