Overview

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. 

Audience

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

Prerequisites

Objective

• 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 Outline

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