Pragmatic AI Labs Courses

AWS Generative AI and Foundation Models

Master building generative AI solutions on AWS using Amazon Bedrock, RAG pipelines, Amazon Q Developer, and open-source LLMs, while evaluating trade-offs between managed services and no-code platforms.

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

AWS Intelligent Applications with Amazon Bedrock

Master building intelligent applications with Amazon Bedrock—explore foundation models, implement APIs in Bash and Rust, create knowledge bases, and construct autonomous agents with RAG capabilities.

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

Build a Production SaaS Application with AI

Master building a complete SaaS app with AI tools—covering FastAPI development, Docker containerization, CI pipelines, landing pages, pricing tiers, API authentication, and deployment from MVP to production launch.

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

Conversational Bot Architecture with Rust and Deno

Master conversational bot development using Rust and Deno, covering Cargo workspaces, Tokio async runtime, Amazon Bedrock LLM integration, and Discord deployment for multi-platform bot systems.

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

OO: Python to Rust

Master object-oriented design in Rust by translating Python OO patterns—dataclasses, ABCs, mixins, and design patterns—into idiomatic Rust using structs, traits, generics, and enums.

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

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

Data Engineering with Delta Lake on Databricks

Master production-ready data pipelines using Delta Live Tables and Medallion Architecture on Databricks through hands-on labs and a complete inventory management capstone project.

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

Databricks Lakehouse Fundamentals

Discover how to build data pipelines on Databricks Lakehouse Platform with hands-on PySpark, Delta Lake, and Unity Catalog training for complete data engineering workflows.

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

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