AWS Certified Machine Learning Specialty Full Practice Exam

Detailed AWS Machine Learning (MLS-C01) certification experience

Since it feels like everybody who passes a certification has to post this on reddit, here is my post :)

Passed the MLS-C01 certification recently. There is not that much detailed info on the exam compared to other popular AWS certifications, so I want to give as detailed information as possible so everybody who is looking into this certification will have a better idea what he can expect from the exam.

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While preparing for SAA-C02 has a gold standard by using adrian cantrill's and/or stephane maarek's course in conjunction with john bonso's exam questions there is nothing comparable for the AWS Machine Learning Certification. I used both available courses from Linux Academy as well as ACloudGuru. Neither of those alone will get you the certification, but both give a very good overview of topics contained in the exam.

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Stuff I already knew:

• did a data science bootcamp a while ago so I have a good understanding of the whole data science lifecycle and already completed couple data science projects myself
• already have the SAA-C02 certification which helps a lot when it comes to dismissing answers in the exam
• 10+ years experience with programming languages, RDS, various developing patterns and IT best practices

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Stuff that I used:

• LA MLS course (good overview)
• ACG MLS course (good overview)
• AWS SageMaker Documentation (main resource)
• Sagemaker DeepDive Playlist - https://www.youtube.com/watch?v=uQc8Itd4UTs&list=PLhr1KZpdzukcOr6jzmSrvYnLUtgqsZz (very good imo)
• Bunch of SageMaker presentations from re:invent (mainly 3xx/4xx)
• AWS Blog (imo most of the scenario based questions in the exam are coming from case studies from the blog)
• Udemy Practice Exam by Abhishek Singh [https://www.udemy.com/course/aws-certified-machine-learning-specialty-full-practice-exams/]
• => very, very good questions which come pretty close to the style of the real exam questions
• Udemy Practice Exam by Frank Kane [https://www.udemy.com/course/aws-machine-learning-practice-exam/]
• => imo a lot weaker (not as close to the exam questions) exam than the one from Singh, still worth the money to find blank spots

Stuff that got mentioned in the exam I had no idea what it does:

• AWS Service Catalog
• AWS Connect
• AWS Alexa Business

Stuff that got asked in the exam

• no questions about hyperparameter, input types, parallelization of built-in algorithms
• LOTS of questions regarding pre-processing of datasets
• dropping/imputation, oversampling
• dealing with skewed datasets (log-transform, binning, etc)
• what to do with correlating/depending features in linear regression
• how to scale and split a dataset correctly (split then scale training and fit test/validation vs scale all and split afterwards, etc)
• mitigation of high/low correlation in datasets with lots of raw features
• what to look for in features (high correlation vs low correlation, etc)
• lots of questions about dealing with over- and underfitting in general and specifically in neural nets
• dropout, early stopping, decrease number of hidden layers,... in all variations and scenarios
• regularization (L1 vs L2)
• evaluation metrics
• trick question with switching positive/negative observations so you have to adjust to that
• business implications of mis-classification (FN more/less impact on cost of business, etc)
• calculate accuracy and precision
• interpret 3x3 confusion matrix
• visualization
• best visualization types for various situations
• visualization for correlation of features (scatter plots)
• custom algorithms
• docker container (which services are used ECR? ECS? both? S3?)
• process of deploying an algorithm in a custom docker container
• docker related questions about entrypoints, paths (/opt/ml,...)
• transfer learning
• hyperparamter optimization
• xgBoost init statement - which hyperparameter to optimize when overfitting
• neural net - learning rate/batch size tuning
• scaling/load balancing
• Endpoint Configuration calculate InvokePerInstance based on given numbers
• TensorFlow scaling horovod
• 2 tricky question with IoT devices and managing endpoints vs using Neo
• algorithm choices
• business scenarios, which algo to use
  • regression scenario
  • recommendation scenario
  • binary classification
• anomaly detection scenario - which algorithm to use
• chaining of AWS Services (most of them regarding ETL)
• scenarios where you should chain services/algorithms as solutions (transcribe, translate,..)
• classical ETL questions: Glue vs Data Pipeline vs Kinesis (in combination with Lambda, Elasticsearch,...)
• EMR related questions \[PySpark integrated solutions, "EMR legacy solution" inclusion, ...\]
• SageMaker Security
• company has certain standards regarding tags, instance-types - how can this accomplished? (aws service catalog vs python script vs cloudformation script vs ...)
• generic question
• optimized filetypes for Athena
• Normal vs Poisson-Distribution
• Baysian Network/Naive Bayes/Pearson co-effcient
• Classification Scenario: Which algorithm to use ? (classic SVM RBF Kernel plot - probably all you need to know about SVM)
• Question regarding activiation function of NN in certain scenario (Softmax vs ReLu vs ...)

Recommendations for AWS Certified Machine Learning Speciality exam preparation?

I'd like materials targeted at the exam.

I would particularly like practice tests, with clear explanations for right and wrong answers. I have found these, and will appreciate appraisals of their quality: Sundog@Udemy, Singh@Udemy, Ahmed@Udemy, ExamRealSkills@Udemy (Course&ExamPrep), Frlez/Udemy, Whizlabs

I'll appreciate appraisals of course materials. I have found: Sundog@Udemy , ACloudGuru, AWS's own training, Coursera, and Linux Academy

Is there a good book? Mengle Mastering Machined Learning on AWS is the only one that I have found

>Thanks!
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>You seem to have to great foundations to pass this exam! Should be easy for you if you are familiar with both ML and AWS. As for rank, my opinion on ranked list from best to worst is:

1. https://www.udemy.com/course/aws-machine-learning-practice-exam/
2. https://www.udemy.com/course/aws-machine-learning/
3. https://www.whizlabs.com/aws-certified-machine-learning-specialty/practice-tests/
4. https://acloud.guru/learn/aws-certified-machine-learning-specialty

IMO the practice tests are best bang for your bucks. They really give my some indication where you are lacking in skills and knowledge. ML part is quite easy with this test if you are familiar with basic ML and DL algorithms.

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Best of luck on your studies and test!