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AWS Certified Machine Learning Specialty 2022 - Hands On!

AWS machine learning certification preparation - learn SageMaker, feature engineering, data engineering, modeling & more

4.51 / 5.0
46827 students11 hours 9 minutes

Created by Sundog Education by Frank Kane, offered on Udemy

bestcourses score™

Student feedback

9/10

To make sure that we score courses properly, we pay a lot of attention to the reviews students leave on courses and how many students are taking a course in the first place. This course has a total of 46827 students which left 6953 reviews at an average rating of 4.51. Impressive!

Course length

8.9/10

We analyze course length to see if courses cover all important aspects of a topic, taking into account how long the course is compared to the category average. This course has a length of 11 hours 9 minutes, which is pretty short. This might not be a bad thing, but we've found that longer courses are often more detailed & comprehensive. The average course length for this entire category is 4 hours 29 minutes.

Overall score

8.9/10

This course currently has a bestcourses score of 8.9/10, which makes it a great course to learn from. On our entire platform, only 15% of courses achieve this rating!

Description

[ Updated for 2022's latest SageMaker features and new AWS ML Services. Happy learning! ]

Nervous about passing the AWS Certified Machine Learning - Specialty exam (MLS-C01)? You should be! There's no doubt it's one of the most difficult and coveted AWS certifications. A deep knowledge of AWS and SageMaker isn't enough to pass this one - you also need deep knowledge of machine learning, and the nuances of feature engineering and model tuning that generally aren't taught in books or classrooms. You just can't prepare enough for this one.

This certification prep course is taught by Frank Kane, who spent nine years working at Amazon itself in the field of machine learning. Frank took and passed this exam on the first try, and knows exactly what it takes for you to pass it yourself. Joining Frank in this course is Stephane Maarek, an AWS expert and popular AWS certification instructor on Udemy.

In addition to the 11-hour video course, a 30-minute quick assessment practice exam is included that consists of the same topics and style as the real exam. You'll also get four hands-on labs that allow you to practice what you've learned, and gain valuable experience in model tuning, feature engineering, and data engineering.

This course is structured into the four domains tested by this exam: data engineering, exploratory data analysis, modeling, and machine learning implementation and operations. Just some of the topics we'll cover include:

  • S3 data lakes

  • AWS Glue and Glue ETL

  • Kinesis data streams, firehose, and video streams

  • DynamoDB

  • Data Pipelines, AWS Batch, and Step Functions

  • Using scikit_learn

  • Data science basics

  • Athena and Quicksight

  • Elastic MapReduce (EMR)

  • Apache Spark and MLLib

  • Feature engineering (imputation, outliers, binning, transforms, encoding, and normalization)

  • Ground Truth

  • Deep Learning basics

  • Tuning neural networks and avoiding overfitting

  • Amazon SageMaker, including SageMaker Studio, SageMaker Model Monitor, SageMaker Autopilot, and SageMaker Debugger.

  • Regularization techniques

  • Evaluating machine learning models (precision, recall, F1, confusion matrix, etc.)

  • High-level ML services: Comprehend, Translate, Polly, Transcribe, Lex, Rekognition, and more

  • Building recommender systems with Amazon Personalize

  • Monitoring industrial equipment with Lookout and Monitron

  • Security best practices with machine learning on AWS

Machine learning is an advanced certification, and it's best tackled by students who have already obtained associate-level certification in AWS and have some real-world industry experience. This exam is not intended for AWS beginners.

If there's a more comprehensive prep course for the AWS Certified Machine Learning - Specialty exam, we haven't seen it. Enroll now, and gain confidence as you walk into that testing center.


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Instructor

My name is Stephane Maarek, and I'll be your co-instructor in this course. I teach about AWS certifications with my focus always on helping my students improve their professional proficiencies in AWS. I am also the author of some of the most highly-rated & best-selling courses on AWS Lambda, AWS CloudFormation & AWS EC2.

Throughout my career in designing and delivering these certifications and courses, I have already taught 1,000,000+ students and gotten 350,000+ reviews!

With AWS becoming much more than a buzzword out there, I've decided it's time for students to properly learn how to be an AWS Machine Learning Professional. So, let’s kick start the course! You are in good hands!

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Instructor

Hey, I'm Frank Kane, and I'm also instructing this course. I spent nine years working for Amazon from the inside as a senior engineer and senior manager, where my specialty was recommender systems and machine learning. As an instructor, I'm best known for my top-selling courses in "big data", data analytics, machine learning, Apache Spark, system design, and Elasticsearch.

I've been teaching on Udemy since 2015, where I've reached over 500,00 students all around the world!

I've worked hard to keep this course up to date with the latest developments in AWS machine learning, and to make sure you're prepared for the latest version of this exam. Let's dive in and get you ready!

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This course also comes with:

  • Lifetime access to all future updates

  • A responsive instructor in the Q&A Section

  • Udemy Certificate of Completion Ready for Download

  • A 30 Day "No Questions Asked" Money Back Guarantee!

Join us in this course if you want to prepare for the AWS Machine Learning Certification and master the AWS platform!

What you will learn

  • What to expect on the AWS Certified Machine Learning Specialty exam
  • Amazon SageMaker's built-in machine learning algorithms (XGBoost, BlazingText, Object Detection, etc.)
  • Feature engineering techniques, including imputation, outliers, binning, and normalization
  • High-level ML services: Comprehend, Translate, Polly, Transcribe, Lex, Rekognition, and more
  • Data engineering with S3, Glue, Kinesis, and DynamoDB
  • Exploratory data analysis with scikit_learn, Athena, Apache Spark, and EMR
  • Deep learning and hyperparameter tuning of deep neural networks
  • Automatic model tuning and operations with SageMaker
  • L1 and L2 regularization
  • Applying security best practices to machine learning pipelines

Requirements

  • Associate-level knowledge of AWS services such as EC2
  • Some existing familiarity with machine learning
  • An AWS account is needed to perform the hands-on lab exercises
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Frequently asked questions

  • Price: $94.99
  • Platform: Udemy
  • Language: English
  • 11 hours 9 minutes
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bestcourses score: 8.9/10

This course is better than many others in its category.