Udacity | Machine Learning Engineer Nanodegree v4.0.0 [FCO]

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  • LanguageEnglish
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  • Last checkedJul. 27th '20
  • Date uploadedJul. 25th '20
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Nanodegree Program–nd009t
Publisher : Udacity
Subtitle : English CC Included
Updated : July 2020
Course Source : https://www.udacity.com/course/machine-learning-engineer-nanodegree--nd009t

Become a Machine Learning Engineer

Learn advanced machine learning techniques and algorithms -- including how to package and deploy your models to a production environment.

ESTIMATED TIME
- 3 Months
- At 10 hrs/week

PREREQUISITES
- Intermediate Python & Machine Learning Algorithms

IN COLLABORATION WITH



What You Will Learn

Machine Learning Engineer


Learn advanced machine learning techniques and algorithms and how to package and deploy your models to a production environment. Gain practical experience using Amazon SageMaker to deploy trained models to a web application and evaluate the performance of your models. A/B test models and learn how to update the models as you gather more data, an important skill in industry.

This program is intended for students who already have knowledge of machine learning algorithms.

PREREQUISITE KNOWLEDGE

To optimize your chances of success in this program, we recommend intermediate Python programming knowledge and intermediate knowledge of machine learning algorithms.

Software Engineering Fundamentals

In this lesson, you’ll write production-level code and practice object-oriented programming, which you can integrate into machine learning projects.

BUILD A PYTHON PACKAGE

Machine Learning in Production

Learn how to deploy machine learning models to a production environment using Amazon SageMaker.

DEPLOY A SENTIMENT ANALYSIS MODEL

Machine Learning Case Studies

Apply machine learning techniques to solve real-world tasks; explore data and deploy both built-in and custom-made Amazon SageMaker models.

PLAGIARISM DETECTOR

Machine Learning Capstone

In this capstone lesson, you’ll select a machine learning challenge and propose a possible solution.

CAPSTONE PROPOSAL AND PROJECT

Learn with the best

Cezanne Camacho, Mat Leonard, Luis Serrano, Dan Romuald Mbanga, Jennifer Staab, Sean Carrell, Josh Bernhard, Jay Alammar, Andrew Paster

GET STARTED WITH

Machine Learning Engineer


LEARN
• Learn advanced machine learning techniques and algorithms, including deployment to a production environment.

AVERAGE TIME
• On average, successful students take 3 months to complete this program.

BENEFITS INCLUDE
• Real-world projects from industry experts
• Technical mentor support
• Personal career coach & career services

STAY SHARP WHILE STAYING IN
• Financial support available worldwide to help in this challenging time
• Spend your time at home learning new, higher-paying job skills
• Commit to a brighter future by learning today

Why should I enroll?

As more and more companies are looking to build machine learning products, there is a growing demand for engineers who are able to deploy machine learning models to global audiences. In this program, you’ll learn how to create an end-to-end machine learning product. You’ll deploy machine learning models to a production environment, such as a web application, and evaluate and update that model according to performance metrics. This program is designed to give you the advanced skills you need to become a machine learning engineer.

Read more at course page.



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