IBM Watson for Artificial Intelligence & Cognitive Computing
IBM Watson for Artificial Intelligence & Cognitive Computing, available at $54.99, has an average rating of 3.5, with 77 lectures, 2 quizzes, based on 82 reviews, and has 643 subscribers.
You will learn about 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 This course is ideal for individuals who are 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. It is particularly useful 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.
Enroll now: IBM Watson for Artificial Intelligence & Cognitive Computing
Summary
Title: IBM Watson for Artificial Intelligence & Cognitive Computing
Price: $54.99
Average Rating: 3.5
Number of Lectures: 77
Number of Quizzes: 2
Number of Published Lectures: 77
Number of Published Quizzes: 2
Number of Curriculum Items: 79
Number of Published Curriculum Objects: 79
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will 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
Who Should Attend
- 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.
Target Audiences
- 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.
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:
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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.
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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.
Course Curriculum
Chapter 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
Chapter 2: Learning to Build Apps Using Watson AI
Lecture 1: The Course Overview
Lecture 2: Fundamentals
Lecture 3: Fundamentals – Part 2
Lecture 4: Introducing IBM Watson
Lecture 5: The IBM Watson Platform
Lecture 6: Adapting Watson
Lecture 7: Examples
Lecture 8: Watson API’s
Lecture 9: IBM Cloud
Lecture 10: Development Environment
Lecture 11: Hello Watson
Lecture 12: Hello Watson (Continued)
Lecture 13: IBM Node-RED
Lecture 14: IBM Node-RED (Continued)
Lecture 15: Python and Node.js SDK
Lecture 16: Python and Node.js SDK (Continued)
Lecture 17: Watson Assistant in Depth
Lecture 18: Watson Assistant in Depth (continued)
Lecture 19: Define Intents and Entities Workspace
Lecture 20: Define Intents
Lecture 21: Define Entities
Lecture 22: Build Dialog Overview
Lecture 23: Build Dialog Conditions and Responses
Lecture 24: Build Dialog Context, Slots and Folders
Lecture 25: Build Dialog Advanced Responses and APIs
Lecture 26: Evaluate and Deploy the Model
Lecture 27: Build: IT Support Assistant
Lecture 28: Improving Models Continuously
Lecture 29: Applying the Capability in Various Use Cases
Lecture 30: Watson NLU in Depth
Lecture 31: Watson NLU in Depth – Part 2
Lecture 32: Understand Entities and Relations
Lecture 33: Concepts, Categories, and Keywords
Lecture 34: Sentiment and Document Emotion
Lecture 35: Build: Analyzing Customer Complaints
Lecture 36: Build: Analyzing Customer Complaints – Part 2
Lecture 37: Applying NLU in Various Use Cases
Lecture 38: Watson Speech to Text in Depth
Lecture 39: Watson Speech to Text in Depth (Continued)
Lecture 40: Key Concepts
Lecture 41: Key Concepts (Continued)
Lecture 42: Testing Watson Speech To Text Model
Lecture 43: Improving STT Model Using Custom Words
Lecture 44: Improving STT Model Using Custom Words(continued)
Lecture 45: Build Your Own Custom Acoustic Model
Lecture 46: Build: Company Earnings Call Transcript Application
Lecture 47: Applying the Capability in Various Use Cases
Lecture 48: Watson Visual Recognition in Depth
Lecture 49: Watson Visual Recognition in Depth (Continued)
Lecture 50: Classifying Images
Lecture 51: Classifying Images (Continued)
Lecture 52: Detecting Food and Faces
Lecture 53: Extracting Text from Images
Lecture 54: Introduction to Watson Studio
Lecture 55: Overall Approach to Training
Lecture 56: Training the Classifier
Lecture 57: Invoke Model, Best Practices and Applicable Cases
Lecture 58: Apply the Capability in Various Use Cases and Convert to Core ML
Instructors
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Packt Publishing
Tech Knowledge in Motion
Rating Distribution
- 1 stars: 3 votes
- 2 stars: 6 votes
- 3 stars: 16 votes
- 4 stars: 33 votes
- 5 stars: 24 votes
Frequently Asked Questions
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