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Exam Details

• Exam Name: Machine Learning Certified Professional (MLCP)
• Exam Format: Multiple choice, online with remote supervision (proctoring)
• Exam Delivery: Safe Exam Browser
• Number of Questions: 50 questions: 70% scenarios / 30% conceptual
• Exam Duration: 120 minutes
• Passing Score: 70% (35 out of 50 correct answers)
• Available Languages: Spanish / English
• Attempts: Maximum 2 attempts (minimum 15 days between attempts)
• Validity: 3 years · 15 CPD credits per year

Main Subjects

• ML and data science fundamentals (20%): Paradigms and deep learning; Algebra, calculus and optimization; Probability and bias-variance; Python, scikit-learn, TensorFlow and PyTorch.
• Data preparation and engineering (15%): EDA; Feature engineering; PCA, t-SNE and UMAP; Reproducibility.
• Supervised and unsupervised models (25%): Regression and trees; Random Forest and Gradient Boosting; k-Means and hierarchical clustering; MLP, CNN and RNN/LSTM.
• Evaluation, optimization and interpretation (20%): Precision, recall, F1 and AUC-ROC; Grid, random and Bayesian search; L1, L2 and Elastic Net; SHAP and LIME.
• Deployment, ethics and AI governance (20%): MLOps and versioning; Bias and differential privacy; NIST AI RMF, ISO/IEC 42001 and the EU AI Act; Model cards.

Who is this certification for?

• Data scientists: Who seek formal certification of their ML skills.
• ML engineers: Who demonstrate mastery of modeling and MLOps.
• AI-focused analysts and software engineers: Who take models into production.

Prerequisites

Mandatory: Machine Learning Certified Associate (MLCA). The path continues to Machine Learning Certified Expert (MLCE).