AWS Certified Machine Learning Specialty 2021- Hands On!

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

[ 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.

David Kolb

Thanks to Frank and Stephane for this excellent course. This helped me pass the AWS Machine Learning Specialty in January 2021. I have studied machine learning for some time, but this course was essential in honing the skills required to pass the exam. The course covers all the necessary AWS and Machine learning topics included in the AWS Machine Learning Specialty and they are presented in a clear and precise way.

Sally Liu

This course is concise and no-fluff — covering the essential things you need to know to pass the exam. I spent 29 hours total to prepare for the exam and pass it 970/1000.

Hayelom Weldemariam

Great all around course and very helpful – covers everything on the exam.

Ramanujam Mangena

Successfully passed the exam! Course is to the point and easy to recap all the areas. But remember that actual exam questions could be tricky. Good Luck!!

Christian Orrego

Excellent course. I just got my certification !!! Thanks.

Course Instructors

Frank Kane Author

Our courses are led by Frank Kane, a former Amazon and IMDb developer with extensive experience in machine learning and data science. With 26 issued patents and 9 years of experience at the forefront of recommendation systems, Frank brings real-world expertise to his teaching. His ability to explain complex concepts in accessible terms has helped over one million students worldwide gain valuable skills in machine learning, data engineering, and AI development.

Stephane Maarek Author

Stephane is a solutions architect, consultant and software developer that has a particular interest in all things related to Big Data, Cloud & API. He's also a many-times best seller instructor on Udemy for his courses in Apache Kafka and AWS. Stéphane is recognized as an AWS Hero and is an AWS Certified Solutions Architect Professional & AWS Certified DevOps Professional. He loves to teach people how to use the AWS properly, to get them ready for their AWS certifications, and most importantly for the real world. He also loves Apache Kafka. He sits on the 2019 Program Committee organizing the Kafka Summit in New York, London and San Francisco. He is also an active member of the Apache Kafka community, authoring blogs on Medium and a guest blog for Confluent. During his spare time he enjoys cooking, practicing yoga, surfing, watching TV shows, and traveling to awesome destinations!