AWS Machine Learning – Specialty Certification Preparation

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DifficultyAdvanced
AVG Duration53h
Students3177
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Description

Learning Path Overview

Specifically designed to help you prepare for the AWS Machine Learning - Specialty Certification, this preview learning path provides interactive content comprised of hands-on labs and video courses. This training content has been carefully created to help you study for this AWS certification. 

Learning Objectives

The aim of the certification is to validate your knowledge across a number of different key areas, which have been defined by AWS as being able to:

  • Select and justify the appropriate ML approach for a given business problem.
  • Identify appropriate AWS services to implement ML solutions.
  • Design and implement scalable, cost-optimized, reliable, and secure ML solutions.

As a means of demonstrating this knowledge, you will be tested across six different domains, with each domain contributing to a total percentage of your overall score. These domains are broken down as:

  • Domain 1: Data Engineering 20% 
  • Domain 2: Exploratory Data Analysis 24% 
  • Domain 3: Modelling 36% 
  • Domain 4: Machine Learning Implementation and Operations 20% 

Intended Audience 

This learning path is suitable for those wanting to pass the AWS Machine Learning - Specialty Certification Exam.

Prerequisites

This is one of the four specialty level certifications available with AWS and it's guided to those who already have experience with AWS, and ideally have already passed an Associate level Exam providing some foundation knowledge of AWS. In addition to this, it is recommended you have experience developing, architecting, or running ML/deep learning workloads on the AWS Cloud, but these are not prerequisites in taking this certification. 

Feedback

We welcome all feedback and suggestions - please contact us at support@cloudacademy.com if you are unsure about where to start or if you would like help getting started. 

Certificate

Your certificate for this learning path
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Training Content

