Pragmatic AI Labs Courses

Generative AI and LLMs on Databricks

Master production GenAI systems on Databricks through prompt engineering, RAG pipelines, model governance, and code intelligence with hands-on projects and evaluation metrics.

• Coursera
• 4 hours 13 minutes
• Self-Paced
• Paid Course

Machine Learning with Databricks and MLflow

Master MLflow and Databricks to build, track, and deploy production-ready machine learning models while solving the reproducibility crisis through structured experiment tracking.

• Coursera
• 4 hours 32 minutes
• Self-Paced
• Paid Course

Production Governance and MLOps on Databricks

Master Databricks governance, Unity Catalog, CI/CD workflows, and MLOps practices to build secure, reliable data pipelines and AI applications with hands-on tools and real-world code.

• Coursera
• 6 hours 59 minutes
• Self-Paced
• Paid Course

GitHub Enterprise Administration

Master GitHub Enterprise administration, covering SAML SSO, access permissions, security compliance, GitHub Actions at scale, and package management with hands-on demos.

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

GitHub Production Applications

Build a complete production app using GitHub Copilot, covering API design, business logic, database persistence, testing, and code review in a real-world development workflow.

• Coursera
• 3 hours 20 minutes
• Self-Paced
• Paid Course

GitHub: Advanced Prompt Engineering for Code

Master advanced GitHub Copilot techniques—multi-turn interactions, iterative refinement, and context control with @workspace and #file markers—to produce production-quality code efficiently.

• Coursera
• 3 hours 14 minutes
• Self-Paced
• Paid Course

GitHub: Codespaces, Actions, and Ecosystem Tools

Master cloud-based dev environments with GitHub Codespaces, GPU-accelerated AI workloads, Copilot-assisted coding, and automated CI/CD pipelines using GitHub Actions.

• Coursera
• 2 hours 38 minutes
• Self-Paced
• Paid Course

GitHub: Evaluating and Integrating AI Models

Explore GitHub Models to evaluate, select, and integrate AI models, build FastAPI endpoints, manage rate limits, and deploy production-ready AI applications using GitHub Codespaces and Azure AI.

• Coursera
• 5 hours 7 minutes
• Self-Paced
• Paid Course

GitHub: Governing AI-Generated Code

Master AI code governance with GitHub Copilot—validate, audit, and secure AI-generated code, configure custom rules, and select the right LLM for production workflows.

• Coursera
• 3 hours 44 minutes
• Self-Paced
• Paid Course

GitHub: Security, Identity, and Access

Master GitHub security by configuring 2FA, managing permissions with least-privilege principles, and implementing enterprise governance controls for accounts, repositories, and organizations.

• Coursera
• 2 hours 49 minutes
• Self-Paced
• Paid Course

Hugging Face Hub and Ecosystem Fundamentals

Discover how to navigate the Hugging Face ecosystem to find, evaluate, and deploy pre-trained ML models for text, image, and audio tasks across 500,000+ options without training from scratch.

• Coursera
• 2 hours 13 minutes
• Self-Paced
• Paid Course

Career Certificate

Next-Gen AI Development with Hugging Face

Master building, deploying, and scaling AI applications using Hugging Face's ecosystem through hands-on projects that run locally without cloud costs.

• Coursera
• 12 weeks, 5 hours/week
• Self-Paced
• Paid Course
• 4 courses

Large Language Models with Hugging Face

Master LLM deployment, prompt engineering, RAG implementation, and agentic systems using Hugging Face ecosystem for real-world AI applications.

• Coursera
• 7 hours 1 minute
• Self-Paced
• Paid Course

Advanced Fine-Tuning in Rust

Master memory-efficient fine-tuning of 7B parameter models on consumer hardware using QLoRA, transformers, and rigorous scientific validation methods in Rust.

• Coursera
• 6 hours 4 minutes
• Self-Paced
• Paid Course

Production ML with Hugging Face

Master production ML deployment using the Sovereign Rust Stack with zero Python dependencies across GPU, CPU, WebAssembly, and edge targets through hands-on projects.

• Coursera
• 5 hours 27 minutes
• Self-Paced
• Paid Course