Skip to main Content

watsonx.ai: Introduction to Data Science and Generative AI

  • Course Code W7L187G
  • Duration 1 day

Course Delivery

Virtual Learning Price

eur850.00

excl. VAT

Request Group Training Add to Cart

Course Delivery

This course is available in the following formats:

  • Public Classroom

    Traditional Classroom Learning

  • Virtual Learning

    Learning that is virtual

Request this course in a different delivery format.

Course Overview

Top

In this course, students will learn to use scientific methods, processes, and algorithms to identify patterns, trends, and insights from data – with the goal of enabling better decision-making.  

Students will use watsonx.ai to synthesize skills from statistics, computer science, and management information systems to analyze and interpret complex datasets.

This course includes a practical component with hands-on exercises focused on collecting, preparing, mining, and visualizing data and then building a machine learning and foundation model with methods on how to deploy them. 

Virtual Learning

This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.

Course Schedule

Top

Target Audience

Top

This course is intended for Data Scientists, AI Specialists, watsonx.ai Specialists, Solution Architects, or anyone interested in data science and gen AI.

Course Objectives

Top

After this course participants should be able to:

  • Understand data concepts and tools
  • Learn how to transform, mine, and visualize data
  • Build machine learning, large language, and foundation models
  • Deploy and measure model performance

Course Content

Top

Section 1 – Introduction to data science

Section 2 – Tools for data analysis

Section 3 – Data analysis and visualization

Section 4 – Machine learning and methodology

Section 5 – MLOps, deployment, and observability

Section 6 – Data Science and Generative AI

Course Prerequisites

Top
General understanding of AI concepts

Further Information

Top
  • Official course book provided to participants.
Cookie Control toggle icon