Ibm Watson For Artificial Intelligence & Cognitive Computing

Build smart cognitive computing, AI, and ML applications and systems with IBM Watson

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 OverviewThis 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.

Overview
Section 1: IBM Watson for Beginners

Lecture 1 The Course Overview

Lecture 2 Review of Cognitive Concepts

Lecture 3 Structure of a Cognitive System

Lecture 4 Watson – Your Next AI Platform

Lecture 5 Recap of REST Paradigm

Lecture 6 Review of Watson APIs – Part I

Lecture 7 Review of Watson APIs – Part II

Lecture 8 Watson Assistant Training

Lecture 9 Watson Assistant Training – II

Lecture 10 Introduction to Discovery Service

Lecture 11 Build Your Own Chatbot

Lecture 12 Natural Language Understanding

Lecture 13 Enrichments in Discovery Service

Lecture 14 Find Insights from Unstructured Data

Lecture 15 Personality Insights

Lecture 16 Sample Use Cases

Lecture 17 Understanding Visual Recognition

Lecture 18 Standard Model

Lecture 19 Creating Custom Models

Section 2: Learning to Build Apps Using Watson AI

Lecture 20 The Course Overview

Lecture 21 Fundamentals

Lecture 22 Fundamentals – Part 2

Lecture 23 Introducing IBM Watson

Lecture 24 The IBM Watson Platform

Lecture 25 Adapting Watson

Lecture 26 Examples

Lecture 27 Watson API’s

Lecture 28 IBM Cloud

Lecture 29 Development Environment

Lecture 30 Hello Watson

Lecture 31 Hello Watson (Continued)

Lecture 32 IBM Node-RED

Lecture 33 IBM Node-RED (Continued)

Lecture 34 Python and Node.js SDK

Lecture 35 Python and Node.js SDK (Continued)

Lecture 36 Watson Assistant in Depth

Lecture 37 Watson Assistant in Depth (continued)

Lecture 38 Define Intents and Entities Workspace

Lecture 39 Define Intents

Lecture 40 Define Entities

Lecture 41 Build Dialog Overview

Lecture 42 Build Dialog Conditions and Responses

Lecture 43 Build Dialog Context, Slots and Folders

Lecture 44 Build Dialog Advanced Responses and APIs

Lecture 45 Evaluate and Deploy the Model

Lecture 46 Build: IT Support Assistant

Lecture 47 Improving Models Continuously

Lecture 48 Applying the Capability in Various Use Cases

Lecture 49 Watson NLU in Depth

Lecture 50 Watson NLU in Depth – Part 2

Lecture 51 Understand Entities and Relations

Lecture 52 Concepts, Categories, and Keywords

Lecture 53 Sentiment and Document Emotion

Lecture 54 Build: Analyzing Customer Complaints

Lecture 55 Build: Analyzing Customer Complaints – Part 2

Lecture 56 Applying NLU in Various Use Cases

Lecture 57 Watson Speech to Text in Depth

Lecture 58 Watson Speech to Text in Depth (Continued)

Lecture 59 Key Concepts

Lecture 60 Key Concepts (Continued)

Lecture 61 Testing Watson Speech To Text Model

Lecture 62 Improving STT Model Using Custom Words

Lecture 63 Improving STT Model Using Custom Words(continued)

Lecture 64 Build Your Own Custom Acoustic Model

Lecture 65 Build: Company Earnings Call Transcript Application

Lecture 66 Applying the Capability in Various Use Cases

Lecture 67 Watson Visual Recognition in Depth

Lecture 68 Watson Visual Recognition in Depth (Continued)

Lecture 69 Classifying Images

Lecture 70 Classifying Images (Continued)

Lecture 71 Detecting Food and Faces

Lecture 72 Extracting Text from Images

Lecture 73 Introduction to Watson Studio

Lecture 74 Overall Approach to Training

Lecture 75 Training the Classifier

Lecture 76 Invoke Model, Best Practices and Applicable Cases

Lecture 77 Apply the Capability in Various Use Cases and Convert to Core ML

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.