AWS Certified Machine Learning - Specialty Test 2021! (Udemy.com)

Get ready for your AWS Certified Machine Learning Specialty certification by taking this practice exam.

( 2 Reviews )

Created by: Demissew Kessela

Produced in 2021

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Overall Score : 70 / 100

Course Description

Realistic practice exam based on the most recent AWS Certified Machine Learning Specialty exam.
Just like the actual exam this practice test has 65 questions and takes 170 minutes.
Questions are mapped based on the actual exam domains:
- Data Engineering
- Exploratory Data Analysis
- Modeling
- Machine Learning Implementation and Operations.

Suggested background knowledge
- Data Engineering
  - AWS services:
    - Glue, EMR ( Apache Spark, Hive metastore), Athena
    - Kinesis family (Streams, data analytics, firehose, video streams)
    - S3, QuickSight
    - Data/File formats (Avro, Parquet, CSV, protobuf recordIO)
- Exploratory Data Analysis
  - Handling missing values (Imputation: median, mean, most frequent, using ML model)
  - Feature scaling
  - Feature engineering
  - Handling outliers
  - One-hot encoding
  - Binning
- Modeling
  - supervised machine learning ( Classification and Regression Algorithms)
  - unsupervised machine learning ( K-Means clustering, PCA)
  - Hyperparameter tuning ( supervised machine learning, deep learning)
  - Performance metrics ( accuracy, RMSE, F1 score, AUC, ROC, Precision, Recall)
  - Tuning deep learning networks ( how to prevent overfitting)
  - AWS services: SageMaker built-in algorithms, Lex, Polly, Transcribe, Translate, Comprehend
- ML Implementation and Operations
  - Amazon SageMaker train and deploy a model
    - Inference pipeline, batch transform, inference endpoints , production variants, hosting services
  - Amazon SageMaker security (data encryption at rest and in transit)
  - Distributed training on Amazon SageMaker ( Using GPUs)
  - AWS SageMaker roles
  - Bring your own model container ( e.g. developed using scikit-learn)
  - Customize SageMaker built-in algorithm containers
  - How to develop and deploy deep learning models on frameworks such as Tensoflow, MXNet

Who this course is for:

Anyone with data science and AWS background preparing to take the AWS Certified Machine Learning Specialty exam.

Demissew Kessela

3.5 Rating
2 Reviews

Demissew Kessela is AWS Certified Machine Learning Specialist, AWS Solution Architect - Associate Certified and AWS Developer- Associate Certified. Alazar has been in the IT industry for over 5 years. He completed the Data Scientist Nanodegree Certification from Udacity. Alazar has worked on building streaming solutions on AWS, creating data pipelines using Spark, and building machine learning models.

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By Rochelle Barber

Many of the questions have errors in them. I got another one of the Udemy ML practice exams and that one did too The other exam has cat/dog questions that don't tell you what you're looking... rightly named cats or rightly named dogs. This one has 25% not 20% in the text for false positives so none of the answers are right.

It makes me have little confidence I'm getting a fair assessment of how well I'd do [and if the answers actually are truly correct]. I gave this 2 stars because your explanations prove my point and are actually solid, but it looks like someone modified the questions and not the answers. I can back pedal into the correct answers using the explanations sometimes.

By Martha Saleh