Download the certification brochure (Spanish): Click here

Exam Details

• Exam Name: Machine Learning Certified Associate (MLCA)
• 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: 90 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 · 10 CPD credits per year

Main Subjects

• Machine Learning fundamentals (20%): ML and AI; Supervised, unsupervised and reinforcement learning; Linear algebra and gradient descent; Project lifecycle.
• Data preparation and exploration (20%): Statistical summary and visualization; Missing values and outliers; Encoding and scaling; Class imbalance.
• Modeling and supervised learning (25%): Linear and logistic regression; Trees and Random Forest; SVM, KNN and Naive Bayes; Cross-validation and regularization.
• Unsupervised learning, evaluation and deployment (20%): K-means, DBSCAN and hierarchical clustering; PCA; ROC, AUC and confusion matrix; Deployment and monitoring.
• ML ethics, governance and applications (15%): Bias and fairness; Privacy; Model governance; Business use cases.

Who is this certification for?

• Data and BI analysts: Who are moving into predictive modeling.
• AI-oriented software engineers: Who add ML to their products.
• Future data scientists and ML engineers: Who are starting the Machine Learning path.

Prerequisites

No mandatory prerequisites: no prior experience, training or certification is required. Registration is direct with CertJoin or through an authorized partner. Recommended (not mandatory): basic statistics and Python programming. Next levels: Machine Learning Certified Professional (MLCP) and Machine Learning Certified Expert (MLCE).