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.
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