MLOps, Machine Learning Operations for beginners

MLOps, Machine Learning Operations for beginners, available at $39.99, has an average rating of 3.9, with 16 lectures, based on 12 reviews, and has 37 subscribers.

You will learn about Understand the lifecycle of a Machine Learning model Gain the best practices for putting Machine Learning models in production Leverage the power of MLOps to productionalise Machine Learning models at scale Get some insights on how to choose your perfect MLOps stack This course is ideal for individuals who are Everyone or Data Scientists or Machine Learning Engineers or Software Engineers or DevOps Engineers It is particularly useful for Everyone or Data Scientists or Machine Learning Engineers or Software Engineers or DevOps Engineers.

Enroll now: MLOps, Machine Learning Operations for beginners

Summary

Title: MLOps, Machine Learning Operations for beginners

Price: $39.99

Average Rating: 3.9

Number of Lectures: 16

Number of Published Lectures: 16

Number of Curriculum Items: 16

Number of Published Curriculum Objects: 16

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

Understand the lifecycle of a Machine Learning model

Gain the best practices for putting Machine Learning models in production

Leverage the power of MLOps to productionalise Machine Learning models at scale

Get some insights on how to choose your perfect MLOps stack

Who Should Attend

Everyone

Data Scientists

Machine Learning Engineers

Software Engineers

DevOps Engineers

Target Audiences

Everyone

Data Scientists

Machine Learning Engineers

Software Engineers

DevOps Engineers

This course is about Machine Learning Operations.

Machine Learning and Artificial Intelligence have became a hot topic in recent years. Numerous techniques and algorithms were developed and proved their efficiencies in addressing business issuesand bringing value to companies. Take fraud detection, recommendation systems or autonomous vehicles, etc. as examples.

However, most of the developed machine learning models do not go to production! Among others, this is due to one major reason: Machine Learning models are not classical software.The existing frameworks and methodologies that work for classical software proved to be inadequate with Machine Learning models. Hence, new paradigms and concepts should be brought to handle the specificities of Machine Learning Algorithms.

This course is addressed to Data professionals (Data Scientists, Data Engineers, Machine Learning Engineers and Software Engineers) as well as to everyone who want to understand the lifecycle of a Machine Learning model from experimentation to production. In this course, wa re going to see the best practices and recommended ways to put machine learning models into production. This will allow us also to see how we can leverage the power of MLOps to deploy Machine Learning at scale. Finally, as deploying models is about tooling, we are going to have a look on how to choose its perfect stack when adopting Machine Learning Operations best practices.

Wish you a nice journey!

Course Curriculum

Chapter 1: Introduction

Lecture 1: Course Introduction

Lecture 2: Course audience and prerequisites

Lecture 3: Take the most of this course

Chapter 2: MLOps Concepts

Lecture 1: MLOps: ML and Ops

Lecture 2: MLOps in the eyes of the giants

Lecture 3: From MLOps to DevOps and Vice-versa

Lecture 4: Traditional Vs. Machine Learning programming – Part 1

Lecture 5: The Machine Learning Lifecycle – Part 1

Lecture 6: The Machine Learning Lifeycyle – Part 2

Chapter 3: MLOps actors

Lecture 1: Subject Matter Expert

Lecture 2: Data Scientist

Lecture 3: Data Engineer

Lecture 4: Software Engineer

Lecture 5: DevOps Engineer

Lecture 6: Machine Learning Engineer

Chapter 4: MLOps tools

Lecture 1: MLOps tools

Instructors

Dat Art
Data centric trainings and courses

Rating Distribution

1 stars: 1 votes

2 stars: 0 votes

3 stars: 3 votes

4 stars: 4 votes

5 stars: 4 votes

Frequently Asked Questions

How long do I have access to the course materials?

You can view and review the lecture materials indefinitely, like an on-demand channel.

Can I take my courses with me wherever I go?

Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!