Fundamentals of IBM Watson Explorer Deep Analytics Edition oneWEX (V12.0.x) Course Overview

To ensure a successful learning experience in the Fundamentals of IBM Watson Explorer Deep Analytics Edition oneWEX (V12.0.x) course, participants should meet the following minimum prerequisites:

• Basic understanding of data structures and formats (e.g., XML, JSON).
• Familiarity with the concepts of data ingestion, data processing, and data analysis.
• Basic knowledge of search technologies and principles.
• Some experience with web-based applications and internet navigation.
• An introductory level of understanding of machine learning concepts, such as classification and clustering, is helpful but not required.
• Prior exposure to IBM Watson technologies is advantageous but not necessary.
• Basic IT literacy, including understanding the use of operating systems (Windows or Linux), and the ability to perform simple command-line operations.
• Ability to understand RESTful APIs and their role in integration workflows.

These prerequisites are intended to provide a foundation for the course material and ensure that all participants can keep pace with the training. However, the course is designed to be accessible to those with a basic IT and data background, and additional learning support will be provided to help participants bridge any knowledge gaps.

Target Audience for Fundamentals of IBM Watson Explorer Deep Analytics Edition oneWEX (V12.0.x)

This course provides comprehensive training on IBM Watson Explorer Deep Analytics Edition oneWEX, tailored for IT professionals involved in data analysis and search solutions.

• Data Scientists
• Data Analysts
• Information Architects
• Solution Architects
• Software Developers
• Application Builders
• IT Managers
• System Administrators
• Database Administrators
• Search Engineers
• Content Management Professionals
• AI and Machine Learning Engineers
• Business Intelligence Professionals
• Technical Support Specialists

Learning Objectives - What you will Learn in this Fundamentals of IBM Watson Explorer Deep Analytics Edition oneWEX (V12.0.x)?

Introduction to Learning Outcomes and Concepts

The "Fundamentals of IBM Watson Explorer Deep Analytics Edition oneWEX (V12.0.x)" course equips learners with the skills to harness oneWEX for advanced data analysis and cognitive exploration.

Learning Objectives and Outcomes

• Understanding of oneWEX: Gain a comprehensive overview of IBM Watson Explorer Deep Analytics Edition oneWEX, including its architecture and application building capabilities.
• Navigational Proficiency: Learn to navigate the oneWEX Admin Console and Content Miner effectively for data management and exploration.
• Data Flow Comprehension: Understand the data flow within oneWEX from ingestion to search and analytics, ensuring efficient data processing.
• Data Acquisition Techniques: Acquire skills in data ingestion, working with datasets and crawlers, using importers, and understanding data conversion processes.
• Analysis with Content Miner: Learn to perform in-depth analysis using Content Miner and experience guided analysis views for better insights.
• Use of Annotators: Understand how to enrich data using different types of annotators, enhancing the value and accuracy of the analysis.
• Document Classification with Labeler: Master document classification techniques using Labeler, and comprehend the differences between classification and clustering.
• Enrichment with Ranker: Learn how to use Ranker for enrichment to prioritize and rank data effectively, based on relevance.
• Migration Skills: Acquire the ability to migrate annotators from Content Analytics Studio to oneWEX, including updating the UIMA pipeline configuration.
• Application Builder Mastery: Develop the expertise to set up and manage oneWEX data sources using Application Builder, and understand user roles and functionalities within the tool.