Alexa Skills in 24 Hours

Learn the first steps to build an Alexa skill, exploring the interaction model, hosting options, intents and slots, and testing in the Alexa developer console.

Explore Alexa intents, including custom and built-in intents, and how utterances trigger them via the front-end interaction model and invocation name.

Build and refine the Alexa interaction model 1.0 by configuring intents, utterances, slot types, and addressing slot conflicts; use the JSON editor and learn about endpoints, interfaces, and permissions.

Explore updates to the alexa developer console, including multimodal responses that combine visuals with audio. Try alexa conversations in beta under interfaces, available in the English US region.

Learn to use slots in Alexa skills, compare built-in and custom slots, add two intents to a first skill, and finalize the interaction model for robust utterances.

The lecture presents a feature update in the developer console: multi-value option for intent slots now defaults to no and can be set to yes to accept multiple color values.

Explore the backend code for Alexa skills with Node.js and the ASK-SDK, covering request and intent handlers, launch handling, and the response builder.

Examine the complete backend code of an Alexa skill, covering the ask-sdk-core setup, launch and name and ice cream intents, slot handling, and simulator testing with a custom skill builder.

Build the habitat skill front end, defining intents and slots while resolving utterance conflicts. Provision a backend with AWS Lambda and use the repeat intent.

Learn to host the back end with AWS Lambda, connect it to the interaction model, and manage global and local variables, including repeat intent and endpoint provisioning.

Learn to use session attributes via the attributesManager to persist data during an Alexa skill, and build arrays that pair animal names with image URLs.

Complete the image quiz back end for an Alexa skill by implementing yes and no intents, testing the skill, and using session attributes, arrays, and display features to track score.

Create and publish your first milestone Alexa skill, Make My Own, a pizza customization experience that lets users choose base, size, toppings, and cheese, and review analytics.

Builds the front end of the milestone project for the Alexa skill and introduces the evaluate model feature. Shows intents for name, size, base, cheese, veggies, and main toppings.

This video builds the back end of the milestone project for an Alexa skill, wiring launch, name, size, base, cheese, veggies, and main toppings handlers with session attributes.

Learn to distribute, certify, publish, and analyze your Alexa skill, including certification, live skill updates, and analytics to monitor performance.

Learn how SSML tags control Alexa speech, including audio, break, emphasis, prosody, and phoneme, and apply voice tags and Amazon Polly voices to enhance your skill’s audio experience.

Explore Amazon Polly, ssml, and voice tags to convert text into speech using multiple voices and locales, and implement them in Alexa skills for engaging, multi-voiced interactions.

Learn to enhance Alexa voices with SSML: apply excited or disappointed emotions, whisper effects, and domain styles like conversational, news, long-form, or music.

Learn to use emphasis, prosody, and phoneme tags in ssml to shape Alexa speech. Test and adjust rate, pitch, and volume, pauses, and pronunciation in the console.

Learn to add built-in and custom sounds to Alexa skills using audio tags, the SSML library, and Amazon S3, and build an animal sounds audio quiz.

Build the back-end for an audio quiz Alexa skill, manage score and question indices, and play animal sounds via audio tags from Amazon S3 with robust intent handling.

Build and test an Alexa skill that uses entity resolution to map user utterances to canonical slot values with synonyms, and handle the er_success_match and er_no_match statuses.

Expand the entity resolution skill by adding a superhero intent, a Marvel/DC slot with canonical values, and a handler that resolves slots to tailor responses based on the character.

Explore dialog management in Amazon Alexa, including slot filling, one-shot utterances, underfilled and overfilled utterances, to manage multi-turn conversations and deliver accurate intent responses.

Develop front-end dialog management by building a movie or song recommender with category and genre slots, slot filling, confirmation, synonyms, and auto delegation.

Complete the back-end dialog management for an Alexa skill by wiring ask-sdk-core, defining category and genre slots, and enabling multi-turn movie and song recommendations with slot resolution.

Conceptualize a back-end dialog management skill and build front end with lambda delegation, managing started, in progress, and completed states and slots education, university, and degree using addDelegateDirective and addElicitSlotDirective.

Implement back-end dialog management for the study intent by creating multiple handlers for slot combinations, using delegate, elicit, and confirm slot directives to capture university, degree, and education values.

Explore state management in Alexa and how memory through request, session, and persistent attributes keeps user data across interactions with DynamoDB and the ask-sdk-dynamodb-persistence-adapter.

Implement state management in an Alexa skill by upgrading a pizza order flow to store and recall past orders using the ASK-SDK library with AWS Lambda and DynamoDB.

Continue building the state management back-end for an Alexa skill with a serverless AWS Lambda setup and the ask-sdk, using persistent attributes to manage a pizza order flow.

Implement state management for an Alexa skill by adding the help, cancel, stop, session ended, intent reflector, and error handlers, wiring with lambda and DynamoDB for persistent user data.

Learn what Alexa blueprints are and create two skills using blueprint templates, including quizzes and flashcards, with no front-end or back-end setup.

Learn how Alexa skill personalization delivers tailored responses by recognizing users with personID and access tokens, while following rules, privacy policies, and using voice profiles.

Learn how to create and manage voice profiles in the Alexa app to enable skill personalization, sign in, train with phrases, and verify identity, including testing multiple profiles.

Build an Alexa skill that personalizes responses using voice profiles, recognizing the user to say 'Hi {name}' or 'Hi Stranger,' and configure locale, permissions, and testing for accurate personalization.

Explore the scope and prospects of Alexa's skill personalization, enabling personalized interactions across multiple linked user accounts through voice profiles, permissions, and user opt-out.

Build a horoscope Alexa skill using personalization to greet recognized users by name and prompt unrecognized users for their zodiac sign, leveraging personID without account linking.

Complete the front-end interaction model for the final milestone project, implementing two intents for recognized and generic users, personalization permissions, and a zodiac slot to deliver horoscopes.

Implement the final milestone back-end by wiring the ask-sdk-core. Define user IDs and a zodiac zod dictionary of horoscopes, and set up launch and horoscope intents to generate random phrases.

Explore the future of voice AI, from Siri and Alexa to in-car assistants, and learn to design, personalize, and publish Alexa skills with SSML.