IBM Watson for Artificial Intelligence & Cognitive Computing
4.3 (39 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
273 students enrolled

IBM Watson for Artificial Intelligence & Cognitive Computing

Build smart cognitive computing, AI, and ML applications and systems with IBM Watson
Bestseller
4.3 (39 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
273 students enrolled
Created by Packt Publishing
Last updated 3/2019
English
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Current price: $139.99 Original price: $199.99 Discount: 30% off
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This course includes
  • 15 hours on-demand video
  • 1 downloadable resource
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of Completion
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What you'll learn
  • Explore the capabilities of IBM Watson APIs to choose the best features for your task
  • Build a Customer Care chatbot using the Watson API
  • Extract metadata from text using Watson
  • Use Watson to get insights into the personality of your users
  • Learn how to use Watson for Computer Vision tasks and Visual Recognition to easily detect images
  • Learn the fundamentals of IBM Cloud and creating service instances
  • Learn Watson Assistant to build an IT Support Assistant conversational application
  • Apply Watson Natural Language Understanding to build an Customer Complaints Analyzer
  • Train Watson Speech to Text to build a financial earnings call analyzer & enricher application
  • Train Watson Visual Recognition to classify & detect rooms in a home
Requirements
  • No prior knowledge is required. However, having background in computer science or development will be beneficial but not mandatory.
Description

IBM Watson has evolved from being a game show winning question & answering computer system to a set of enterprise-grade artificial intelligence (AI) application program interfaces (API) available on IBM Cloud. These Watson APIs can ingest, understand & analyze all forms of data, allow for natural forms of interactions with people, learn, reason - all at a scale that allows for business processes and applications to be reimagined. If you’re someone who wants to build applications based on cognitive computing, AI, and ML, then this course is perfect for you.

This practical course on IBM Watson is designed to teach you how to build intelligent AI, ML, and Cognitive Computing based applications and systems. Beginning with an introduction to IBM Watson and exploring its components/features, you will learn how it can solve common pitfalls and be beneficial for your businesses. You will then learn the core Cognitive Computing techniques, concepts, and practices that Watson adopts and makes accessible to all. You will also get a detailed understanding of the Watson APIs such as training them and eventually building applications using them. Next, you will learn how to build chatbots, analyze text at a deeper level, transcribe audio, train a machine to classify & detect objects in pictures, extract entities, emotions, sentiment and relationships from news articles, and more. Finally, you will learn machine learning and deep learning to build intelligent AI systems.

Contents and Overview

This training program includes 2 complete courses, carefully chosen to give you the most comprehensive training possible.

The first course, IBM Watson for Beginners, will start by introducing Watson and what it can do for you. You will discover the kind of problems Watson can help with and discover the main components/features that enable it to work. Along the way you will learn the core Cognitive Computing techniques, concepts, and practices that Watson adopts and makes accessible to all. After that brief start, you'll delve into problem solving with Watson. Each section will deal with a kind of problem that Watson can solve, using 1 or more illustrative examples to show you how Watson can be used to solve your own business problems and build powerful intelligent systems.

The second course, Learning to Build Apps Using Watson AI, will give you a hands-on introduction to getting a detailed understanding of the Watson APIs, how to train them, and eventually build applications using them. You will go through the fundamentals behind each of the APIs, lots of code examples on how to use them on different types of unstructured data, spot the scenarios where you can apply them as well as real-life use case examples. You will learn about how to build conversational apps a.k.a., chatbots, analyze text at a deeper level, transcribe audio, training a machine to classify & detect objects in pictures, extract entities, emotions, sentiment and relationships from news articles, and more. You will also learn the different types of data, basics of AI including machine & deep learning, approach to building AI systems. You will learn about the basics of getting started with IBM Cloud, Watson and setting up an environment to build AI infused apps.

By the end of this course, you will have a complete understanding of the various Watson APIs and will have developed the skills to effectively use them in applications and business processes you may be working on.

Meet Your Expert(s):

We have the best work of the following esteemed author(s) to ensure that your learning journey is smooth:

  • Duvier Zuluaga Mora is a systems engineer who graduated from National University of Colombia, with a degree in Image Processing and Computer Graphics. He has more than 10 years of experience, including Application Integration Solutions, Service Oriented Architectures (SOA), Business Process Management Systems (BPM), and, in recent years, experience in Cognitive Solutions Architecture for Latin America. He was passionate about algorithms from a young age, and was part of the Colombian Team for International Olympiad in Informatics (IOI), first as a contestant and then as a National Team Trainer. He likes to work with technologies that have the potential to change the World.

  • Swami Chandrasekaran is a managing director at KPMG's AI Innovation & Enterprise Solutions. He leads the architecture, technology, creation of AI + emerging tech offerings as well as innovation efforts. He has led the creation of products and solutions that have solved a wide range of problems in areas such as tax and audit, industrial automation, aviation safety, contact centers, insurance claims, field service, multimedia enrichment, social care, digital marketing, M&A, and KYC. These solutions have leveraged automation, ML/DL, NLP, advanced analytics, as well as RPA, cloud and IoT capabilities. He is currently also driving explainable and trusted AI efforts. Previously, he spent 12 years at IBM, out of which 5 years were spent in the core Watson division. He led an organization that drove innovation and also creation + incubation of several solutions that leveraged Watson and IBM Cloud capabilities. He was also responsible for creating a library of Watson Accelerators that were used by several clients and field teams to accelerate their adoption of AI across various industries. He was appointed as one of their most elite IBM Distinguished Engineer.

