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Certified Artificial Intelligence (AI) Practitioner (CN8534)

CAIP - CertNexus - Eccentrix

Artificial intelligence (AI) and machine learning (ML) have become an essential part 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 course shows you how to apply various approaches and algorithms to solve business problems through AI and ML, follow a methodical workflow to develop sound solutions, use open source, off-the-shelf tools to develop, test, and deploy those solutions, and ensure that they protect the privacy of users.

  • Specify a general approach to solve a given business problem that uses applied AI and ML.
  • Collect and refine a dataset to prepare it for training and testing.
  • Train and tune a machine learning model.
  • Finalize a machine learning model and present the results to the appropriate audience.
  • Build linear regression models.
  • Build classification models.
  • Build clustering models.
  • Build decision trees and random forests.
  • Build support-vector machines (SVMs).
  • Build artificial neural networks (ANNs).
  • Promote data privacy and ethical practices within AI and ML projects

Suivez nos formations CertNexus en direct avec notre classe virtuelle.
Des tarifs spéciaux pourraient être applicables sur votre inscription de groupe - communiquez avec nous pour en savoir plus.

Un test de préparation est disponible afin de vous aider à évaluer vos compétences actuelles par rapport aux thèmes abordées lors de cette formation.

Démarrez le test de préparation ici, c'est gratuit: https://certnexus.com/caip-readiness-assessment/ (les instructions sont fournies sur la page)

Votre clé d'accès: CNWCIZH4CF

Classe publique

Durée: 
5 jours / 35 heures

Classe privée

En ligne
Nombre de participants minimum: 3
5 jours / 35 heures
Prix sur demande
français ou anglais
Plan de formation: 

Module 1Solving Business Problems Using AI and ML

  • Identify AI and ML Solutions for Business Problems
  • Formulate a Machine Learning Problem
  • Select Appropriate Tools

Module 2: Collecting and Refining the Dataset

  • Collect the Dataset
  • Analyze the Dataset to Gain Insights
  • Use Visualizations to Analyze Data
  • Prepare Data

Module 3Setting Up and Training a Model

  • Set Up a Machine Learning Model
  • Train the Model

Module 4Finalizing a Model

  • Translate Results into Business Actions
  • Incorporate a Model into a Long-Term Business Solution

Module 5Building Linear Regression Models

  • Build a Regression Model Using Linear Algebra
  • Build a Regularized Regression Model Using Linear Algebra
  • Build an Iterative Linear Regression Model

Module 6Building Classification Models

  • Train Binary Classification Models
  • Train Multi-Class Classification Models
  • Evaluate Classification Models
  • Tune Classification Models

Module 7Building Clustering Models

  • Build k-Means Clustering Models
  • Build Hierarchical Clustering Models

Module 8Building Advanced Models

  • Build Decision Tree Models
  • Build Random Forest Models

Module 9Building Support-Vector Machines

  • Build SVM Models for Classification
  • Build SVM Models for Regression

Module 10Building Artificial Neural Networks

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

Module 11Promoting Data Privacy and Ethical Practices

  • Protect Data Privacy
  • Promote Ethical Practices
  • Establish Data Privacy and Ethics Policies
Exclusivités: 
  • Un an d'accès à l'enregistrement vidéo de votre cours
  • Matériel de cours accessible au format électronique
  • Certificat de présence
Pré-requis: 

To ensure your success in this course, you should have at least a high-level understanding of fundamental AI concepts, including, but not limited to: machine learning, supervised learning, unsupervised learning, artificial neural networks, computer vision, and natural language processing. You can obtain this level of knowledge by taking the CertNexus AIBIZ (Exam AIZ-110) course. You should also have experience working with databases and a high-level programming language such as Python, Java, or C/C++.

Informations sur la certification: 

Caractéristiques de l'examen:

  • Préparatoire pour la certification Certified Artificial Intelligence (AI) Practitioner
  • Code de l'examen: AIP-110
  • Coût: 0$ (inclus dans votre formation)
  • Compétences mesurées
    • This exam will certify that the candidate has the knowledge and skill set of AI concepts, technologies, and tools that will enable them to become a capable AI practitioner in a wide variety of AI-related job functions.
  • Nombre de questions: 80
  • Durée: 2 heures
  • Notes de passage: 60%
  • Tous les détails... 

Contact us for more price information:

Ksenija Kesić
Sales Development Manager

Eccentrix
Office: +381 11 71 38 192
Mobile: +381 65 31 38 196
E-mail: Ksenija.Kesic@eccentrix.rs

9đ, Milutina Milankovića St,
11070 New Belgrade
www.eccentrix.rs