Machine Learning and Data Science with AWS

Description

In this course, you will learn :

• You could use AWS Glue and Quicksight to prepare your dataset.
• Using Athena, conduct data analysis.
• Quicksight could be used to create data visualisation charts.
• Natural Language Processing could be used to create and develop machine learning models.

Syllabus :

1. Glue and Athena

• Create a S3 bucket and add dataset
• Create a Crawler using AWS Glue
• Configuring output database name for crawler
• Customize Schema, find table details in Glue and Log groups in Cloud Watch
• Run SQL Queries on Athena and store output in S3 bucket
• Create and Save Custom Query in AWS Athena

 

2. Data Preparations with Quicksight

• Getting Started with Quicksight- installation
• Importing dataset and understanding group and values
• Creating Treemap and Customizing charts
• Data Preparation- Editing Dataset before creating Charts
• Create a Calculated Field using Functions- ceil and concat

 

3. Data Visualization with Quicksight

• Map Chart and Conditional Formatting
• Word Cloud
• Funnel Chart

 

4. NLP Natural Language Processing

• Build frontend for ML Application
• Build Backend for ML Application
• Add NLP task (translation)
• Demo: Translation ML app
• Creating Sentiment Analysis ML app
• Demo: Sentiment Analysis ML app
• POS tagging ML App

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