BONUS! Cyber Phoenix Subscription Included: All Phoenix TS students receive complimentary ninety (90) day access to the Cyber Phoenix learning platform, which hosts hundreds of expert asynchronous training courses in Cybersecurity, IT, Soft Skills, and Management and more!
Course Overview
This 5 day, instructor led Certified Artificial Intelligence Practitioner™ (CAIP) course brought to you by CertNexus 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. At the completion of this course, participants will be able to:- 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.
Schedule
Certified Artificial Intelligence Practitioner™ (CAIP)
date
location
price
Program Level
AdvancedTraining Delivery Methods
Group LiveDuration
5 Days / 32 hours TrainingCPE credits
26 NASBA CPE CreditsField of Study
Information TechnologyAdvanced Prep
N/ACourse Registration
Candidates can choose to register for the course by via any of the below methods:- Email: Sales@phoenixts.com
- Phone: 301-582-8200
- Website: www.phoenixts.com
Complaint Resolution Policy
To view our complete Complaint Resolution Policy policy please click here: Complaint Resolution PolicyRefunds and Cancellations
To view our complete Refund and Cancellation policy please click here: Refund and Cancellation PolicyCourse Outline
Lesson 1: Solving Business Problems Using AI and ML
- Topic A: Identify AI and ML Solutions for Business Problems
- Topic B: Formulate a Machine Learning Problem
- Topic C: Select Approaches to Machine Learning
Lesson 2: Preparing Data
- Topic A: Collect Data
- Topic B: Transform Data
- Topic C: Engineer Features
- Topic D: Work with Unstructured Data
Lesson 3: Training, Evaluating, and Tuning a Machine Learning Model
- Topic A: Train a Machine Learning Model
- Topic B: Evaluate and Tune a Machine Learning Model
Lesson 4: Building Linear Regression Models
- Topic A: Build Regression Models Using Linear Algebra
- Topic B: Build Regularized Linear Regression Models
- Topic C: Build Iterative Linear Regression Models
Lesson 5: Building Forecasting Models
- Topic A: Build Univariate Time Series Models
- Topic B: Build Multivariate Time Series Models
Lesson 6: Building Classification Models Using Logistic Regression and k-Nearest Neighbor
- Topic A: Train Binary Classification Models Using Logistic Regression
- Topic B: Train Binary Classification Models Using k-Nearest Neighbor
- Topic C: Train Multi-Class Classification Models
- Topic D: Evaluate Classification Models
- Topic E: Tune Classification Models
Lesson 7: Building Clustering Models
- Topic A: Build k-Means Clustering Models
- Topic B: Build Hierarchical Clustering Models
Lesson 8: Building Decision Trees and Random Forests
- Topic A: Build Decision Tree Models
- Topic B: Build Random Forest Models
Lesson 9: Building Support-Vector Machines
- Topic A: Build SVM Models for Classification
- Topic B: Build SVM Models for Regression
Lesson 10: Building Artificial Neural Networks
- Topic A: Build Multi-Layer Perceptrons (MLP)
- Topic B: Build Convolutional Neural Networks (CNN)
- Topic C: Build Recurrent Neural Networks (RNN)
Lesson 11: Operationalizing Machine Learning Models
- Topic A: Deploy Machine Learning Models
- Topic B: Automate the Machine Learning Process with MLOps
- Topic C: Integrate Models into Machine Learning Systems
Lesson 12: Maintaining Machine Learning Operations
- Topic A: Secure Machine Learning Pipelines
- Topic B: Maintain Models in Production
- Appendix A: Mapping Course Content to CertNexus® Certified Artificial Intelligence (AI) Practitioner (Exam AIP-210)
- Appendix B: Datasets Used in This Course
CertNexus Certified Artificial Intelligence Practitioner™ (CAIP) Exam Information
EXAM CODE: (Exam AIP-210)
LAUNCH DATE: March 2023
SUNSET DATE: TBD
PASSING SCORE: 60% or 59% depending on exam form
NUMBER OF ITEMS: 80
ITEM FORMATS: Multiple Choice/Multiple Response
TARGET CANDIDATE
This certification exam is designed for practitioners who are seeking to demonstrate a vendor neutral, cross-industry skill set within AI and with a focus on ML that will enable them to design, implement, and hand off an AI solution or environment.
EXAM DURATION
120 minutes (including 5 minutes for Candidate Agreement and 5 minutes for Pearson VUE tutorial)
EXAM OPTIONS
In person at Pearson VUE test centers or online via Pearson OnVUE online proctoring
BONUS! Cyber Phoenix Subscription Included: All Phoenix TS students receive complimentary ninety (90) day access to the Cyber Phoenix learning platform, which hosts hundreds of expert asynchronous training courses in Cybersecurity, IT, Soft Skills, and Management and more!
Phoenix TS is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have final authority on the acceptance of individual courses for CPE credit. Complaints re-garding registered sponsors may be submitted to the National Registry of CPE Sponsors through its web site: www.nasbaregistry.org
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