Model Selection Courses and Certifications

Coursera

Apply AI Techniques & Prescriptives

Apply ensemble AI techniques to business decision problems, weigh accuracy, latency and interpretability trade-offs, and optimize product mix with linear programming and weighted-scoring models.

• Coursera
• 3 weeks, 1 hour a week
• Self-Paced
• Paid Course

HuggingFace

Getting Started with Hugging Face Transformers

Navigate the Hugging Face Hub's two million models: run pipeline inference on text, vision and audio, tokenize with AutoTokenizer, load AutoModel classes, and judge model cards.

• Coursera
• 4 weeks, 1 hour a week
• Self-Paced
• Paid Course

Packt

Agentic AI Foundations: Architectures & Adaptation Strategy

Learn to select, deploy, and adapt large language models with RAG and fine-tuning, then design hierarchical agentic architectures for enterprise automation.

• Coursera
• 4 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coursera

Automate, Evaluate and Deploy ML Models Confidently

Build a CI/CD pipeline with GitHub Actions and MLflow: select models from Optuna trials by cost and latency, and gate underperforming models from production.

• Coursera
• 2 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coursera

Optimize AI: Build Reusable Model Pipelines

Build standardized, reproducible ML pipelines with Scikit-learn's Pipeline object, weighing large pre-trained versus smaller custom models on inference speed, cost, and versioning.

• Coursera
• 2 weeks, 1 hour a week
• Self-Paced
• Paid Course

Coursera

Unlock Product Insights: Analyze and Evaluate

Apply a six-step hypothesis-driven analysis framework to product questions and weigh decision trees against logistic regression on interpretability, data characteristics, and preprocessing needs.

• Coursera
• 2 weeks, 1 hour a week
• Self-Paced
• Paid Course

Packt

NVIDIA GenAI & LLMs: Learn and Pass NCA-GENL Certification

Learn to build and customize generative AI systems, understand transformer architecture, select and train models, use NVIDIA CUDA, RAPIDS, TensorRT, and Triton, and prepare for NCA-GENL certification.

• Coursera
• 14 weeks, 1 hour a week
• Self-Paced
• Paid Course

Gen AI Dev- Implementing Cost Opt. & Resource Eff Strategies

Implement generative AI cost optimization through token efficiency, cost-effective model selection, resource utilization, throughput maximization, and caching strategies.

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

Claude Platform 101

Build from Claude chat to production agents by understanding requests, tool use, agent loops, context limits, and managed handoffs—each lesson ends with runnable code.

• Coursera
• 2 hours
• Self-Paced
• Free Online Course

John Savill's Technical Training

Using Foundry's Model Router to Simplify Optimal AI Model Selection

Discover how Microsoft Foundry's Model Router streamlines AI model selection for optimal performance in applications and agents through automated routing methods.

• YouTube
• 18 minutes
• Self-Paced
• Free Video

Krish Naik

EvalML AutoML Library to Automate Feature Engineering, Feature Selection, Model Creation and Tuning

Use EvalML to automate feature engineering, feature selection, machine learning pipeline construction, model tuning, and evaluation.

• YouTube
• 23 minutes
• Self-Paced
• Free Video

Krish Naik

Step-by-Step Machine Learning Project Implementation: EDA, Feature Engineering, Selection, and Model Training

A hands-on machine learning project follows data from cleaning and exploratory analysis through feature selection, model training, and hyperparameter tuning.

• YouTube
• 1 hour 26 minutes
• Self-Paced
• Free Video

Data Science Festival

Choosing the Right LLM - A Framework for Model Evaluation and Selection

Discover a systematic approach to evaluating and selecting Large Language Models for specific tasks, focusing on practical frameworks and custom testing methods for optimal results.

• YouTube
• 44 minutes
• Self-Paced
• Free Video

Learn to choose and tune a linear regression model for a research question, then justify and report your choices through a Craigslist analysis.

• Codecademy
• 1 hour
• Self-Paced
• Free Trial Available

Amazon Web Services;  Amazon

AWS ML Engineer Associate 2.1 Choose a Modeling Approach

Choose cost-efficient, interpretable machine learning approaches across AWS AI services, SageMaker algorithms, JumpStart solutions, and Bedrock built-in solutions.

• AWS Skill Builder
• 1 hour 30 minutes
• Self-Paced
• Paid Course