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AWS: Machine Learning & MLOps Foundations · LearnSpace
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AWS: Machine Learning & MLOps Foundations

Курс от Whizlabs
Средний≈ 5.8 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

"AWS: Fundamentals of Machine Learning & MLOps is the first course of Exam Prep (MLA-C01): AWS Certified Machine Learning Engineer – Associate Specialization. This course assists learners in building foundational knowledge of core machine learning concepts, including types of learning, data preparation, model evaluation, and operationalization. Learners gain a strong understanding of the difference between AI, Deep Learning, and Machine Learning, and how to identify and apply real-world ML use cases using AWS services. This course allows learners to explore key topics such as model selection, classification workflows, confusion matrices, and regression evaluation techniques. In addition, learners are introduced to the concepts of MLOps and the AWS services used to streamline ML deployment and monitoring in production environments. The course is divided into two modules, and each module is further segmented by Lessons and Video Lectures. This course facilitates learners with approximately 2:30–3:00 hours of video lectures that provide both theory and hands-on knowledge using AWS tools. Also, Graded and Ungraded Quizzes are provided with every module to test the understanding and application readiness of learners." Module 1: Machine Learning and MLOps Concepts Module 2 : Model Development & Evaluation Techniques By the end of this course, learners will be able to: - Apply foundational machine learning and MLOps concepts using AWS tools - Build and evaluate ML models with services like Amazon SageMaker - Understand end-to-end ML workflows, including data preparation, model training, and deployment - Strengthen their preparation for the AWS Certified Machine Learning Engineer – Associate (MLA-C01) exam This course is ideal for aspiring ML practitioners, data engineers, and developers with 6 months to 1 year of AWS experience who want to build practical skills in machine learning and MLOps. It also supports learners preparing for the AWS Certified Machine Learning Engineer – Associate (MLA-C01) exam and professionals seeking hands-on knowledge of implementing and managing ML workflows using AWS services.

Навыки, которые вы освоите

Model EvaluationMLOps (Machine Learning Operations)Machine LearningAWS SageMakerMachine Learning AlgorithmsSupervised LearningApplied Machine LearningPredictive ModelingData PreprocessingArtificial Intelligence and Machine Learning (AI/ML)Data ProcessingUnsupervised LearningModel DeploymentMachine Learning MethodsClassification AlgorithmsAmazon Web ServicesModel Training

Программа курса

2 модулей · 29 учебных материалов

01Machine Learning Concepts & Use Cases [Machine Learning and MLOps Concepts & Use Cases]14 материалов

Foundations of Machine Learning & Use Cases

Welcome to SpecializationВидеоWelcome to the CourseЧтениеOverview of Machine Learning Concepts & Use CasesЧтениеWhat is Machine Learning?Видео

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Преподаватель курса

AWS: Machine Learning & MLOps Foundations
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Обучение на Coursera

≈ 5.8 ч

2 модулей

Язык: Английский

Субтитры: Дари, Казахский, Пушту

Часть программы вашего университета
Understanding difference - AI Vs Deep Learning Vs Machine LearningВидео
Types of DataВидео
Types of Machine LearningВидео
Identify the Machine Learing Use CaseВидео
Steps for Machine LearningВидео
AWS Services for Machine LearningВидео
What is MLOps ?Видео
AWS Services for MLOpsВидео
Foundations of Machine Learning & Use Cases - Knowledge CheckЗадание
Machine Learning Concepts & Use Cases [Machine Learning and MLOps Concepts & Use Cases] - AssessmentЗадание
02Model Development & Evaluation Techniques15 материалов

Building, Training & Evaluating ML Models

Overview of Model Development & Evaluation TechniquesЧтениеClassification task - DemoВидеоModel Selection, Training and EvaluationВидеоData Preprocessing EssentialsВидеоEvaluating Classification ModelsВидеоConfusion MatrixВидеоExamples of Interpretation of Confusion MatrixВидеоEvaluation Metrics - RegressionВидеоMeet and GreetОбсуждениеUnsupervised Learning - ClusteringВидеоTypes of Inferencing - When to Use What ?ВидеоBuilding, Training & Evaluating ML Models - Knowledge CheckЗаданиеModel Development & Evaluation Techniques - AssessmentЗаданиеCourse ConclusionЧтениеWhat's Next ? Чтение