1
Course - Beginner - 10m
Introduction to AWS Machine Learning – Specialty Certification Preparation
This course introduces the AWS Certified Machine Learning - Specialty learning path which prepares you to take the certification exam.
2
Course - Beginner - 11m
Observations on the AWS Machine Learning - Specialty Exam
In this course, follow along with AWS certification specialist, Stephen Cole, as he discusses his experience taking the AWS Machine Learning - Specialty Exam.
3
Course - Beginner - 48m
Introduction to Machine Learning Concepts
In this course, you'll learn about Machine Learning and where it fits within the wider Artificial Intelligence (AI) field.
4
Course - Beginner - 37m
Introduction to Data and Machine Learning
This course has been expertly created to provide you with a strong foundation in machine learning and deep learning.
5
Course - Beginner - 1h 23m
Module 0 - What is Machine Learning? - Part One
This course is the first in a two-part series covering the fundamentals of machine learning.
6
Course - Beginner - 1h 30m
Module 0 - What is Machine Learning? - Part Two
This course is part two of the module on machine learning and covers unsupervised learning, the theoretical basis for machine learning, model and linear regression, the semantic gap, and how we approximate the truth.
7
Exam - 35m
Knowledge Check: Practical Machine Learning - Module 0
Knowledge Check: Practical Machine Learning - Module 0
8
Course - Intermediate - 1h 26m
Working with Distributed Machine Learning
This course covers Distributed Machine Learning, Apache Spark, Amazon Elastic Map Reduce, Spark MLib, and AWS Glue.
9
Hands-on Lab - Intermediate - 1h 40m
TensorFlow Machine Learning on the Amazon Deep Learning AMI
Develop, visualize, serve, and consume a TensorFlow machine learning model using the Amazon Deep Learning AMI in this Lab.
10
Hands-on Lab - Beginner - 45m
Analyzing CPU vs GPU Performance for AWS Machine Learning
Take control of a p2.xlarge instance equipped with an NVIDIA Tesla K80 GPU to perform CPU vs GPU performance analysis for AWS Machine Learning in this Lab.
11
Course - Beginner - 52m
Module 1 – Python for Machine Learning
This course covers the basics of python in machine learning, how to use loops, regressions, and classification, and how to set up machine learning in python.
12
Exam - 45m
Knowledge Check: Practical Machine Learning - Module 1
Knowledge Check: Practical Machine Learning - Module 1
13
Course - Beginner - 1h 5m
Getting Started With Deep Learning: Working With Data
Learn the ways in which data comes in many forms and formats with this course.
14
Course - Beginner - 2h 4m
Getting Started with Deep Learning: Introduction To Machine Learning
This course covers the foundations and history of machine learning as well as the principles of memory storage, computing power, and phone/web applications.
15
Exam - 30m
Knowledge Check: Zero to Deep Learning - Introduction to Data Science and Machine Learning
Knowledge Check: Zero to Deep Learning - Introduction to Data Science and Machine Learning
16
Course - Beginner - 1h 45m
Module 2 - Maths for Machine Learning - Part One
This course is the first part of the two-part series on the mathematics of machine learning.
17
Course - Beginner - 1h 32m
Module 2 - Maths for Machine Learning - Part Two
This course is the second part of the two-part series on the mathematics of machine learning.
18
Exam - 55m
Knowledge Check: Practical Machine Learning - Module 2
Knowledge Check: Practical Machine Learning - Module 2
19
Course - Beginner - 1h 13m
Introduction to Deep Learning
This course gives an informative introduction to deep learning and introducing neural networks.
20
Course - Beginner - 1h 45m
Getting Started With Deep Learning: Working With Data: Gradient Descent
This course expertly covers the essentials needed to succeed in machine learning.
21
Exam - 30m
Knowledge Check: Zero to Deep Learning - Introduction to Deep Learning
Knowledge Check: Zero to Deep Learning - Introduction to Deep Learning
22
Course - Beginner - 1h 19m
Getting Started With Deep Learning: Convolutional Neural Networks
In this course, discover convolutions and the convolutional neural networks involved in Data and Machine Learning.
23
Course - Beginner - 45m
Getting Started With Deep Learning: Recurrent Neural Networks
In this course, you'll learn how to use recurrent neural networks to train more complex models.
24
Course - Beginner - 1h 2m
Getting Started With Deep Learning: Improving Performance
In this course, you'll learn how to improve the performance of your neural networks with this learning path.
25
Exam - 30m
Knowledge Check: Zero to Deep Learning - Working with Convolutional and Recurrent Neural Networks
Knowledge Check: Zero to Deep Learning - Working with Convolutional and Recurrent Neural Networks
26
Course - Intermediate - 31m
Introduction to SageMaker
This course provides a practical understanding of the steps required to build and deploy machine learning models using Amazon SageMaker.
27
Course - Beginner - 32m
Get Started with Amazon SageMaker Data Wrangler, Data Pipeline, Feature Store and Ground Truth
Get started with the latest SageMaker Data Wrangler, Data Pipeline and Feature Store services (released at re:invent Dec 2020) and SageMaker Ground Truth
28
Course - Beginner - 1h
Module 3 - Supervised Learning - Part One
The course introduces you to supervised learning and the nearest neighbors algorithm.
29
Course - Beginner - 1h 52m
Module 3 - Supervised Learning - Part Two
This course explores hyperparameters, distance functions, similarity measures, logistic regression, the method and workflow of machine learning and evaluation, and the train-test split.
30
Exam - 45m
Knowledge Check: Practical Machine Learning - Module 3
Knowledge Check: Practical Machine Learning - Module 3
31
Hands-on Lab - Intermediate - 1h
Using SageMaker Notebooks to Train and Deploy Machine Learning Models
In this lab, you'll use a SageMaker notebook to learn how to write Python code to prepare data, train and deploy models, and use them for real-time inference.
32
Hands-on Lab - Beginner - 2h
Amazon SageMaker Notebook Playground
This playground lab allows you to choose from Amazon's curated library of sample notebooks to learn about what is most important to you.
33
Hands-on Lab - Beginner - 1h 30m
Forecast Flight Delays with Amazon SageMaker
This lab uses Amazon SageMaker to create a machine learning model that forecasts flight delays for US domestic flights.
34
Exam - 25m
Knowledge Check: Start Modeling Data with Amazon SageMaker
Knowledge Check: Start Modeling Data with Amazon SageMaker
35
Course - Beginner - 48m
Module 4 - Model Selection
Selecting the right machine learning model will help you find success in your projects. In this module, we’ll discuss how to do so, as well the difference between explanatory and associative approaches, before we end on how to use out-sample performance.
36
Exam - 45m
Knowledge Check: Practical Machine Learning - Module 4
