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AWS Certified Machine Learning Specialty 2021 – Hands On! – Udemy

(10 customer reviews)

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Description

What you’ll 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

[ Updated for 2021’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 9-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

  • 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.

Who this course is for:

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

Course content

  • Introduction
  • Data Engineering
  • Exploratory Data Analysis
  • Modeling
  • ML Implementation and Operations
  • Wrapping Up
  • Practice Exams

10 reviews for AWS Certified Machine Learning Specialty 2021 – Hands On! – Udemy

  1. Donny Phan

    Super practical. Lessons are catered towards anyone looking to find work in this industry. It felt very comprehensive and gave me a broad understanding of the programming spectrum

  2. Madhav raj Verma

    Thanks for your great effort. i am fully satisfied with this course the way you teach and your explanation are very clear ,The content you provide in your course no one can do this at this price.

  3. Sachin Gupta

    I really didn’t want to leave a low rating as Angela is a great teacher. The 1st half of this course was terrific. The 2nd half was terrible. Under the justification of “teaching students how to figure things out on their own”, pretty much all videos and all explanations were dropped. You were just told what to do, given links to documentation and told to figure it out on your own. I understand doing that to some degree, but to revert to that entirely for nearly half the content barely makes this a course. It’s just a list of things for you to learn, then you’re left on your own to learn them. The 2nd half was so bad, especially the data science component, that I didn’t bother finishing the course.

  4. Vincent Beaudet

    Amazing 40 days course.
    Angela is a great teacher.
    The other 60 days are all about web developement, interacting with web pages, on your own with little to no explanations. I did not expect that at all. I wanted to learn more about software and scripting.
    This left me disappointed , confused and i started to doubt myself. Not a fun experience after the amount of effort i’v put in this course.

    Exercices format and explanations for the first 40 days were worth it tho.

  5. Ben K

    Not just an introduction to python, but really helps you learn fundamental aspects of python and coding in general. Some parts may require some knowledge on the subject (data science comes to mind) and there is quite some web development in the course. So, a few areas were not completely to my liking (I would have liked to see it done differently), but this course deserves the 5 stars in my opinion.

  6. Omid Alikhel

    I found the method a bit difficult when a code is written and then changed back to something different, with no enough explanation of how something happened and where it came from or a step by step explanation of why something is happening, i have no doubt in the instructors talent, but we are beginners!

  7. Alica Cverdeľová

    I love this course, Angela explained it very easily and clearly from the beginning, but I loved her 1 minute final videos, which ended later: What a pity.
    BUT I felt a little disappointed now with the project Day 39/40. Where I was maximally lost, I could not come out of where to look for anything and it was poorly explained and the biggest mistake was that there were no videos with explanations, I think it was quite a complicated project where many things were used and no explanation, only the final results. And they carried a few things in the projects before, so I had her project run once and it showed her the mistake as well as me, so in that case you have to leave it at that and what else is a shame. It’s hard to do a project when you don’t see what’s going on there.
    I’m a little worried about the next few weeks, and I hope it won’t be a waste of time.

  8. Szymon Kozak

    I think that the course tutor is really good in giving right information to learn at the right time. Thanks to this fact, my understanding of coding in python after 29 days of learning is above my expectations.

  9. Begoña Ruiz Diaz

    Ha sido la mejor elección que podría haber hecho.

  10. Vaibhav Sachdeva

    I want to thank Angela for making such an amazing course. It really helped me explore more things with python.

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