AWS Machine Learning Certification Exam | Complete Guide

After completing the course, you will learn…

  • Data Engineering
  • Data types, Python Libraries (pandas, Numpy, scikit Learn, MatplotLib, Seaborn), data distributions, timeseries, Feature Engineering (imputation, binning, encoding, and normalization)
  • AWS Services and Algorithms
  • Amazon SageMaker, Amazon S3 Storage services, AWS Glue
  • AWS Kinesis Services (Kinesis firehose, Kinesis video streams, Kinesis data streams, Kinesis analytics)
  • Redshift, Redshift Spectrum, DynamoDB, Athena, Amazon Quicksight, Elastic Map Reduce (EMR)
  • Rekognition, Lex, Polly, Comprehend, Translate, transcribe, BlazingText Word2Vec, DeepAR, Factorization Machines, Gradient Boosted Trees (XGBoost)
  • Image Classification (ResNet), IP Insights, K-Means Clustering, K-Nearest Neighbor (k-NN)
  • Latent Dirichlet Allocation (LDA), Linear Learner (Classification), Linear Learner (Regression)
  • Neural Topic Modelling (NTM), Object2Vec, Object Detection, Principal Component Analysis (PCA), Random Cut Forest, Semantic Segmentation, and Seqence2Sequence
  • Machine and Deep Learning Basics

Who this course is for:

  • Developers and data scientists wanting to get certified in AWS Machine Learning
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