XGBoost Courses and Certifications

Machine Learning Fundamentals in R

Predict categorical and numeric responses via classification and regression, and discover the hidden structure of datasets with unsupervised learning.

• DataCamp
• 1 day
• On-Demand
• Free Trial Available

Machine Learning Scientist in Python

Discover machine learning with Python and work towards becoming a machine learning scientist. Explore supervised, unsupervised, and deep learning.

• DataCamp
• 3 days 13 hours
• On-Demand
• Free Trial Available

Supervised Machine Learning in Python

Master the most popular supervised machine learning techniques to begin making predictions with labeled data.

• DataCamp
• 1 day 1 hour
• On-Demand
• Free Trial Available

Machine Learning Scientist in R

A machine learning scientist researches new approaches and builds machine learning models.

• DataCamp
• 2 days 17 hours
• On-Demand
• Free Trial Available

Introduction to Machine Learning

Explore machine learning concepts and workflows using AWS SageMaker, from data analysis to model deployment. Learn to apply ML techniques, use advanced algorithms, and optimize models for real-world scenarios.

• Udacity
• 18 hours
• On-Demand
• Paid Course

1littlecoder

AutoXGB - Automated ML with XGBoost + Optuna + FastAPI - Kaggle Demo

Explore AutoXGB, a Python library for automated machine learning using XGBoost, Optuna, and FastAPI. Learn its parameters and application in a Kaggle competition.

• YouTube
• 24 minutes
• On-Demand
• Free Video

Eran Feit

Object Classification Using VGG16 and XGBoost for Vehicle Classification with TensorFlow

Learn to classify vehicles using VGG16 and XGBoost in TensorFlow. Covers data preparation, feature extraction, model training, and testing. Gain practical skills in object classification and deep learning.

• YouTube
• 32 minutes
• On-Demand
• Free Video

The Machine Learning Engineer

MLOps: Databricks and MLFlow Hyper-parameter Tuning for XGBoost Models

Optimize machine learning models using Databricks and MLflow for hyperparameter tuning with XGBoost and HyperOpt.

• YouTube
• 56 minutes
• On-Demand
• Free Video

Augmented Startups

Build a Powerful Backend for Soil Fertility Analysis - Flask, XGBoost, and GPT Integration

Master backend development for soil analysis by integrating Flask APIs, XGBoost models, and GPT-powered insights. Create robust endpoints for IoT sensor data processing and AI-driven agricultural recommendations.

• YouTube
• 16 minutes
• On-Demand
• Free Video

Data Science Conference

MRI Brain Scan Classification Using FastSurfer, XGBoost and 3D CNNs

Master medical image classification techniques using FastSurfer pipeline, XGBoost, and 3D CNNs for MRI brain scan analysis. Learn preprocessing steps and implement neural networks in PyTorch for advanced medical data analysis.

• YouTube
• 1 hour 20 minutes
• On-Demand
• Free Video

DigitalSreeni

Understanding Model Predictions with SHAP - XGBoost vs Neural Networks

Discover how SHAP explains machine learning predictions using game theory concepts, comparing XGBoost and neural networks on breast cancer data for interpretable AI decisions.

• YouTube
• 41 minutes
• On-Demand
• Free Video

XGBoost & Random Forest: Decision Trees + Boosting in R

53 ratings at Udemy

XGBoost, Random Forest, Decision Trees, Gradient Boosting, ROC Curve/AUC, Machine Learning in R (RStudio), rpart, party

• Udemy
• 5 hours 58 minutes
• On-Demand
• Paid Course

Ensemble Methods from Scratch

Master ensemble methods by building Bagging, Random Forest, AdaBoost, and Gradient Boosting implementations from scratch. Learn to enhance predictive models through hands-on coding without relying on libraries.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Microcredential

Improving Machine Learning and Deep Learning Models

Master model optimization through hands-on techniques covering evaluation, regularization, hyperparameter tuning, and neural network enhancement with scikit-learn, XGBoost, and PyTorch.

• CodeSignal
• 4 hours
• On-Demand
• Free Certificate
• 4 courses

Fixing Classical Models – Diagnosis & Regularization

Discover how to diagnose and fix underperforming ML models through evaluation metrics, regularization techniques, capacity tuning, and early stopping with scikit-learn and XGBoost.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate