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Course Contents
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In this one-day instructor-led training (ILT) course, you will learn how to assess your readiness for the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam. The exam validates a candidate's ability to build, operate, and maintain machine learning (ML) solutions and pipelines using the AWS Cloud.
This intermediate-level course prepares you for the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam by providing a comprehensive review of the exam topics. You will explore the key areas of the exam and understand how they relate to developing AI and machine learning solutions on the AWS platform. With detailed explanations and walkthroughs of exam-style questions, you will solidify your knowledge, identify gaps in your understanding, and gain valuable strategies for answering questions effectively. The course also includes review of exam-style sample questions to help you recognize incorrect answers and improve your test-taking skills. By the end of the course, you will have a solid grasp of the concepts and practical applications tested in the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam.
This course includes presentations on the topic, exam-style questions, use cases, and group discussions and activities.
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Target Group
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This course is aimed at people preparing for the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam.
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Knowledge Prerequisites
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You do not need to complete any specific training before attending this course. However, the following prior knowledge is recommended before taking the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam:
- One year of experience in a related role is recommended, e.g. as a backend software developer, DevOps developer, data engineer or data scientist.
- Basic understanding of common ML algorithms and their use cases
- Basics of data science, including knowledge of common data formats, data ingestion and transformation for working with ML data pipelines
- Knowledge of querying and converting data
- Knowledge of software engineering best practices for developing modular, reusable code, deployment and debugging
- Familiarity with provisioning and monitoring ML resources in the cloud and on-premise
- Experience with continuous integration and continuous delivery (CI/CD) and infrastructure as code (IaC)
- Experience with code repositories for version control and CI/CD pipelines
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Classroom training
- Do you prefer the classic training method? A course in one of our Training Centers, with a competent trainer and the direct exchange between all course participants? Then you should book one of our classroom training dates!
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Hybrid training
- Hybrid training means that online participants can additionally attend a classroom course. The dynamics of a real seminar are maintained, and the online participants are able to benefit from that. Online participants of a hybrid course use a collaboration platform, such as WebEx Training Center or Saba Meeting. To do this, a PC with browser and Internet access is required, as well as a headset and ideally a Web cam. In the seminar room, we use specially developed and customized audio- and video-technologies. This makes sure that the communication between all persons involved works in a convenient and fault-free way.
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Online training
- You wish to attend a course in online mode? We offer you online course dates for this course topic. To attend these seminars, you need to have a PC with Internet access (minimum data rate 1Mbps), a headset when working via VoIP and optionally a camera. For further information and technical recommendations, please refer to.
-
Tailor-made courses
-
You need a special course for your team? In addition to our standard offer, we will also support you in creating your customized courses, which precisely meet your individual demands. We will be glad to consult you and create an individual offer for you.
You can find the complete description of this course with dates and prices ready for download at as PDF.-
Course Contents
-
In this one-day instructor-led training (ILT) course, you will learn how to assess your readiness for the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam. The exam validates a candidate's ability to build, operate, and maintain machine learning (ML) solutions and pipelines using the AWS Cloud.
This intermediate-level course prepares you for the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam by providing a comprehensive review of the exam topics. You will explore the key areas of the exam and understand how they relate to developing AI and machine learning solutions on the AWS platform. With detailed explanations and walkthroughs of exam-style questions, you will solidify your knowledge, identify gaps in your understanding, and gain valuable strategies for answering questions effectively. The course also includes review of exam-style sample questions to help you recognize incorrect answers and improve your test-taking skills. By the end of the course, you will have a solid grasp of the concepts and practical applications tested in the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam.
This course includes presentations on the topic, exam-style questions, use cases, and group discussions and activities.
-
Target Group
-
This course is aimed at people preparing for the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam.
-
Knowledge Prerequisites
-
You do not need to complete any specific training before attending this course. However, the following prior knowledge is recommended before taking the AWS Certified Machine Learning Engineer - Associate (MLA-C01) exam:
- One year of experience in a related role is recommended, e.g. as a backend software developer, DevOps developer, data engineer or data scientist.
- Basic understanding of common ML algorithms and their use cases
- Basics of data science, including knowledge of common data formats, data ingestion and transformation for working with ML data pipelines
- Knowledge of querying and converting data
- Knowledge of software engineering best practices for developing modular, reusable code, deployment and debugging
- Familiarity with provisioning and monitoring ML resources in the cloud and on-premise
- Experience with continuous integration and continuous delivery (CI/CD) and infrastructure as code (IaC)
- Experience with code repositories for version control and CI/CD pipelines
-
Classroom training
- Do you prefer the classic training method? A course in one of our Training Centers, with a competent trainer and the direct exchange between all course participants? Then you should book one of our classroom training dates!
-
Hybrid training
- Hybrid training means that online participants can additionally attend a classroom course. The dynamics of a real seminar are maintained, and the online participants are able to benefit from that. Online participants of a hybrid course use a collaboration platform, such as WebEx Training Center or Saba Meeting. To do this, a PC with browser and Internet access is required, as well as a headset and ideally a Web cam. In the seminar room, we use specially developed and customized audio- and video-technologies. This makes sure that the communication between all persons involved works in a convenient and fault-free way.
-
Online training
- You wish to attend a course in online mode? We offer you online course dates for this course topic. To attend these seminars, you need to have a PC with Internet access (minimum data rate 1Mbps), a headset when working via VoIP and optionally a camera. For further information and technical recommendations, please refer to.
-
Tailor-made courses
-
You need a special course for your team? In addition to our standard offer, we will also support you in creating your customized courses, which precisely meet your individual demands. We will be glad to consult you and create an individual offer for you.
You can find the complete description of this course with dates and prices ready for download at as PDF.
Hybrid Training
Trainer language German