Certified Artificial Intelligence Practitioner
A comprehensive, hands-on program for aspiring AI professionals. Learn to develop, train, and deploy machine learning models, build neural networks, and apply ethical AI practices — all aligned with the CertNexus AIP-210 certification exam.
Duration:
Fees with SST:
5 Days
RM 7,020.00
Artificial Intelligence and Machine Learning have become the cornerstone of business innovation. The Certified Artificial Intelligence (AI) Practitioner (CAIP) course from CertNexus equips you with the knowledge and skills to develop, test, and deploy AI and ML solutions confidently.
This 5-day instructor-led course covers the end-to-end AI project lifecycle — from problem framing, dataset preparation, and model training to model evaluation, deployment, and governance. You’ll build regression, classification, clustering, and neural network models while applying ethical and privacy standards in your AI projects.
Designed for data analysts, developers, and business professionals alike, this program bridges theory and hands-on application using open-source tools such as Python, scikit-learn, and Keras — preparing you for real-world AI implementation and the CertNexus AIP-210 certification exam.
Module 1: Solving Business Problems Using AI and ML
Identify business problems solvable through AI/ML, explore big data, workflows, concept drift, and tool selection.
Module 2: Collecting and Refining the Dataset
Collect datasets, clean data, analyze with statistics, use visualizations, and prepare training/testing data.
Module 3: Setting Up and Training a Model
Configure, train, and tune models using bias–variance management, regularization, and cross-validation.
Module 4: Finalizing a Model
Translate results into business actions and integrate models into long-term business workflows.
Module 5: Building Linear Regression Models
Develop linear and regularized regression models with gradient descent and error analysis.
Module 6: Building Classification Models
Train binary and multi-class classification models (Logistic Regression, k-NN) and evaluate performance metrics.
Module 7: Building Clustering Models
Apply k-Means and Hierarchical clustering; assess results using silhouette and elbow methods.
Module 8: Building Advanced Models
Implement Decision Trees, Random Forests, and ensemble learning models.
Module 9: Building Support-Vector Machines (SVMs)
Train linear and non-linear SVMs with kernel tricks for classification and regression.
Module 10: Building Artificial Neural Networks (ANNs)
Design and train MLPs and CNNs; explore GAN architectures for generative learning.
Module 11: Promoting Data Privacy and Ethical Practices
Protect data privacy, avoid bias, implement responsible AI governance, and ensure compliance.
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Frequently Asked Questions (FAQs)
Is coding required for this course?
Yes. You’ll use Python-based tools such as scikit-learn and Keras for hands-on exercises.
Will I build real AI models?
Yes. You’ll create regression, classification, clustering, and neural network models with real data.
Is this certification globally recognized?
Yes. The CertNexus CAIP™ is recognized internationally across industries.
What industries value this certification most?
It’s highly sought in finance, healthcare, retail, manufacturing, and technology sectors.
Do I need prior AI experience?
Basic AI knowledge (e.g., AIBIZ™) is helpful but not mandatory.