Shrinking 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. Machine Learning with PySpark: Customer Churn Analysis

This 90-minute guided-project, "Pyspark for Data Science: Customer Churn Prediction," is a comprehensive guided-project that teaches you how to use PySpark to build a machine learning model for predicting customer churn in a Telecommunications company. This guided-project covers a range of essential tasks, including data loading, exploratory data analysis, data preprocessing, feature preparation, model training, evaluation, and deployment, all using Pyspark. We are going to use our machine...

3. Productivity Machine: Time Management & Productivity Hacks

4.5

(27,996)

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

4. Machine Learning Product Management: A Practical Guide 2023

4.5

(268)

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

5. 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...

6. 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...

7. 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...

8. Deployment of Machine Learning Models

4.5

(4,961)

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

9. Build and Operate Machine Learning Solutions with Azure

Azure Machine Learning is a cloud platform for training, deploying, managing, and monitoring machine learning models. In this course, you will learn how to use the Azure Machine Learning Python SDK to create and manage enterprise-ready ML solutions. This is the third course in a five-course program that prepares you to take the DP-100: Designing and Implementing a Data Science Solution on Azurecertification exam. The certification exam is an opportunity to prove knowledge and expertise operate...

10. 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!...

11. 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...

12. Mechanical design and Product development process

4.2

(604)

Learn the basic ideas and concepts behind developing mechanical products related to mechanical engineering...

13. 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...

14. Data Science: Master Machine Learning Without Coding

4.7

(911)

Learn Fundamentals Of Data Science & Machine Learning With Rapidminer (No Coding). Dataset & Solutions Included...

15. Machine Learning with Javascript

4.7

(3,132)

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

16. Deployment of Machine Learning Models in Production Python

4.5

(341)

Deploy ML Model with BERT, Distil BERT, Fast Text NLP Models in Production with Flask, u WSGI, and NGINX at AWS EC2...

17. 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...

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. Executive Briefing: Machine Learning

4.1

(5,211)

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