IBM Watson for Artificial Intelligence & Cognitive Computing

This video provides an overview of the entire course.

What does it mean to have a cognitive system and what are the main features?

• Review general concepts behind the term cognition

• Explore the main characteristics of a cognitive system

• Understand why it matters to build cognitive systems

What are the differences between cognitive systems and traditional development?

• Understand the different computing paradigms for solving problems

• Change the focus from rules definition and development to data analysis and training

• Explore the conceptual components that make a cognitive system

A quick summary of Watson as an implementation of a cognitive system, from its history to its current offering.

• Go through a brief history of Watson and the Jeopardy challenge

• Review the evolution of Watson after it won the Jeopardy contest

• Review the current status of Watson and the way of using it

Have a review of the first set of APIs available in IBM Cloud.

• Explore some high level categorization of API functionality

• Look at the summary of natural language and empathy APIs

• Review some demos of the APIs

Complete the review of the other Watson APIs.

• Explore signal processing APIs

• Review data analysis services

• Explore some demos of the remainder APIs

How do you train Watson to learn how to interact with your users?

• Understand the natural language processing capability and the difference with traditional approaches

• Explore the high level structure of a conversation

• Define an intent as a conversation building block

What are the others Building Blocks of Watson Assistant?

• Complement the intent detection with the entities parsing

• Model the script of the dialog flow

• Put all the pieces together in a sample

What additional APIs can I use in my chatbots solutions?

• Explore the document processing capabilities offered in Watson

• Compare cognitive search and analytics

• Look at a practical use of Discovery for enhancing chatbot behavior

Train your own domain inside a Watson Solution.

• Define the set of intents and entities

• Create your workspace and teach Watson your utterances examples

• Model the dialog flow and try the solution

What does it mean to understand text? How can you get from an open text to useful information that a program can process?

• Understand metadata and its role in natural language processing

• Explore the kind of metadata that Watson can extract from your data

• Use a sample app for looking at the results with feature extraction with NLU

How to include the NLP capabilities to enrich the analysis you can do over your documents?

• Review the three stages for processing a set of documents

• Understand the structure of the Discovery Service and the functionalities it offers

• Configure your own environment for uploading documents and doing the NLP processing

How do I use the extracted metadata for getting useful information?

• Understand the two types of queries you can use

• Explore the Discovery Query Language for querying metadata

• Use the GUI for building your own queries and finding insights

How can you better understand your users? What additional information can Watson provide you about your customers?

• Introduce the Big 5 model of personality

• Show how Watson predicts your user's personality

• Explore the additional information that Watson can get from your users

How can you build an integrated solution using personality insights results?

• Explore scenario: Enhancing a chatbot

• Explore scenario: Leveraging human resources process and making more appealing offers

• Explore a sample call to the service from a Node.js program

How Watson provides capabilities for computer vision.

• Understand the kind of information that Watson extracts from images

• Explore the concepts of model and classes

• Review the high-level features that you can use in your solutions

What are the models and features that Watson can extract out-of-the-box?

• Explore the tags returned by the standard general model

• Look at the capabilities of face detection

• Review the beta models and create your own service and classify images

How can you extend the functionality of Watson, by training on your own images?

• Design the classification taxonomy

• Understand the training method and the concepts of positive and negative examples

• Review some useful tips for building classifiers and train your own service

This video will give you an overview of the course.

In this video, we will look at structured and unstructured data, features, and machine learning.

• Understand structured and unstructured data

• Understand machine learning

In this video, we will learn about features, supervised, and unsupervised learning, and deep learning.

• Understand features and supervised and unsupervised learning

• Understand deep learning

In this video, we will learn what cognitive computing is, the key characteristics of a cognitive system and what IBM Watson is.

• Learn the key characteristics of a cognitive system

• Understand the building blocks of cognitive systems

• Understand what IBM Watson is

In this video, we will learn AI APIs on the Watson platform and see how Watson learns.

• Understand how IBM Watson APIs are available

• Learn the capabilities of Watson’s AI

• Understand how Watson learns

In this video, we will learn how cognitive systems are trained, and cover domain adaptation of Watson APIs.

• Understand domain adaptation in Watson

• Understand how cognitive systems are trained

In this video, we will learn examples of cognitive systems.

• Understand how IBM Watson works

In this video, we will test drive the Watson API, API documentation.

• List the Watson APIs

• Navigate through the API documentation

• Test the APIs using API Explorer

In this video, we will signup for using Watson API’s on IBM Cloud.

• Sign up into IBM Cloud

• Login to IBM Cloud Console

In this video, we will be setting up the environment for development with IBM Watson API’s.

• Understand Cloud Foundry

• Install and setup the environment

In this video, we will setup and test Watson discovery news API using POSTMAN.

• Create Watson NLU service

In this video, we will continue to setup and test Watson discovery news API using POSTMAN.

• Test Watson Discovery News and Watson NLU

In this video, we will setup & install IBM Node-RED including Watson Nodes.

• Install IBM Node-RED

In this video, we will continue to setup & install IBM Node-RED including Watson Nodes.

