# Machine Learning Concepts Assessment

## Description
The Machine Learning Concepts assessment is designed to evaluate the knowledge and skills of entry-level to mid-level information technology professionals in designing and developing machine learning models for common business applications. The test measures a broad range of competencies including supervised and unsupervised learning algorithms, model evaluation and metrics, overfitting and underfitting, data preprocessing and feature engineering, and training, validation, and test set splits. It assesses familiarity with key algorithms such as linear regression, logistic regression, decision trees, random forests, and k-means clustering, as well as tools and frameworks including scikit-learn, TensorFlow, and PyTorch.

The assessment uses a variety of question formats including multiple choice, multiple correct answer, and essay composition questions, with questions drawn from a large pool to help prevent cheating. One or more questions are scored using artificial intelligence, and certain questions include individual time limits to further deter cheating and enhance predictive performance.

## Competencies Measures
- Data Preprocessing and Feature Engineering
- Model Evaluation and Metrics
- Model Evaluation and Metrics (Free Text Responses)
- Overfitting, Underfitting, and Model Generalization
- Supervised Learning Algorithms
- Supervised Learning Algorithms (Free Text Responses)
- Training, Validation, and Test Set Splits
- Unsupervised Learning and Clustering

## Metadata
- **Duration:** 19.0 Minutes
- **Language:** English (US)
- **Type:** Skills/Knowledge Assessment (Test)
- **Last Updated:** July 2, 2026

## Catalog Link
View additional details or to administer the assessment to a candidate here:
[View in Online Test Catalog](https://www.hravatar.com/ta/tests/9709/machine-learning-concepts.html)