Decision Trees Courses and Certifications

Evaluating and Finalizing Your Feature-Driven Model

Master feature engineering across Linear Regression, Random Forest, and LightGBM—build model-specific features, compare RMSE results, and refine pipelines with evidence-based decisions.

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

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

Credential

Implementing AI Algorithms from Scratch in C++ (Part 1)

Master machine learning fundamentals by building regression, classification, and optimization algorithms from scratch in C++ without high-level libraries.

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

Ensemble Methods

Master ensemble methods by implementing Bagging, Random Forest, AdaBoost, and Stacking from scratch in C++ using mlpack for robust machine learning model aggregation.

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

Classification Algorithms and Metrics

Dive into classification algorithms by building Logistic Regression, k-NN, Naive Bayes, and Decision Trees from scratch without libraries, plus implement AUCROC metrics.

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

NPTEL;  IIT Delhi

Project and Production Management

5 ratings

Comprehensive overview of project and production management, covering identification, appraisal, scheduling, resource allocation, monitoring, and organizational aspects, plus production system lifecycle and decision-making tools.

• YouTube
• 1 day 15 hours
• Self-Paced
• Free Video

Kaggle;  Amazon Web Services;  Amazon Credential

Introduction to Machine Learning with TensorFlow

5 ratings

Learn supervised and unsupervised machine learning techniques using TensorFlow and Python. Master regression, neural networks, clustering, and more to solve real-world problems and build an image classifier.

• Udacity
• 49 hours
• Self-Paced
• Paid Course

Credential

Python for Data Science and Machine Learning

Dive into Python for data science and machine learning, gaining practical skills in sklearn, Pandas, matplotlib, and numPy to build complex data sets and analyze them for a career in this high-demand field.

• edX
• 14 weeks, 3-4 hours/week
• Self-Paced
• $598.00
• 2 courses

Predictive Modeling and Analytics

605 ratings at Coursera

Gain insights through data analysis, visualization, and predictive modeling techniques. Learn to use XLMiner for regression, classification, decision trees, and neural networks in business contexts.

• Coursera
• 10 hours 53 minutes
• Self-Paced
• Paid Course

Intro to Predictive Analytics Using Python

Master predictive analytics fundamentals using Python, from regression models to advanced techniques like random forests and unsupervised learning, enabling data-driven forecasting and pattern recognition.

• Coursera
• 10 hours 52 minutes
• Self-Paced
• Paid Course

Introduction to Machine Learning in Sports Analytics

27 ratings at Coursera

Explore supervised machine learning techniques using Python and real athletic data to predict sports outcomes, applying methods like SVM, decision trees, and ensembles to analyze professional leagues and wearable device data.

• Coursera
• 12 hours 55 minutes
• Self-Paced
• Paid Course

Introduction to AI for Cybersecurity

97 ratings at Coursera

Gain foundational knowledge of AI in cybersecurity, exploring techniques to enhance security, detect threats, and secure systems through hands-on implementations using tools like Jupyter Notebooks.

• Coursera
• 9 hours 55 minutes
• Self-Paced
• Paid Course

Coursera

Machine Learning Pipelines with Azure ML Studio

831 ratings at Coursera

Build end-to-end machine learning pipeline in Azure ML Studio using Adult Income Census data to predict income levels. Train, evaluate, and deploy a Two-Class Boosted Decision Tree classifier as a web service.

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

AI for Medical Prognosis

800 ratings at Coursera

In this course, you will build risk models and survival estimators for heart disease using statistical methods and a random forest predictor to determine patient prognosis.

• Coursera
• 1 day 5 hours 44 minutes
• Self-Paced
• Paid Course

Introduction to AI: Key Concepts and Applications

25 ratings at Coursera

Master essential AI foundations, from R.O.A.D framework to algorithm selection, data quality, and performance metrics. Gain practical insights for evaluating and implementing AI systems while balancing technical depth with strategic decision-making.

• Coursera
• 19 hours 58 minutes
• Self-Paced
• Paid Course