• Build a simple Node-RED flow

• Invoke Watson NLU Service

In this video, we will setup & Install Node.js and Python SDK based environment.

• Install Node.js and Python client SDK’s

In this video, we will continue to setup & Install Node.js and Python SDK based environment.

• Build a Python notebook

In this video, we will learn about what the API does, when to use, capabilities and supported languages.

• Understand conversational systems

In this video, we will learn about what the API does, when to use, capabilities and supported languages.

• Learn what is Watson Assistance

In this video, we will learn about the workspace of Intents and Entities.

• Understand the conversational system HL Architecture

• Learn the workspaces

In this video, we will learn about the Intents.

• Learn about Intents

In this video, we will learn about the Entities.

• Learn about Entities

In this video, we will learn have an overview to Build Dialog.

• Have an overview of Dialog

In this video, we will understand to conditions to Build Dialog.

• Look at Dialog nodes and invocation

• Understand the conditions and responses

In this video, we will understand the context, slots and folders fro Build Dialog.

• Understand the dialog design

In this video, we will look at the responses and APIs to Build Dialog.

• Make the responses using JSON editor

• Programmatic calls to API

In this video, we will evaluate and deploy the model.

• Evaluate Watson assistant intent using Python Notebook

In this video, we will learn the various application use cases.

• Understand the IT support assistant

In this video, we will understand the user interactions and analytics to improve the models.

• Understand to improve component

In this video, we will apply the capability in various use cases.

• Apply the capability in various use cases

In this video, we will learn what the API does, when to use it, API operations, and supported languages.

• Understand what Watson NLU is

• Learn what the API does

In this video, we’ll continue learning what the API does, when to use it, API operations, and supported languages.

• Understand when to use Watson NLU

• Understand the use cases solved by NLU

In this video, we will extract and recognize semantic entities and relations from text input.

• Understand entities and relations

• Get a hands-on demo of entities and relations in Postman

• Understand where to use entities and relations

In this video, we will derive semantic information and features from text input.

• Understand concepts, categories, and keywords

• Get a hands-on demo of Postman for keywords

In this video, we will extract the overall sentiment and emotion from text inputs.

• Understand sentiments and emotions

• Get a hands-on demo of Postman for sentiments and emotions

In this video, we will learn to build a pipeline in Python to ingest, enrich, and analyze customer complaints.

• Learn unstructured and structured data

• Analyze customer reviews using IBM Watson NLU

We will continue building a pipeline in Python to ingest, enrich, andanalyze customer complaints.

• Understand Jupyter IPython notebook

In this video, we will look at some example use cases in action and recommended practices.

• Look at some examples of Watson NLU API

• Demo of email accelerator and cognitive social CRM

In this video, we will understand what the API does, when to use, API Operations, pre-trained models and their supported audio formats.

• Understand Speech Recognition basics

• Understand the API operations

In this video, we will continue to understand what the API does, when to use, API Operations, pre-trained models and their supported audio formats.

• Look at supported Audio formats and applicable use cases

In this video, we will learn about Available models, audio formats, making recognition requests, word alternatives, keyword spotting, custom corpus, acoustic model.

• Understand the available models and ways to make recognition requests

In this video, we will continue learning about Available models, audio formats, making recognition requests, word alternatives, keyword spotting, custom corpus, acoustic model.

• Learn Model customization, custom corpus and words, and acoustic model

In this video, we will test the out of the box Watson Speech to Text models (narrowband and broadband).

• Test STT models

• Understand Input and Output features

In this video, we will train and improve Watson STT accuracy using language model customization service.

• Understand to customize interface

In this video, we will continue to train and improve Watson STT accuracy using language model customization service.

• Train the model on the custom words

In this video, we will train and improve Watson STT accuracy using acoustic model customization service.

• Learn acoustic model customization

In this video, we will build Company Earnings Call Analyzer Application.

• Build an application in Node-RED

• Analyze company earnings call audio

In this video, we will apply Watson STT in various use cases and also recommend best practices.

• Learn various enterprise Use Cases for STT

In this video, we will understand what the API does, when to use, API Operations, pre-trained models and their supported audio formats.

• Understand what the API does

• Learn API operations

In this video, we will continue to understand what the API does, when to use, API Operations, pre-trained models and their supported audio formats.

• Learn to use and pre-train model

• Understand use cases and supported image formats

In this video, we will learn to classify, categorize and extract information from raw images.

• Understand image classification

• Learn API Operations

In this video, we will continue to learn to classify, categorize and extract information from raw images.

• Learn where to use them

In this video, we will identify food items from images and locate faces, assess gender and age from an image.

• Learn to use food model

• Learn to use face model

In this video, we will learn to extract short words and text from within images.

• Understand to extract words, text and location

In this video, we will get introduced to Watson Studio.

• Introduce Watson Studio

In this video, we will have an overall approach to training.

• Understand the general approach to training models

In this video, we will train the classifier.

• Train a custom Watson VR model

In this video, we will invoke model and understand the best practices.

• Invoke custom trained VR model

In this video, we will look at the examples of use cases in action and recommended practices.

• Look at various enterprise use cases for VR

• Deploy Watson VR model as core ML model