Lesson One: Introduction to Amazon Web Services

The basics of working on AWS using S3

Importing and exporting data.

Using the AWS console and identifying the services available for Machine Learning.

Create a S3 bucket and import text data into it.

Lesson Two: Summarize Text Documents using NLP

Use Amazon Comprehend to detect the language which a document is written in.

Extract information such as entities (persons or places), key phrases (noun phrases indicative of the content), and emotional sentiment from a set of documents.

Sample project: Set up a Lambda function to process and analyze the imported text using Comprehend.

Lesson Three: Perform Topic Modelling and Theme Extraction

Understand what business use cases to apply the machine learning algorithm (Latent Dirichlet Allocation (LDA)) that is used for topic modeling.

Extract and analyze common themes through topic modelling with Amazon Comprehend.

Sample project: Perform topic modeling on a set of documents and analyze the results.

Lesson Four: Creating Chatbot with Natural Language

Explore the basics of chatbots and chatbot design.

Set up with the Amazon Lex service and create a sample chatbot to order flowers.

Create a custom chatbot which will look up market prices for a given stock

Lesson Five: Using Speech with the Chatbot

Set up Amazon Connect as a personal call center.

Integrate the chatbot you built in the previous lesson with Amazon Connect.

Interact with the chatbot using voice and speech by calling it.

Lesson Six: Analyzing Images with Computer Vision

Use Rekognition service for image analysis using computer vision.

Detect objects and scenes in images.

Detect the need for content moderation in images.

Analyze faces and recognize celebrities in images.

Compare faces in different images to see how closely they match.

Extract text from images