*Best value for money, with practice test included*
*Updated for 2020’s latest AWS Machine Learning and SageMaker features*
*FEATURED INTERVIEW WITH AWS ML EXPERT* Topics discussed are:
-
Example of real project of AWS ML services
-
Some of the challenges faced on the project
-
What do companies look for when hiring for AWS specialists?
-
How can someone showcase their skills?
At the time of publication, this is the only complete AWS Machine Learning Specialty Certification course on udemy to include a full length practice test.
The course will follow the exam structure, and is divided into the following sections: Data Engineering, Exploratory Data Analysis, Modeling, Machine Learning Implementation and Operations.
Topics we will cover include:
-
Featured interview with AWS Expert that covers practical and job related aspects, important AWS tools etc.
-
Basics of Data Science, Artificial Neural Networks, and Deep Learning
-
Practical examples and use cases
-
S3
-
Glue and Glue ETL
-
Kinesis data streams, firehose, and video streams
-
Data Pipelines, AWS Batch, and Step Functions
-
scikit_learn, numpy, panda
-
Athena and Quicksight
-
Elastic MapReduce (EMR)
-
Apache Spark
-
Feature engineering
-
SageMaker Ground Truth, Built-in Algorithms
-
Deep Learning basics
-
How to evaluate machine learning models (confusion matrix)
-
Regularisation techniques
-
Comparison of various AWS services to help you understand when to use which service
-
High Level Machine Learning Services: Polly, Transcribe, Lex, Rekognition, and more
-
Security on AWS
