Compiled from AWS. Amazon, Heart of machine, participation: Si Yuan, Wang Shuting.
Starting today, anyone can access the machine learning courses Amazon uses to train its own engineers from AWS. Its 90 courses offer different learning paths for developers, business decision makers, data scientists and data platform engineers.
Courses address: aws.amazon.com/cn/training…
The program has been in place for more than 20 years. With thousands of in-house engineers specialising in machine learning, amazon’s retail pages, products, implementation technology and store are rarely without improvements. Many AWS customers have benefited, and now Amazon plans to make the courses available to all developers, not just the most powerful, well-funded tech companies.
Regardless of their level of machine learning, Amazon customers always ask the question, “How can our team accelerate the improvement of machine learning skills?” These open courses are part of the new AWS training and machine learning course certification and are now part of the answer to this question.
In all, there are more than 30 self-service, self-paced digital courses with more than 45 hours of lectures, videos, and LABS, all aimed at four key demographics: developers, data scientists, data platform engineers, and business people. Each course starts with the basics and is based on real-world cases and LABS, allowing developers to explore machine learning through some interesting problems that Amazon has already solved. These include predicting gift-wrapping eligibility, optimizing delivery routes or predicting entertainment award nominations using data from Amazon subsidiary IMDb. These courses help solidify best practices and show how to start a range of AWS machine learning services, These include Amazon SageMaker, AWS DeepLens, Amazon Rekognition, Amazon Lex, Amazon Polly, and Amazon Both.
The figure above shows an example of courses, in which there are 89 digital courses, each with a different goal and topic, so that specific courses can be strung together to form a specific learning path.
Choose your learning path
AWS machine learning courses have five main learning paths. There are four learning paths for developers, decision makers, data scientists, and data platform engineers, as well as a “test” path for engineers who want to gain AWS certification quickly, which requires a certain level of expertise.
Of course, developers can view the 90 courses directly and choose their own areas of interest, such as model security, application deployment, outlier detection or neural machine translation. The following is a brief description of the characteristics of each learning path, which can be selected by different readers according to their needs.
developers
This learning path is designed for builders and software developers who want to use machine learning and artificial intelligence to better collaborate with data scientists and innovate with machine learning techniques. The course starts with basic machine learning solutions and moves up to advanced courses, with the option to supplement your training with elective courses.
Data scientist
This path is designed for people who are good at math, statistics, and analytics and want to become a subject matter expert in machine learning within an organization or company. These individuals can take basic, intermediate, and advanced courses to learn how to apply machine learning frameworks and analytical tools to work and improve collaboration.
Data Platform Engineer
This approach mainly helps data skewness engineers understand how machine learning will change data acquisition, system configuration, system performance, and user experience of systems, services, and applications. The learning path mainly focuses on the concept and tools of machine learning, and focuses on the solutions and application practices of machine learning.
Corporate decision makers
This learning path is primarily intended for enterprise decision makers who want to use machine learning technologies for productization or for assisted management. The following courses focus on clarifying machine learning concepts or terms to help decision makers understand the true business value of machine learning.
advantage
Free digital Education: You can start building your ML skills on demand and now get flexible digital education for free.
Tailored learning path: Participate in training that matches your specific ML goals and new learning path. Amazon has also created a pathway to help developers and data scientists prepare for the new AWS ML certification.
Get AWS Certified: A new AWS Certified Machine Learning — Specialty — test that validates your expertise and helps you gain recognition in the industry.
Currently, users can take the new AWS Machine Learning certification test for a fee. Finally, the digital course is now available online for free, although there is a fee for services used in LABS and exams during training, so there is still a fee for using AWS computing services or other resources.
