AWS Machine Learning Speciality

2750 Ratings (4.2)

The AWS Certified Machine Learning - Specialty (MLS-C01) examination is intended for individuals who perform a development or data science role. This exam validates an examinee’s ability to build, train, tune, and deploy machine learning (ML) models using the AWS Cloud.

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About the course

The AWS Certified Machine Learning - Specialty (MLS-C01) examination is intended for individuals who perform a development or data science role. This exam validates an examinee’s ability to build, train, tune, and deploy machine learning (ML) models using the AWS Cloud.

Since 2006, Amazon Web Services has been the world’s most comprehensive and broadly adopted cloud platform. AWS offers over 90 fully featured services for compute, storage, networking, database, analytics, application services, deployment, management, developer, mobile, Internet of Things (IoT), Artificial Intelligence, security, hybrid and enterprise applications, from 44 Availability Zones across 16 geographic regions. AWS services are trusted by millions of active customers around the world — including the fastest-growing startups, largest enterprises, and leading government agencies — to power their infrastructure, make them more agile, and lower costs. It also gives you the hands-on experience required to use machine learning and deep learning in a real-world environment.

This course starts off with coming to grips with Machine Learning (ML), Deep Learning (DL), and Artificial Intelligence (AI) terminology. After the theory comes the practice. You'll get hands-on with a number of ML frameworks and AWS services specific to the certification.

Course Contents

Introduction to Machine Learning
  • What is Machine Learning?
  • What is Artificial Intelligence?
  • What is Deep Learning?
  • Understanding Neural Networks
  • Machine Learning Algorithms Explained
Machine Learning Pipeline
  • The Machine Learning Process
Data
  • Introduction
  • Feature Selection and Engineering
  • Principal Component Analysis (PCA)
  • Missing and Unbalanced Data
  • Label and One Hot Encoding
  • Splitting and Randomization
  • RecordIO Format
Machine Learning Algorithms
  • Introduction
  • Logistical Regression
  • Linear Regression
  • Support Vector Machines
  • Decision Trees
  • Random Forests
  • K-Means
  • K-Nearest Neighbour
  • Latent Dirichlet Allocation (LDA) Algorithm)
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Course Prerequisites

The successful candidate likely has 1–2 years of hands-on experience developing, architecting, or running ML/deep learning workloads on the AWS Cloud, along with:

  • The ability to express the intuition behind basic ML algorithms
  • Experience performing basic hyperparameter optimization
  • Experience with ML and deep learning frameworks
  • The ability to follow model-training best practices
  • The ability to follow deployment and operational best practices

Who should attend?

  • Individuals performing a development or data science role seeking certification in machine learning and AWS

Number of Hours: 40hrs

Certification

AWS Certified Machine Learning – Specialty (MLS-C01)

Keyfeatures

  • One to One Training
  • Online Training
  • Fastrack & Normal Track
  • Resume Modification
  • Mock Interviews
  • Video Tutorials
  • Materials
  • Real Time Projects
  • Virtual Live Experience
  • Preparing for Certification

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