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AWS Certified Machine Learning - Specialty
Coursera
Course
Unknown

AWS Certified Machine Learning - Specialty

Pearson

Develop advanced skills to automate machine learning tasks on the cloud, including data preparation, model training, and deployment using AWS tools.

Unknown1 weeksEnglish

About this Course

Achieving a cloud-based machine learning certification demonstrates a high level of versatility and expertise as a machine learning engineer. Traditionally, professionals in this field concentrate on tasks such as data handling and model creation. However, possessing skills in utilizing cloud tools significantly enhances your value, especially in roles related to machine learning operations. With this certification, you gain the ability to independently manage the entire machine learning workflow. This includes ingesting and preparing data, performing feature engineering, training and evaluating models, and deploying them to environments where they can be accessed and used effectively. Such comprehensive capabilities are essential for operationalizing machine learning solutions, ensuring that models are not only accurate but also scalable, maintainable, and seamlessly integrated into business processes. The certification serves as proof that you can handle both the technical and practical aspects of machine learning projects, from start to finish. It highlights your proficiency in full-stack development within the machine learning domain, making you a valuable asset to organizations seeking robust and efficient solutions. In summary, this credential validates your ability to execute end-to-end machine learning tasks using advanced cloud technologies, setting you apart in the competitive landscape of data science and artificial intelligence

What You'll Learn

  • Master strategies to pass the AWS Certified Machine Learning – Specialty exam
  • Implement data ingestion solutions with Amazon Kinesis for large data streams
  • Deploy machine learning models using AWS tools
  • Manage the complete machine learning lifecycle effectively

Prerequisites

  • Basic familiarity with machine learning and cloud computing concepts
  • Readiness to practice through applied exercises or case-based work

Instructors

P

Pearson

M

Milecia McGregor

Senior Staff Engineer

Topics

Algorithms
Computer Science
Data Processing
Data Pipelines
Extract, Transform, Load
Model Deployment
Application Deployment
Data Preprocessing
Predictive Modeling
Cloud Deployment

Course Info

PlatformCoursera
LevelUnknown
PacingUnknown
PriceFree

Skills

الخوارزميات
علوم الحاسوب
معالجة البيانات
أنابيب البيانات
استخراج وتحويل وتحميل
نشر النماذج
نشر التطبيقات
تحضير البيانات
Predictive Modeling
Cloud Deployment

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