Cross-Validation Courses and Certifications

Hypertuning Classical Models

Master systematic hyperparameter optimization techniques using grid search, random search, and cross-validation strategies to transform weak ML baselines into high-performing models.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

PredictHealth's Multi-Factor Cost Models

Master advanced regression techniques to build sophisticated multi-factor prediction models with data cleaning, validation, and custom feature engineering for insurance cost analysis.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate

PredictHealth's Advanced Pricing System

Master advanced modeling techniques to build state-of-the-art insurance pricing systems with non-linear patterns, feature interactions, regularization, and robust validation methods.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

Python Machine Learning

Master machine learning fundamentals through hands-on Python programming, covering regression, classification, decision trees, and ensemble methods to solve real-world data problems.

• VDCI
• 30 hours
• Self-Paced
• $1,895.00

Foundations of Gradient Boosting

Master gradient boosting by building decision trees, creating ensembles, and understanding feature importance through hands-on banking data analysis and model optimization.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Python Machine Learning Advanced

Master advanced machine learning techniques using Python, including deep learning, ensemble methods, and model optimization for complex real-world applications.

• VDCI
• 30 hours
• Self-Paced
• $1,895.00

Statistical Learning with Python

Master statistical learning fundamentals through hands-on Python implementation, covering regression, classification, neural networks, and unsupervised methods without heavy mathematics.

• YouTube
• 20 hours 18 minutes
• Self-Paced
• Free Video

Statistical Learning with R

Master supervised and unsupervised learning techniques using R, from linear regression to deep learning, with hands-on implementation of modern data science methods.

• YouTube
• 20 hours 28 minutes
• Self-Paced
• Free Video

Data Science: Supervised Machine Learning in Python

3554 ratings at Udemy

Full Guide to Implementing Classic Machine Learning Algorithms in Python and with Scikit-Learn

• Udemy
• 6 hours 25 minutes
• Self-Paced
• Paid Course

Regression Analysis

10 ratings at Coursera

Master regression analysis techniques to model relationships, prevent overfitting, and make data-driven decisions. Explore linear and polynomial regression, regularization, cross-validation, and ensemble methods through hands-on practice.

• Coursera
• 1 day 16 hours 1 minute
• Self-Paced
• Paid Course

Resampling, Selection and Splines

Explore advanced statistical learning techniques for data science, including resampling methods, model optimization, and non-linear approaches to enhance prediction accuracy and interpretability.

• Coursera
• 15 hours 56 minutes
• Self-Paced
• Paid Course

Machine Learning for Marketers

Enhance marketing strategies with machine learning: predict customer behavior, optimize campaigns, uncover hidden patterns, and personalize experiences using advanced analytics techniques.

• Coursera
• 21 hours 57 minutes
• Self-Paced
• Paid Course

Coursera

Support Vector Machines in Python, From Start to Finish

162 ratings at Coursera

Build a Support Vector Machine classifier using scikit-learn and RBF Kernel to predict heart disease. Hands-on project using UCI Machine Learning Repository data, focusing on implementation and evaluation techniques.

• Coursera
• 1 hour 55 minutes
• Self-Paced
• Paid Course

EDUCBA

Recommendation Engine - Basics

29 ratings at Coursera

Discover how to build movie recommendation systems using Python, collaborative filtering, and the Surprise library with hands-on model evaluation and deployment techniques.

• Coursera
• 2 hours 43 minutes
• Self-Paced
• Paid Course

Predictive Analytics

Gain insights into predictive analytics with Python, learning to build models, diagnose performance issues, leverage advanced techniques like neural networks, and integrate data-driven insights into decision-making for digital transformation.

• Coursera
• 1 day 23 hours 19 minutes
• Self-Paced
• Paid Course