Model Evaluation Courses and Certifications

Applied Machine Learning: Techniques and Applications

12 ratings at Coursera

Master applied machine learning techniques for computer vision, data analysis, and model evaluation. Gain hands-on experience with image processing, supervised learning, and essential skills in data pre-processing and performance assessment.

• Coursera
• 19 hours 24 minutes
• On-Demand
• Paid Course

Introduction to Social Computing

Explore social computing's impact on society. Gain skills in social media analytics, responsible AI, and gamification. Apply machine learning to real-world scenarios and understand online behavior dynamics.

• Coursera
• 20 hours 45 minutes
• On-Demand
• Paid Course

Masterclass Testing Machine Learning (AI) Models

713 ratings at Udemy

Gain basic understanding how to test Foundation Models, LLMs, Chatbots and AI bases systems.

• Udemy
• 13 hours 23 minutes
• On-Demand
• Paid Course

Data Science- Project Management Methodology-CRISP-DM-2025

667 ratings at Udemy

End to End High Level Overview of Data Science & AI projects

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

Machine Learning Product Management: A Practical Guide

661 ratings at Udemy

Kick start your career in Machine Learning Product Management with just one course.

• Udemy
• 4 hours 44 minutes
• On-Demand
• Paid Course

Meaningful Predictive Modeling

49 ratings at Coursera

Evaluate and compare predictive models using diagnostic techniques and performance measures. Learn to implement training/validation/test pipelines for robust model generalization.

• Coursera
• 8 hours 33 minutes
• On-Demand
• Paid Course

The Nuts and Bolts of Machine Learning

610 ratings at Coursera

Explore machine learning algorithms, from supervised to unsupervised techniques. Learn to apply models like Naive Bayes, decision trees, and K-means clustering to solve complex data problems and make predictions.

• Coursera
• 1 day 9 hours 53 minutes
• On-Demand
• Paid Course

Finetuning Large Language Models

613 ratings at Coursera

Learn essential concepts and techniques for finetuning large language models using your own data, enabling you to optimize performance and produce transformative results in natural language processing tasks.

• Coursera
• 1 hour 30 minutes
• On-Demand
• Paid Course

Machine Learning No-Code Approach: Using Azure ML Studio

583 ratings at Udemy

A hands-on approach to Machine Learning using the easy drag-n-drop environment of Azure Machine Learning Studio

• Udemy
• 2 hours 41 minutes
• On-Demand
• Paid Course

Support Vector Machines in Python: SVM Concepts & Code

556 ratings at Udemy

Learn Support Vector Machines in Python. Covers basic SVM models to Kernel-based advanced SVM models of Machine Learning

• Udemy
• 6 hours 20 minutes
• On-Demand
• Paid Course

Advanced Deployment Scenarios with TensorFlow

512 ratings at Coursera

Explore advanced deployment scenarios using TensorFlow Serving, TensorFlow Hub, TensorBoard, and federated learning to effectively bring machine learning models into real-world applications.

• Coursera
• 12 hours 52 minutes
• On-Demand
• Paid Course

Azure AI Foundry (AI Hub) : Prompt Flow, LLMOps & RAG

457 ratings at Udemy

Unlock Azure AI Studio Full Potential: Dive into Prompt Flow, Content Safety, Evaluation, LLMOps, and RAG Techniques

• Udemy
• 14 hours 7 minutes
• On-Demand
• Paid Course

Data Science at Scale - Capstone Project

26 ratings at Coursera

Apply data science skills to real-world projects, from data preparation to model evaluation. Collaborate with stakeholders on ambiguous problems, gaining practical experience in tackling complex challenges.

• Coursera
• 8 hours 10 minutes
• On-Demand
• Paid Course

Master Course : Fundamentals of Machine Learning (101 level)

325 ratings at Udemy

Machine Learning, Supervised Machine Learning, Unsupervised Machine Learning, Deep Learning, TensorFlow, Keras, NLP

• Udemy
• 1 hour 51 minutes
• On-Demand
• Paid Course

Machine Learning Introduction for Everyone

307 ratings at Coursera

Comprehensive introduction to machine learning concepts, applications, and techniques. Covers supervised/unsupervised learning, classification, regression, and model evaluation through hands-on labs and a final project.

• Coursera
• 6 hours 24 minutes
• On-Demand
• Paid Course