Training Course Overview
Artificial intelligence (AI) and machine learning (ML) have become essential parts of the toolset for many organizations. When used effectively, these tools provide actionable insights that drive critical decisions and enable organizations to create exciting, new, and innovative products and services. This Anderson training course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, all while following a methodical workflow for developing data-driven solutions.
To ensure your success in this course, specific prerequisites are mandatory to take. The program prerequisites can be accessed and viewed by visiting the following hyperlinked file: CAIP Prerequisites, and CertNexus Exam Blueprints.
Training Course Objectives
At the end of this Anderson training course, you will develop AI solutions for business problems.
- Solve a given business problem using AI and ML.
- Prepare data for use in machine learning.
- Train, evaluate, and tune a machine learning model.
- Build linear regression models.
- Build forecasting models.
- Build classification models using logistic regression and k -nearest neighbor.
- Build clustering models.
- Build classification and regression models using decision trees and random forests.
- Build classification and regression models using support-vector machines (SVMs).
- Build artificial neural networks for deep learning.
- Put machine learning models into operation using automated processes.
- Maintain machine learning pipelines and models while they are in production.
Designed For
The skills covered in this training course converge on four areas—software development, IT operations, applied math and statistics, and business analysis. Target participants for this course should be looking to build upon their knowledge of the data science process so that they can apply AI systems, particularly machine learning models, to business problems.
So, the target participant is likely a data science practitioner, software developer, or business analyst looking to expand their knowledge of machine learning algorithms and how they can help create intelligent decision-making products that bring value to the business.
A typical participant in this course should have several years of experience with computing technology, including some aptitude in computer programming.
This Anderson training course is also designed to assist participants in preparing for the CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification.