Digital Badge Program Watson

This credential earner has completed instructor-led learning for administering Watson Knowledge Catalog at an advanced level. The earner can manage user roles, permissions, data connections, data discovery, metadata, catalogs, assets, and governance artifacts, and work with relevant APIs.

Course Objectives

Badge Criteria and Activities

Attendance and successful completion of 6XL640G Advanced Administration for IBM Watson Knowledge Catalog (V4.5) instructor-led training course

This credential earner has completed instructor-led learning for intelligent document processing at a deeper level. They can create regular expressions, import rule-based models, customize query results, conduct web crawling, and teach the domain language to Watson Discovery to enhance relevance and accuracy.

Course Objectives

Badge Criteria and Activities

Attendance and successful completion of W7L152G Advanced Intelligent Document Processing with IBM Watson Discovery instructor-led training course

The successful badge earner can outline basic NLP tasks and language models, define rule-based models and machine learning models in NLP, and define information retrieval and information extraction. The earner can apply smart document understanding, modify display of query results, and show how to improve the accuracy of query results.

Course Objectives

Badge Criteria and Activities

Attendance and successful completion of W7L148G Basics of Intelligent Document Processing with IBM Watson Discovery instructor-led training course

This credential earner has completed instructor-led learning for Creating Voice Interfaces with Watson Speech to Text and Text to Speech. The earner can explain the underlying science behind the technology of Watson Speech to Text and Text to Speech as developed by IBM, leverage the API methods for calling speech services, customize, and deploy speech prototypes to suit a unique domain language, and integrate voice capabilities to an existing IBM Watson Assistant agent.

Course Objectives

Badge Criteria and Activities

Attendance and successful completion of W7L162G Creating Voice Interfaces with Watson Speech to Text and Text to Speech instructor-led training course

The successful badge earner can use the tools and services from IBM Watson Studio to build, deploy, and test machine learning models. The earner can access the relevant data sets, build machine learning models by using various editors and graphical user interfaces, deploy the models, and test them for correct operation. The earner can also be able to share the assets with colleagues.

Course Objectives

Badge Criteria and Activities

Attendance and successful completion of W7L149G Creating, Testing, and Deploying Machine Learning Models with IBM Watson Studio instructor-led training course

This credential earner has completed instructor-led learning for Watson Assistant, focusing on actions that are built with steps. They can distinguish among agents, explain the capabilities of Watson Assistant, and summarize the basics of planning and building an intelligent virtual agent.

Course Objectives

Badge Criteria and Activities

Attendance and successful completion of W7L151G Introduction to intelligent virtual agents with IBM Watson Assistant instructor-led training course

The successful badge earner can distinguish between supervised and unsupervised machine learning, define deep learning and reinforcement learning, and demonstrate the basic functions of Watson Studio for machine learning. The earner can list the model development steps, develop a Random Forest model, and evaluate the results.

Course Objectives

Badge Criteria and Activities

Attendance and successful completion of W7L160G Learn the Basics of Machine Learning with IBM Watson Studio instructor-led training course

This badge holder has demonstrated understanding of the core features and functionality of Watson Explorer Analytical Components. Recipient is able to use the content analytics, annotator, and content mining functionality. This primary functionality is found in an Analytics collections crawling, parsing, indexing, annotating, and searching components.

Course Objectives

Badge Criteria and Activities

Badge earners have successfully achieved class objectives demonstrated by progress in lab exercises, attendance, participation in question & answer sessions, and/or assessments associated with: