ARTIFICIAL INTELLIGENCE (AI) AND MACHINE LEARNING (ML)-Essentials

Course Overview

 This introduction-level hands-on course explores the field of artificial intelligence (AI), programming, logic, search, machine learning (ML), and natural language understanding. You’ll learn current AI and ML methods, tools, techniques, and their application to computational problems.  In this course, we’ll cut through the math and you’ll learn exactly how machine learning algorithms work. We’ll focus on the algorithms used to create machine learning models. Using clear explanations, simple Python code (no libraries), and step-by-step labs, you’ll discover how to load and prepare data, evaluate your models, and implement a suite of linear and nonlinear algorithms along with assembling algorithms from scratch. You’ll also learn about algorithm applicability along with their limitations and practical use cases.  This course presents a wide variety of related technologies, concepts, and skills in a fast-paced, hands-on format. This provides you with a solid foundation for understanding and getting a jumpstart  into working with artificial intelligence and machine learning.

Course Objectives:

Join an engaging hands-on learning environment, where you’ll explore:  Getting Started with Python and 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 and REST API for your Models

Target Audience

 Business Analysts, Data Analysts, Developers, Administrators, Architects, Managers, and others new to AI and ML who want to understand the core skills and how to put them into practice.