Cursos de IBM Watson

The overall intention of watsonx Assistant is to enable the user to interact from anywhere and to engage with any company data. This course enables the student to create watsonx Assistant instances that resolve multiple user tasks through the access of channels like webchat, telephone and third-party customer service applications like GENESYS and custom extensions that hold proprietary real time data, as well as, provide generative AI interactions. A persona and its personality are important characteristics of the users' interaction. Emotions, tone, and language can affect a user's experience and thus the company's image. Actions contain steps which begin with conditions that evaluate user, session, and extension variables and decide whether specific steps should run or not run.  Primary actions can orchestrate a complex system of tasks by sending users to subactions and their requests to different custom extensions.  Journeys provide the user with assistance to complete complex tasks already available in a web site using the techniques of Show, Tell, and Do. The user can switch between chat and web site functionality and back to chat using a number of different tools like images, text, video, and interactive iFrames. watsonx Assistant includes the preview function which provides a number of debugging tools which allow the practitioner to find the value of variables, steps, confidence scores, and extension properties.

In this comprehensive course, you will learn how to harness the power of Watson Discovery API to build a robust document retrieval system. From regular expressions to advanced techniques like Discovery Query Language, relevancy training, and result modification, this course will equip you with the skills needed to create highly accurate and efficient search applications. The course begins by introducing you to the Watson Discovery API and its capabilities. You will gain hands-on experience by developing a document retrieval project from scratch.  Moving forward, the course delves into the features of Watson Discovery user interface. You will explore text classification techniques, leveraging the power of machine learning to categorize and organize your documents effectively. The course also covers relevancy training, a powerful technique that fine-tunes the search results based on user feedback. You will learn how to train the system to improve the ranking of search results and provide a more personalized experience to users. Additionally, you will discover how to expand the meaning of searches, enabling the system to comprehend user intent and deliver accurate results even when the query may not match the exact keywords. Furthermore, you will explore result modification techniques, allowing you to customize and refine search results to better align with specific requirements. Finally, you will learn how to extract the retrieved data and export it to a CSV file for further analysis or integration with other systems. By the end of this course, you will have the expertise to build sophisticated document retrieval systems using Watson Discovery API. Whether you are a developer, data scientist, or a technology enthusiast, this course will empower you to leverage the full potential of Watson Discovery API and revolutionize information retrieval in your projects.

In this course, the learner is guided through a realistic data science project. The project focuses on extracting business insights from large amounts of unstructured voice data, by using IBM Watson APIs. Starting from voice recorded customer reviews, the data are transcribed by using Watson Speech to Text and then are analyzed for emotion and keywords by using Watson Discovery. The structured results are stored in a tabular form and used to extract business insights in Watson Studio. The course focuses on hands-on coding exercises that provide an opportunity to work with Watson Studio, Watson Discovery, and Watson Speech to Text. The exercises guide the learner on importing data and manipulating in a Watson Studio project, activate instances of installed services, and authenticate API connections by using Jupyter Notebooks. The exercises also introduce how to configure Watson Speech to Text and create custom language models, work with Watson Discovery, and introduce enrichments. Also, every exercise demonstrates suitable data manipulation that results in saved structured data. The three hands-on exercises are included in this course, each focusing on a Jupyter Notebook and correspond to the three modules of the course. The necessary data, notebooks, and services are all available in the corresponding lab environment.

The focus of this course is on the tools and services available in IBM Watson Studio that can be used to build, test, and deploy machine learning models on Cloud Pak for Data V4.8. It takes the data scientist or business analyst on a journey from the creation of several machine learning models to its deployment and testing. Various tools and services, as well as programming and graphical user interfaces, are used in the process. The course ends with the sharing of assets on GitHub, and a brief discussion on governance and stewardship.

The overall intention of watsonx Assistant is to enable the user to interact from anywhere and to engage with any company data. This course enables the student to create watsonx Assistant instances that resolve multiple user tasks through the access of channels like webchat, telephone and third-party customer service applications like GENESYS and custom extensions that hold proprietary real time data, as well as, provide generative AI interactions. A persona and its personality are important chrematistics of the users' interaction. Emotions, tone, language can call impact a user's experience and thus the company's image. Actions contain steps which begin with conditions that evaluate user, session, and extension variables and decide whether specific steps should run or not run.  Primary actions can orchestrate a complex system of tasks by sending users to subactions and their requests to different custom extensions.  Journeys provide the user with assistance to complete complex tasks already available in a web site using the techniques of Show, Tell, and Do. The user can switch between chat and web site functionality and back to chat using a number of different tools like images, text, video, and interactive iFrames. watsonx Assistant includes the preview function which provides a number of debugging tools which allow the practitioner to find the value of variables, steps, confidence scores, and extension properties.

In this 6 hour web-based training (WBT), you will learn how Watson Discovery lets business analysts and developers rapidly build cognitive, cloud-based exploration applications that unlock actionable insights hidden in unstructured data — including your own proprietary data, as well as public and third-party data.

In this course you will connect a device to IBM Watson IoT Platform and explore how this device can be managed. The device management feature enhances the Watson Internet of Things Platform service with new capabilities for managing devices. This course provides a sample agent implementation that demonstrates the following device management capabilities on a Raspberry Pi.

This course will teach you how to connect an OEM device to the Watson IoT Platform.