technifyed

Overview

Streamline AI Operations: Leverage DevOps, DataOps, and MLOps for End-to-End Machine Learning Solutions.

What you'll learn

  • Use web frameworks like Gradio & Hugging Face for interactive ML
  • Build command-line tools for ML/AI applications with Click
  • Leverage Rust's performance for Kubernetes, Docker & Serverless use cases
  • Containerize and deploy ML pipelines across cloud environments

Skills you'll practise

MLOps (Machine Learning Operations)DataOpsGitHub CopilotArtificial IntelligenceSoftware EngineeringOperationsDevOpsRust (Programming Language)Machine Learning

Advantages and disadvantages

Advantages

  • University courses you can audit for free, with lectures, readings and practice quizzes.
  • A verified certificate from the university if you pay for it.
  • Self-paced: start any time.

Disadvantages

  • Graded assignments and the certificate need the paid track.
  • Audit access can expire a few weeks after the course ends.
  • Learning is free, but the certificate costs money.
  • Some parts (graded work, certificate) are paid.

Some points apply to every course of this kind; see how we rank.

Free to audit

  • Free: Choose "Audit this course" when you enrol: lectures, readings and practice are free.
  • Paid: Graded assignments and the verified certificate (Certificate $249). Audit access may end after the course closes.

Taught by

  • Noah GiftExecutive in Residence and Founder of Pragmatic AI Labs

Pragmatic AI Labs is in Tier 4: commercial training companies and platform-made courses of our institution ranking (58/100).

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