Knowledge Check: Practical Machine Learning - Module 4
37
Course - Intermediate - 55m
Common Machine Learning Models & How to Train Them
This course explores the core concepts of machine learning, the models available, and how to train them.
38
Hands-on Lab - Beginner - 2h 30m
Machine Learning - Training Custom Models
This lab is aimed at machine learning beginners who want to understand how to train custom models.
39
Hands-on Lab - Intermediate - 1h
Evaluating Binary Classification Models
This lab will walk you through building several binary classification models using different model methodologies and then comparing the model predictions using evaluation tools.
40
Hands-on Lab - Beginner - 1h
Testing Your Models in the Real World
How do you know that your models will do a good job making predictions on new, unseen data? This lab will discuss the fundamentals.
41
Exam - 30m
Knowledge Check: Getting Started with Machine Learning Models
Knowledge Check: Getting Started with Machine Learning Models
42
Course - Beginner - 36m
Module 5 - Regression
Regression is a widely used machine learning and statistical tool and it’s important you know how to use it. In this module, we’ll discuss interpreting modes, as well as how to interpret linear classification models.
43
Hands-on Lab - Intermediate - 43m
Evaluating Model Predictions for Regression Models
This lab walks you through building several multivariate linear regression models using different prediction variables and evaluating the models' predictions.
44
Exam - 30m
Knowledge Check: Practical Machine Learning - Module 5
Knowledge Check: Practical Machine Learning - Module 5
45
Course - Beginner - 55m
Module 6 - Unsupervised learning
This course covers the concept of unsupervised learning within the context of machine learning and how unsupervised learning differs from supervised learning.
46
Course - Beginner - 1h 3m
Module 7 - Probability and statistics
This course explores the topic of probability and statistics, including various mathematical approaches and some different interpretations of probability.
47
Course - Beginner - 1h 11m
Introduction to Amazon Rekognition
In this course, you'll learn about Amazon Rekognition, a service that enables you to easily and quickly integrate computer vision features directly into your own applications.
48
Hands-on Lab - Intermediate - 1h
Handling Missing Data
This lab will walk you through a number of ways to handle missing data including using a default value and building a model to predict the missing data.
49
Hands-on Lab - Beginner - 1h
Automate Image Labeling with Amazon Rekognition
Learn how to implement object detection on every new image uploaded on Amazon S3.
50
Course - Intermediate - 49m
Working with Amazon Lex - Chatbots
In this course, you'll learn about the key features and components of Amazon Lex, and how to develop, configure, and build an end-to-end Chatbot using the Lex service.
51
Hands-on Lab - Intermediate - 1h 10m
Using an MXNet Neural Network to Style Images
Join this Lab and gain experience using an MXNet convolutional neural network to style images and monitor the GPU used for training in Amazon CloudWatch.
52
Course - Intermediate - 1h 12m
FREE
AWS: Overview of AWS Identity & Access Management (IAM)
This course explains AWS Identity & Access Management (IAM), what it is, and how to implement it.
53
Hands-on Lab - Intermediate - 1h 15m
UPDATED
Advanced Roles and Groups Management Using IAM
Learn how to manage our organization using IAM Users and Groups and IAM Roles 
54
Exam - 35m
FREE
Knowledge Check: Overview of AWS Identity and Access Management (IAM)
Knowledge Check: Overview of AWS Identity and Access Management (IAM)
55
Course - Beginner - 1h 28m
FREE
Storage Fundamentals for AWS
This course covers the wide range of storage services within AWS, their key features, and when and why you would use them.
56
Course - Beginner - 52m
Designing Secure Applications and Architectures
In this course, you'll learn to recognize and explain what encryption is at a high level as well as the various encryption options provided by AWS.
57
Course - Intermediate - 48m
Using Amazon S3 Bucket Properties & Management Features to Maintain Data
This course will look at some of the management and bucket property features that Amazon S3 has to offer, and how you can use them to maintain and control your data.
58
Course - Intermediate - 22m
Amazon S3: Data Replication and Bucket Key Encryption
This course explores two different Amazon S3 features: the replication of data between buckets and bucket key encryption when working with SSE-KMS to protect your data.
59
Course - Intermediate - 1h 10m
How to Use KMS Key Encryption to Protect Your Data
In this course, you will learn the basics of KMS, what it will cost to implement, how to encrypt data, and more...
60
Exam - 30m
FREE
Knowledge Check: AWS Storage Fundamentals
Knowledge Check: AWS Storage Fundamentals
61
Course - Intermediate - 13m
AWS Step Functions
This course introduces AWS Step Functions and its uses, benefits, and limitations.
62
Hands-on Lab - Intermediate - 1h 30m
Introduction to AWS Step Functions
Learn how to use AWS Step Functions.
63
Course - Intermediate - 32m
Analyzing Data with Amazon Athena
This course explores the AWS Athena service, reviewing fundamental AWS Athena storage and querying concepts.
64
Hands-on Lab - Beginner - 1h 20m
Query encrypted Amazon S3 data with Amazon Athena
Use Amazon Athena to query encrypted data on S3 and encrypt the query results as well.
65
Course - Beginner - 32m
Developing Serverless ETL with AWS Glue
This course will take you through the fundamentals of AWS Glue to get you started with the service.
66
Course - Beginner - 15m
Overview of Amazon Kinesis
This course provides an introduction to Amazon Kinesis including what it does and why it's important.
67
Course - Advanced - 40m
Working with Amazon Kinesis Analytics
In this course, you'll learn about the key features and core components of Kinesis Analytics, and what an end-to-end real-time data streaming example looks like.
68
Exam - 3h
Cert Prep: Certified Machine Learning - Specialty for AWS
Cert Prep: Certified Machine Learning - Specialty for AWS
About the Author
Students13238
Courses14
Learning paths4

Stephen is the AWS Certification Specialist at Cloud Academy. His content focuses heavily on topics related to certification on Amazon Web Services technologies. He loves teaching and believes that there are no shortcuts to certification but it is possible to find the right path and course of study.

Stephen has worked in IT for over 25 years in roles ranging from tech support to systems engineering. At one point, he taught computer network technology at a community college in Washington state.

Before coming to Cloud Academy, Stephen worked as a trainer and curriculum developer at AWS and brings a wealth of knowledge and experience in cloud technologies.

In his spare time, Stephen enjoys reading, sudoku, gaming, and modern square dancing.