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CertNexus

Certified Artificial Intelligence (AI) Practitioner (CAIP)

A five-day, vendor-neutral path to building AI and machine learning solutions.

5 daysIntermediate12 modulesCertified Artificial Intelligence (AI) Practitioner (CAIP)

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Overview

About this course

A five-day, vendor-neutral path to building AI and machine learning solutions. You will prepare data, train, evaluate and tune models, and build regression, forecasting, classification, clustering and neural network models, preparing for the CAIP certification.

What you'll learn

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.

Curriculum

12 modules

Identify AI and ML Solutions for Business Problems
Formulate a Machine Learning Problem
Select Approaches to Machine Learning

Collect Data
Transform Data
Engineer Features
Work with Unstructured Data

Train a Machine Learning Model
Evaluate and Tune a Machine Learning Model

Build Regression Models Using Linear Algebra
Build Regularized Linear Regression Models
Build Iterative Linear Regression Models

Build Univariate Time Series Models
Build Multivariate Time Series Models

Train Binary Classification Models Using Logistic Regression
Train Binary Classification Models Using k-Nearest Neighbor
Train Multi-Class Classification Models
Evaluate Classification Models
Tune Classification Models

Build k-Means Clustering Models
Build Hierarchical Clustering Models

Build Decision Tree Models
Build Random Forest Models

Build SVM Models for Classification
Build SVM Models for Regression

Build Multi-Layer Perceptrons (MLP)
Build Convolutional Neural Networks (CNN)
Build Recurrent Neural Networks (RNN)

Deploy Machine Learning Models
Automate the Machine Learning Process with MLOps
Integrate Models into Machine Learning Systems

Secure Machine Learning Pipelines
Maintain Models in Production

Who it's for

Developers, analysts and data professionals moving into AI practice.

Before you start

A typical student in this course should have several years of experience with computing technology, including some aptitude in computer programming. This course is also designed to assist students in preparing for the CertNexus® Certified Artificial Intelligence (AI) Practitioner certification.

Certification

Prepares for

CertNexus

Tell us the course or certification you have in mind and we'll send the outline, upcoming dates, fees and private-team options.

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