Developing Machine Learning Applications

Course Modality

Instructor-led (classroom)

Course Level

ADVANCED

Course Time

2.5 HOURS

Course Language

ENGLISH

Course Overview

In this curriculum, we’ll explore Amazon’s fully managed ML platform, Amazon SageMaker. Specifically, we’ll discuss how to train and tune models, how certain algorithms are built in, how you can bring your own algorithm, and how to build for particular use cases like recommender systems or anomaly detection.

Why The DataTech Labs ?

Self-Paced Online Video

A 360-degree learning approach that you can adapt to your learning style

A 360-degree learning approach that you can adapt to your learning style

Engage and learn more with these live and highly-interactive classes alongside your peers

24/7 Teaching Assistance

24/7 Teaching Assistance Keep engaged with integrated teaching

Online Practice Labs

Projects provide you with sample work to show prospective employers.

Applied Projects

Real-world projects relevant to what you’re learning throughout the program

Learner Social Forums

A support team focused on helping you succeed alongside a peer community

Course Curriculum

Introduction to Amazon SageMaker

Introduction to Amazon SageMaker Neo

Machine Learning Algorithms Explained

Automatic Model Tuning in Amazon SageMaker

Advanced Analytics with Amazon SageMaker

Anomaly Detection on AWS

Building Recommendation Systems with MXNet and GluOn

Recommended Exams

b

AWS Certified Machine Learning – Specialty

The AWS Certified Machine Learning - Specialty certification is intended for individuals who perform a development or data science role. It validates a candidate's ability to design, implement, deploy, and maintain machine learning (ML) solutions for given business problems

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