Gradient Boosting Courses and Certifications

Coursera

Scikit-Learn For Machine Learning Classification Problems

19 ratings at Coursera

Learn to build and train classifier models using Scikit-Learn, exploring algorithms for classification, regression, and clustering, including support vector machines, random forests, and k-means.

• Coursera
• 1 hour 48 minutes
• Self-Paced
• Paid Course

Coursera

Scikit-Learn to Solve Regression Machine Learning Problems

11 ratings at Coursera

Learn to build and train regression models using Scikit-Learn, exploring algorithms like support vector machines, random forests, and gradient boosting. Gain practical skills applicable to various industries.

• Coursera
• 1 hour 56 minutes
• Self-Paced
• Paid Course

Machine Learning in Healthcare: Fundamentals & Applications

10 ratings at Coursera

Explore data mining in healthcare, from theoretical foundations to practical applications. Learn to select methods, use software, and address real-world challenges in data cleaning, transformation, and modeling.

• Coursera
• 18 hours 23 minutes
• Self-Paced
• Paid Course

Modeling Time Series and Sequential Data

Aprenda a modelar séries temporais e dados sequenciais usando abordagens tradicionais, bayesianas e de aprendizado de máquina. Explore técnicas avançadas de previsão e combine diferentes métodos para melhorar a precisão.

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

Coursera

Machine/Deep Learning for Mining Quality Prediction-Enhanced

Train machine learning and deep learning models to predict Silica Concentrate in iron ore, enhancing mining efficiency with faster, accurate predictions compared to traditional methods.

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

Packt

Machine Learning Foundations

Master feature engineering, core ML algorithms, and advanced techniques like neural networks and reinforcement learning through hands-on Python implementation.

• Coursera
• 7 hours 22 minutes
• Self-Paced
• Paid Course

Coursera

ML: Build, Train, Justify Models

Master practical ML workflows: transform business problems into ML tasks, train logistic regression, random forest, and gradient boosting models, and justify selections using bias-variance reasoning.

• Coursera
• 3 hours 4 minutes
• Self-Paced
• Paid Course

Packt

Deep Learning and Advanced Techniques

Master advanced deep learning with ensemble methods, neural networks, and frameworks like TensorFlow, PyTorch, XGBoost for real-world AI applications and model deployment.

• Coursera
• 9 hours 23 minutes
• Self-Paced
• Paid Course

Coursera

Forecast Business Metrics: Uncover Value Drivers

Master supervised learning to forecast business metrics like EBITDA using Python, regression models, and explainable AI techniques for actionable insights.

• Coursera
• 2 hours 7 minutes
• Self-Paced
• Paid Course

Coursera

Nail Regression & Classification

Master predictive modeling through regression diagnostics, advanced classification methods, and systematic model evaluation for business-critical decisions.

• Coursera
• 3 hours 16 minutes
• Self-Paced
• Paid Course

Machine Learning: Classification

This course covers key supervised machine learning (ML) and classification techniques, including logistic regression, decision trees, ensemble methods, and handling unbalanced datasets. Build and evaluate classification models using real-world data.

• edX
• 2 weeks, 30-35 hours/week
• Self-Paced
• Free Online Course (Audit)

Coursera

Advanced Model Architectures & Language AI

Master advanced AI techniques including decision trees, ensemble methods, neural networks, LLMs, and RAG chatbots to build and deploy production-ready machine learning solutions.

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

10 Days: Prompt Engineering, Generative AI and Data Science

403 ratings at Udemy

All-in-One Prompt Engineering, Generative AI & Data Science Bootcamp: Build a Portfolio with GenAI & AI Agents Projects

• Udemy
• 14 hours 33 minutes
• Self-Paced
• Paid Course

EuroPython Conference

Histogram-based Gradient Boosting in scikit-learn 0.21

Explore the new Histogram-based Gradient Boosting implementation in scikit-learn 0.21, offering competitive performance with XGBoost and LightGBM for efficient machine learning on tabular data.

• YouTube
• 45 minutes
• Self-Paced
• Conference Talk

Decision Trees, Random Forests, Bagging & XGBoost: R Studio

242 ratings at Udemy

Decision Trees and Ensembling techinques in R studio. Bagging, Random Forest, GBM, AdaBoost & XGBoost in R programming

• Udemy
• 5 hours 56 minutes
• Self-Paced
• Paid Course