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IBM Watson for Artificial Intelligence & Cognitive Computing
Rating: 4.1 out of 5(91 ratings)
733 students

IBM Watson for Artificial Intelligence & Cognitive Computing

Build smart cognitive computing, AI, and ML applications and systems with IBM Watson
Created byPackt Publishing
Last updated 7/2020
English

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

Explore related topics

Course content

2 sections • 77 lectures • 15h 6m total length

  • The Course Overview4:28

    This video provides an overview of the entire course.

  • Review of Cognitive Concepts11:44

    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

  • Structure of a Cognitive System11:37

    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

  • Watson – Your Next AI Platform6:50

    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

  • Recap of REST Paradigm8:38

    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

  • Review of Watson APIs – Part I13:38

    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 II8:31

    Complete the review of the other Watson APIs.

    • Explore signal processing APIs

    • Review data analysis services

    • Explore some demos of the remainder APIs

  • Watson Assistant Training10:45

    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 – II9:49

    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

  • Introduction to Discovery Service9:04

    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

  • Build Your Own Chatbot20:10

    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

  • Natural Language Understanding8:51

    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

  • Enrichments in Discovery Service12:08

    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

  • Find Insights from Unstructured Data8:43

    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

  • Personality Insights11:12

    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

  • Sample Use Cases14:10

    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

  • Understanding Visual Recognition6:48

    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

  • Standard Model11:04

    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

  • Creating Custom Models8:45

    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

  • Test Your Knowledge

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.

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