Model Optimization Courses and Certifications

Model Optimization Foundational Principles

Master essential techniques to enhance machine learning models through quantization, pruning, profiling, and hands-on GPT-2 optimization for real-world deployment.

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

Microcredential

Machine Learning Model Optimization

Master advanced techniques for optimizing ML models through quantization, pruning, compression, and hardware acceleration to deploy efficient, scalable solutions.

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

Intro to Model Optimization in Machine Learning

Master machine learning optimization techniques using real medical data, from hyperparameter tuning to advanced ensemble methods, enhancing your ability to build accurate predictive models.

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

Optimizing AI Strategies

Master AI model optimization through hyperparameter tuning, regularization, and deployment strategies to enhance trading performance and prevent overfitting.

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

Data Science Dojo

Model Optimization - Series Conclusion - Introduction to Text Analytics with R

Optimize text analytics models, explore sensitivity/specificity tradeoffs, and discover resources for further study in R. Learn feature engineering and algorithm selection for improved effectiveness.

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

PyTorch Techniques for Model Optimization

Master advanced PyTorch optimization techniques including regularization, dropout, batch normalization, and learning rate scheduling to enhance model performance and prevent overfitting.

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

Model Evaluation and Optimization

Master advanced techniques for evaluating and optimizing regression models, from cross-validation to hyperparameter tuning and regularization methods for enhanced predictive accuracy.

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

TensorFlow Techniques for Model Optimization

Master advanced TensorFlow optimization techniques, from regularization and dropout implementation to callback utilization and Scikit-Learn integration, enhancing model performance and preventing overfitting.

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

Coursera

Optimize AI Inference Speed & Accuracy

Master neural network optimization techniques to achieve 3-5x faster inference while maintaining accuracy across mobile, edge, and cloud deployments using profiling, pruning, and quantization.

• Coursera
• 4 hours 26 minutes
• On-Demand
• Paid Course

Coursera

Optimizing Models for Production

Master quantization, inference optimization, and hardware tuning to deploy efficient, scalable generative AI models in production environments.

• Coursera
• 8 hours 40 minutes
• On-Demand
• Paid Course

Packt

Foundations of Model Optimization and Deep Learning

Master model optimization and CNNs through hyperparameter tuning, regularization techniques, and hands-on image classification projects using Keras, TensorFlow, and PyTorch.

• Coursera
• 7 hours 7 minutes
• On-Demand
• Paid Course

Packt

Applied Machine Learning and Model Optimization

Master advanced ML algorithms, hyperparameter tuning, and model optimization techniques through hands-on projects with XGBoost, ensemble methods, and real-world applications.

• Coursera
• 21 hours 9 minutes
• On-Demand
• Paid Course

Deep Learning: Model Optimization and Tuning

208 ratings at LinkedIn Learning

Learn about various optimization and tuning options available for deep learning models and use them to improve models.

• LinkedIn Learning
• 54 minutes
• On-Demand
• Free Trial Available

Yannic Kilcher

Movement Pruning - Adaptive Sparsity by Fine-Tuning

Explore Movement Pruning, an adaptive sparsity technique for fine-tuning deep neural networks. Learn its advantages over Magnitude Pruning in transfer learning scenarios and its impact on model efficiency.

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

Trelis Research

How to Pick a GPU and Inference Engine for Large Language Models

Explore GPU selection and inference engine optimization for large language models. Compare quantization effects, software options, and cost-efficiency across various GPUs and model sizes.

• YouTube
• 1 hour 4 minutes
• On-Demand
• Free Video