• Classroom
  • Online, Instructor-Led

Introduction to Artificial Intelligence (AI) & Machine Learning (AI & ML JumpStart) is a three-day, foundation-level, hands-on course that explores the fast-changing field of artificial intelligence (AI). programming, logic, search, machine learning, and natural language understanding. Students will learn current AI / ML methods, tools, and techniques, their application to computational problems, and their contribution to understanding intelligence.

Learning Objectives

This “skills-centric” course is about 50% hands-on lab and 50% lecture, with extensive practical exercises designed to reinforce fundamental skills, concepts and best practices taught throughout the course. Students will be led through a series of progressively advanced topics, where each topic consists of lecture, group discussion, comprehensive hands-on lab exercises, and lab review. Throughout the course students will learn about and explore popular machine learning algorithms, their applicability and limitations; practical application of these methods in a machine learning environment; and practical use cases and limitations of algorithms. Working in a hands-on learning environment led by our expert practitioner, attendees will explore: Getting Started with Python & Jupyter Statistics and Probability Refresher, and Python Practice Matplotlib and Advanced Probability Concepts Algorithm Overview Predictive Models Applied Machine Learning Recommender Systems Dealing with Data in the Real World Machine Learning on Big Data (with Apache Spark) Testing and Experimental Design GUIs and REST: Build a UI & REST API for your Models

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):