We start off by building a simple Alexa Skill using the Alexa developer UI. This allows us to get a good understanding of what it required to build and deploy an Alexa skill before we go writing any code.

In this section we go over the code required by our Alexa skill to return random quotes. This code will be uploaded to AWS Lambda and eventually connected to our Alexa skill

With our completed Lambda code, we work on Uploading this to AWS Lambda before finally connecting it to our Alexa Skill

We have our code uploaded and connected to our Alexa Skill, now its time to test and make sure its all working as expected

Lets get started by creating our very first ASK SDK backed project using the ask-cli toolchain. In this video we'll setup your system with the ask-cli tool and NodeJS if you haven't already got it installed.

We'll then go through the base project structure and show you what each of the main folders do.

Before we get started writing too much code, let's have a look at our architecture to get a better understanding of what we're trying to achieve. In this video we'll confirm what we are going to build and formulate a plan of attack

For this course we require a database to store all our information about animals. We'll be using DynamoDB for this; however instead of creating and managing the database through the website, we'll be writing a small toolchain to accomplish what we need.

In this video we create the create.js module that will spin up a new DynamoDB instance for us via some NodeJS code

For this course we require a database to store all our information about animals. We'll be using DynamoDB for this; however instead of creating and managing the database through the website, we'll be writing a small toolchain to accomplish what we need.

In this video we create the insert.js module that will insert all our JSON entries into our DynamoDB instance for us via some NodeJS code

For this course we require a database to store all our information about animals. We'll be using DynamoDB for this; however instead of creating and managing the database through the website, we'll be writing a small toolchain to accomplish what we need.

In this video we create the test.js module that will confirm we can get access to entries within our DynamoDB instance via some NodeJS code

Keeping our code clean and management as we slowly build up functionality is important; In this video we work on breaking up the largely confusing code blocks from index.js into smaller, more manageable modules

Now that we have a Minimum viable product complete, lets confirm we're able to deploy as a functioning Alexa skill by making use of the ask-cli deploy tool.

We need a way of getting a value associated with words said by users. In order to do this we'll use something called Slots. These Slots allow us to define wildcards and have Alexa pass in the outcomes of these wildcards to our code

Now that we have access to the value of the slot for an Animal Name, we can use it to perform a database action to retrieve information about an Animal; and have Alexa read it out loud to us.

Supporting a variety of languages and locations is really important if we want out skill to be successful in the global market. In this video I show you have to setup a convenient system to manage various translations within one resource file

Session Attributes allow us to store and reference values within the local state of our Alexa skills session. In this video we look at defining the model, and add some dialogue and prompts that will allow Alexa to elicit a value from us by asking a variety of questions.

With out model setup for eliciting us for values, we're ready to add the code that will enable Alexa to ask for our Users name and store it in local state.

Being able to instantiate and safely close down certain things before and after full-filling an intent is an important feature to Alexa skills; especially when we're working with session data.

In this video we setup Request and Response interceptors to initialise variables before they are accessed from our various intents.

Now that we have our attributes stored locally in session state, we can move onto ensure that our Attributes are saved and loaded to a DynamoDB persistence layer using a helpful library within ask-sdk

Ensuring that Alexa responds in as life-like ways as possible is sometimes difficult; but there are a couple really small things we can do to make her seem more personal. In this video we cover adding a utility to make Alexa appear more personal by making her timezone aware and response based on whether its Morning, Evening or Night-time.

Now that we have most of our core logic complete, let's go ahead and clean up some of the random strings within our Intents and move them into our Localisation resource section.

In this video we add some more personality to Alexa, but allowing her to play audio clips based on the Type of animal we query for.

We do this by pulling audio clips from S3 using the SSML language for Alexa Skills.