Pragmatic AI Labs Courses

Career Certificate

Enterprise AI and Data Engineering with Databricks

12 ratings at Coursera

Master enterprise AI and data engineering on Databricks through hands-on lakehouse architecture, Delta Lake pipelines, MLflow tracking, generative AI with LLMs, and production MLOps governance.

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

Career Certificate

Rust for Data Engineering

6 ratings at Coursera

Master production-grade data engineering in Rust, building ETL pipelines, serverless functions, SQL/NoSQL systems, and GCP deployments through hands-on, project-driven courses with real workloads.

• Coursera
• Self-Paced
• Paid Course
• 31 courses

HelixDB From Zero

Explore HelixDB, a Rust-native graph and vector engine, mastering HelixQL schema design, graph traversal, vector search, hybrid-RAG patterns, and typed Rust client integration in one unified process.

• Coursera
• 1 hour
• Self-Paced
• Paid Course

IAC from Zero

Explore IAC fundamentals using OpenTofu and Forjar, covering plans, lifecycle, drift detection, policy gates, testing, and state security across ten feature comparisons.

• Coursera
• 5 weeks, 1 hour a week
• 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

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

GitHub: From Zero to Pull Request

Master Git and GitHub from setup to pull requests, then automate workflows with AI agents using MCP, GitHub Actions, and CI/CD pipelines in this hands-on, end-to-end guide.

• Coursera
• 4 hours 26 minutes
• Self-Paced
• Paid Course

GitHub: AI-Augmented Testing and Refactoring

Master AI-augmented workflows using GitHub Copilot for test-driven development, system-wide refactoring, and infrastructure-as-code generation with Ansible, Docker, and Terraform.

• Coursera
• 3 hours 22 minutes
• 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

AI-Powered Data Pipelines with Deno

Master building AI-powered data pipelines with Deno, covering task automation, git quality gates, standalone binary compilation, and dependency vendoring for production-ready, reproducible workflows.

• Coursera
• 3 hours
• 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

AI Code Review Automation with GitHub Actions

Master building an AI-powered code review bot with GitHub Actions, using LLMs to automate pull request feedback, from prompt engineering to GitHub Marketplace publishing.

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

AI Orchestration: From local models to cloud

Master AI orchestration across local and cloud environments—build prompt engineering pipelines, deploy models with Ollama and llamafile, optimize GPU inference in Rust, and design cost-effective workflows using AWS Spot instances.

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