AWS Machine Learning Certification Exam | Complete Guide

500+ Slides | 200+ Questions | Become Certified in AWS ML| SageMaker|Data Engineering | Visualization | Model Deployment

Created by: Dr. Ryan Ahmed, Ph.D., MBA
Best-Selling Professor, 400K+ students, 250K+ YT Subs

Created by: SuperDataScience Team
Helping Data Scientists Succeed

Created by: Ligency Team
Helping Data Scientists Succeed

What Will I 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

Requirements

• Basic AI/ML/AWS knowledge

Target audience

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