Pragmatic AI Labs Courses

Career Certificate

Enterprise AI and Data Engineering with Databricks

9 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

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

Career Certificate

Mastering GitHub

Master GitHub from foundational Git skills to autonomous AI agent systems, covering CI/CD, Copilot, enterprise security, and prompt engineering in a 9-course path.

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

AI-Powered Analytics and Performance Engineering

Master building AI-powered analytics pipelines on AWS using Amazon Bedrock, Lambda benchmarking, and Amazon Q for BI, including Rust integration, cost optimization, and natural language SQL queries.

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

Agentic AI: Actor Models and Subagent Architecture

Master agentic AI systems using actor model principles, subagent architecture, and multi-language implementations in Rust, Go, and Deno for fault-tolerant, production-ready AI solutions.

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

Building deterministic MCP Agents

Master building deterministic AI agents using MCP, PMAT quality metrics, finite state machines, and property-based testing for verifiable, repeatable outputs across real-world codebases.

• Coursera
• 3 hours 40 minutes
• Self-Paced
• Paid Course

CLI Automation with Amazon Q and CloudShell

Master CLI automation using Amazon Q and CloudShell to deploy containers to ECR, build CDK infrastructure, and develop Rust apps with AI-powered assistance in AWS workflows.

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

Deterministic LLM programming

Master deterministic LLM programming with AWS Bedrock, RAG pipelines, local inference via llama.cpp, and quality evaluation for production-grade AI systems.

• Coursera
• 5 hours 11 minutes
• Self-Paced
• Paid Course

Enterprise AIOps with Amazon Q Business

Master enterprise AIOps on AWS by deploying Amazon Q Business, managing AI costs with CloudShell automation, and implementing production MLOps pipelines and RAG workflows using Amazon Bedrock.

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

LLM Security and Vulnerabilities

Explore LLM security vulnerabilities—prompt injection, model theft, insecure outputs—and master defense patterns to protect AI-powered applications in production.

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

Multi-modal AI

Explore multi-modal AI development by combining visual and textual inputs to convert screenshots into production code using GitHub Copilot, Playwright, and MCP for automated, iterative workflows.

• Coursera
• 3 hours 36 minutes
• Self-Paced
• Paid Course

Career Certificate

AI Tooling

Master generative AI on AWS, from Amazon Bedrock fundamentals to deploying serverless multi-model systems, covering security, orchestration, agentic AI, and SaaS development with Rust and Python.

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

Fine-Tuning Transformers with Hugging Face

Master transformer fine-tuning with Hugging Face ecosystem, from data preprocessing to model deployment, building production-ready sentiment analysis systems.

• Coursera
• 7 hours 52 minutes
• 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