Who this course is for:
  • This course is for developers, business analysts, and technical officers who wish to unleash the power of IBM Watson for Cognitive Computing, Artificial Intelligence, and Machine Learning.
Course content
Expand all 77 lectures 15:06:08
+ IBM Watson for Beginners
19 lectures 03:16:55

This video provides an overview of the entire course.

Preview 04:28

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

Review of Cognitive Concepts
11:44

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

Structure of a Cognitive System
11:37

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

Watson – Your Next AI Platform
06:50

How does Watson expose its capabilities? And how can you integrate them into your apps?

  • Review the rest-style integration approach

  • Explore the use of rest in the Watson APIs

  • Make your first call to a Watson API using cURL

Recap of REST Paradigm
08:38

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

Review of Watson APIs – Part I
13:38

Complete the review of the other Watson APIs.

  • Explore signal processing APIs

  • Review data analysis services

  • Explore some demos of the remainder APIs

Review of Watson APIs – Part II
08:31

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

Watson Assistant Training
10:45

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

Watson Assistant Training – II
09:49

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

Introduction to Discovery Service
09:04

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

Build Your Own Chatbot
20:10

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

Natural Language Understanding
08:51

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

Enrichments in Discovery Service
12:08

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

Find Insights from Unstructured Data
08:43

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

Personality Insights
11:12

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

Sample Use Cases
14:10

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

Understanding Visual Recognition
06:48

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

Standard Model
11:04

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

Creating Custom Models
08:45
Test Your Knowledge
5 questions
+ Learning to Build Apps Using Watson AI
58 lectures 11:49:13

This video will give you an overview of the course.

Preview 10:46

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

  • Understand structured and unstructured data

  • Understand machine learning

Fundamentals
10:01

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

Fundamentals – Part 2
07:24

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

Introducing IBM Watson
08:58

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

The IBM Watson Platform
14:53

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

Adapting Watson
06:49

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

  • Understand how IBM Watson works

Examples
03:47

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

Watson API’s
09:31

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

  • Sign up into IBM Cloud

  • Login to IBM Cloud Console

IBM Cloud
04:06

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

Development Environment
10:40

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

  • Create Watson NLU service

Hello Watson
08:45

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

  • Test Watson Discovery News and Watson NLU

Hello Watson (Continued)
04:10

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

  • Install IBM Node-RED

IBM Node-RED
08:02

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

IBM Node-RED (Continued)
07:54

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

  • Install Node.js and Python client SDK’s

Python and Node.js SDK
06:56

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

  • Build a Python notebook

Python and Node.js SDK (Continued)
08:25

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

  • Understand conversational systems

Watson Assistant in Depth
15:40

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

  • Learn what is Watson Assistance

Watson Assistant in Depth (continued)
14:05

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

  • Understand the conversational system HL Architecture

  • Learn the workspaces

Define Intents and Entities Workspace
20:20

In this video, we will learn about the Intents.

  • Learn about Intents

Define Intents
19:31

In this video, we will learn about the Entities.

  • Learn about Entities

Define Entities
24:35

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

  • Have an overview of Dialog

Build Dialog Overview
11:22

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

  • Look at Dialog nodes and invocation

  • Understand the conditions and responses

Build Dialog Conditions and Responses
10:34

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

  • Understand the dialog design

Build Dialog Context, Slots and Folders
26:19

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

  • Make the responses using JSON editor

  • Programmatic calls to API

Build Dialog Advanced Responses and APIs
12:52

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

  • Evaluate Watson assistant intent using Python Notebook

Evaluate and Deploy the Model
18:10

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

  • Understand the IT support assistant

Build: IT Support Assistant
24:06

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

  • Understand to improve component

Improving Models Continuously
08:26

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

  • Apply the capability in various use cases

Applying the Capability in Various Use Cases
05:29

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

Watson NLU in Depth
15:04

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

Watson NLU in Depth – Part 2
08:01

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

Understand Entities and Relations
14:53

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

Concepts, Categories, and Keywords
08:01

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

Sentiment and Document Emotion
06:26

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

Build: Analyzing Customer Complaints
07:41

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

  • Understand Jupyter IPython notebook

Build: Analyzing Customer Complaints – Part 2
16:45

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

Applying NLU in Various Use Cases
09:04

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

Watson Speech to Text in Depth
23:58

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

Watson Speech to Text in Depth (Continued)
18:33

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

Key Concepts
09:13

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

Key Concepts (Continued)
31:02

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

Testing Watson Speech To Text Model
14:39

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

  • Understand to customize interface

Improving STT Model Using Custom Words
18:16

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

Improving STT Model Using Custom Words(continued)
16:09

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

  • Learn acoustic model customization

Build Your Own Custom Acoustic Model
16:23

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

  • Build an application in Node-RED

  • Analyze company earnings call audio

Build: Company Earnings Call Transcript Application
13:26

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

  • Learn various enterprise Use Cases for STT

Applying the Capability in Various Use Cases
09:16

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

Watson Visual Recognition in Depth
19:01

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

Watson Visual Recognition in Depth (Continued)
14:24

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

  • Understand image classification

  • Learn API Operations

Classifying Images
10:21

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

  • Learn where to use them

Classifying Images (Continued)
07:40

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

Detecting Food and Faces
05:21

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

  • Understand to extract words, text and location

Extracting Text from Images
03:12

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

  • Introduce Watson Studio

Introduction to Watson Studio
11:40

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

  • Understand the general approach to training models

Overall Approach to Training
12:14

In this video, we will train the classifier.

  • Train a custom Watson VR model

Training the Classifier
08:44

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

  • Invoke custom trained VR model

Invoke Model, Best Practices and Applicable Cases
13:33

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

Apply the Capability in Various Use Cases and Convert to Core ML
03:37
Test Your Knowledge
5 questions