Certified Artificial Intelligence (AI) Practitioner (CAIP)

مسار لخمسة أيام محايد تجاه المورّدين لبناء حلول الذكاء الاصطناعي وتعلّم الآلة. تُعدّ البيانات، وتدرّب النماذج وتقيّمها وتضبطها، وتبني نماذج الانحدار والتنبّؤ والتصنيف والتجميع والشبكات العصبية، استعداداً لشهادة CAIP.

5 أياممتوسط12 وحدةCertified Artificial Intelligence (AI) Practitioner (CAIP)

سجّل أو استفسر ←اسأل عبر واتساب

نظرة عامة

ما ستتعلّمه

المحتوى التقني أدناه معروضٌ باللغة الإنجليزية كما ورد في منهاج الدورة، حفاظاً على دقّة المصطلحات.

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.

المنهاج

12 وحدة

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

لمن هذه الدورة

المطوّرون والمحلّلون ومختصو البيانات المنتقلون إلى ممارسة الذكاء الاصطناعي.

قبل أن تبدأ

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.

الشهادة

الشهادة التي تؤهّلك لها

CertNexus

Certified Artificial Intelligence (AI) Practitioner (CAIP)

AIP-110

دورة واحدة

CertNexus

3 أيام

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أخبرنا بالدورة أو الشهادة التي تهمّك، ونرسل لك المنهاج والمواعيد القادمة والرسوم وخيارات التدريب الخاص لفريقك.

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