Certified Artificial Intelligence Practitioner (CAIP)

At the end of this Certified Artificial Intelligence Practitioner (CAIP) training course, you will develop AI solutions for business problems. You will:

• 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.

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 Certified Artificial Intelligence Practitioner (CAIP) training course is also designed to assist participants in preparing for the CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210) certification.

Personal Impact

By attending this Certified Artificial Intelligence Practitioner Training Course, participants will be able to:

• Boosts professional value through validated AI proficiency, enhancing career prospects and advancement opportunities.
• Expand their technical abilities in AI and machine learning, opening up new job opportunities and enabling the undertaking of complex projects.
• Enhance problem-solving and critical thinking skills by teaching individuals to address complex challenges with AI-driven solutions effectively.
• Make valuable networking opportunities with AI professionals, facilitating collaboration, mentorship, and potential job offers.