Slicing machine operator education requirements

1. Machine Learning Engineering for Production (MLOps)

Understanding machine learning and deep learning concepts is essential, but if you’re looking to build an effective AI career, you need production engineering capabilities as well.\n\nEffectively deploying machine learning models requires competencies more commonly found in technical fields such as software engineering and DevOps. Machine learning engineering for production combines the foundational concepts of machine learning with the functional expertise of modern software development and...

2. Deploying Machine Learning Models in Production

In the fourth course of Machine Learning Engineering for Production Specialization, you will learn how to deploy ML models and make them available to end-users. You will build scalable and reliable hardware infrastructure to deliver inference requests both in real-time and batch depending on the use case. You will also implement workflow automation and progressive delivery that complies with current MLOps practices to keep your production system running. Additionally, you will continuously...

3. Machine Learning Product Management: A Practical Guide 2023

4.5

(268)

Kick start your career in Machine Learning Product Management with just one course...

4. Productivity Machine: Time Management & Productivity Hacks

4.5

(27,996)

Productivity & Time Management Strategies for Goal Setting, Eliminating Distractions, & Building Habits for Success...

5. MLOps | Machine Learning Operations

This comprehensive course series is perfect for individuals with programming knowledge such as software developers, data scientists, and researchers. You'll acquire critical MLOps skills, including the use of Python and Rust, utilizing GitHub Copilot to enhance productivity, and leveraging platforms like Amazon SageMaker, Azure ML, and MLflow. You'll also learn how to fine-tune Large Language Models (LLMs) using Hugging Face and understand the deployment of sustainable and efficient binary...

6. Deployment of Machine Learning Models

4.5

(4,961)

Learn how to integrate robust and reliable Machine Learning Pipelines in Production...

7. The Complete Machine Learning Course with Python

4.5

(6,881)

Build a Portfolio of 12 Machine Learning Projects with Python, SVM, Regression, Unsupervised Machine Learning & More!...

8. Executive Briefing: Machine Learning

4.1

(5,211)

Machine Learning for Executives and Top-Level Managers: understand Machine Learning in under 90 Minutes...

9. Introduction to Machine Learning for Data Science

4.6

(13,692)

A primer on Machine Learning for Data Science. Revealed for everyday people, by the Backyard Data Scientist...

10. Machine Learning with Javascript

4.7

(3,132)

Master Machine Learning from scratch using Javascript and Tensorflow JS with hands-on projects...

11. Excel for Data Science and Machine Learning

4.5

(413)

Perform Machine Learning and Advanced Statistical Analysis On Your Own - Even If You Don't Code! 100% in Excel...

12. Machine Learning Classification Bootcamp in Python

4.5

(934)

Build 10 Practical Projects and Advance Your Skills in Machine Learning Using Python and Scikit Learn...

13. DP-100: A-Z Machine Learning using Azure Machine Learning

4.4

(6,728)

Microsoft Azure DP-100: Designing and Implementing a Data Science Solution Exam Covered. Learn Azure Machine Learning...

14. Ensemble Machine Learning in Python: Random Forest, AdaBoost

4.6

(2,091)

Ensemble Methods: Boosting, Bagging, Boostrap, and Statistical Machine Learning for Data Science in Python...

15. Machine Learning Practical: 6 Real-World Applications

4.5

(2,836)

Machine Learning - Get Your Hands Dirty by Solving Real Industry Challenges with Python...

16. Azure Machine Learning & MLOps: Beginner to Advance

4.4

(465)

The most compressive course covering MLOps and machine learning on Azure Zero to Hero...

17. Machine Learning No-Code Approach: Using Azure ML Studio

4.9

(542)

A hands-on approach to Machine Learning using the easy drag-n-drop environment of Azure Machine Learning Studio...

18. Data Science: Supervised Machine Learning in Python

4.6

(2,941)

Full Guide to Implementing Classic Machine Learning Algorithms in Python and with Scikit-Learn...

19. Machine Learning: A Beginner's Basic Introduction

4

(338)

Learn Machine Learning Basics with a Practical Example...