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We’re working with Amazon Web Services (AWS) and their AWS Educate program to teach you how to deploy machine learning models using Amazon SageMaker.  

Over the past few years, the demand for machine learning specialists and engineers has soared, with machine learning engineers and specialists ranking amongst the top emerging jobs on LinkedIn. Recently, machine learning has been adopted by a wide range of industries, including medical diagnostic companies, finance firms, and more. Udacity’s Intro to Machine Learning Nanodegree program and Machine Learning Engineer Nanodegree program were built in response to this demand to provide access to this growing tech field.

We’ve seen advances in research and industry practices as more companies look to build machine learning products. Specifically, there is a growing demand for engineers who are able to deploy machine learning models to a global audience. Deployment means making a model available for use in a piece of hardware or web application, such as a voice assistant or recommendation engine. Knowing how to build machine learning models is a great starting point, but to truly make an impact at scale, a data scientist or programmer needs to know the techniques and tools to deploy that model so that it’s highly accessible.

To keep up with this advancement and bring the best educational experience to our students, we are updating the Machine Learning Engineer Nanodegree program to include the latest skills by adding two new projects focused on deployment skills.

This is the right time to learn these AI deployment skills because they are in high demand by employers across all industries.

“We’re very excited to continue to work with Udacity to put machine learning in the hands of even more developers and data scientists,” said Dr. Matt Wood, General Manager of Artificial Intelligence at AWS. “Machine learning skills are among the most sought after by organizations in virtually every industry, and through this new Nanodegree program , AWS Educate, and services such as Amazon SageMaker, anyone can start to learn and apply this technology for the first time.”

I’m excited to tell you more about our program and recent additions!

Intro to Machine Learning Nanodegree Program

Before getting into advanced deployment content, the Intro to Machine Learning Nanodegree program teaches you the theory behind foundational machine learning algorithms, such as k-means clustering, logistic regression, and neural networks. Designed for anyone with some Python programming and basic statistics knowledge, this Nanodegree program will teach you to apply your knowledge and complete practical coding exercised in Python. Additionally, you will utilize libraries like Scikit-Learn and PyTorch that are common in research and industry. This program will equip you with the machine learning skills to enroll in the Machine Learning Engineer Nanodegree program, where we’ll introduce you to our new deployment content!

Collaborating with AWS

We’ve collaborated with AWS Educate and experts on the Amazon SageMaker team to create  new deployment content for the Machine Learning Engineer Nanodegree program. AWS Educate provides Udacity students access to AWS content and AWS Promotional Credits. These benefits will allow students to use Amazon SageMaker for assignments developed in tandem with AWS Subject Matter Experts (SMEs). The opportunity to work with industry experts at AWS enables us to provide you with the most relevant deployment technologies. We’ve added content that examines a variety of machine learning models as they are applied at-scale to real-world tasks. You’ll learn how to deploy both unsupervised and supervised algorithms and apply them to tasks such as feature engineering and time series forecasting. This content addresses questions such as:

  1. How do you decide on the correct machine learning model for a given task?
  2. How can you use cloud deployment tools such as Amazon SageMaker to work with data and improve your machine learning models?
Machine learning model example with Amazon SageMaker improving data modeling

Model Deployment and Serving

In addition to learning about model deployment, you’ll also learn about model serving and updating. We’ve added content that shows you how to connect a deployed sentiment analysis model to a website through an API using AWS. After deploying the model, you’ll update the model to account for changes in the underlying text data – an especially valuable skill in industries that continuously collect data. By the end of this section, you should have the skills you need to train and deploy models to solve tasks of your own design!

Project Highlights

1. Deploying a Sentiment Analysis Model

In this project, you’ll work with a dataset of movie reviews and identify reviews as having either a positive or negative sentiment. You’ll explore this data and train your own sentiment analysis model using the deep learning framework PyTorch. Then, you’ll deploy the model and create a gateway for accessing it from a website using AWS resources.

2. Deploying a Plagiarism Detector

In this project, you’ll use your machine learning skills to compare text files, extract text features, and identify similarities between files. Considering different design decisions and metrics for success, you’ll train and deploy a plagiarism detection model. This is a great portfolio project to show to employers to demonstrate your proficiency as a machine learning engineer.

Both the Intro to Machine Learning and Machine Learning Engineer Nanodegree programs are part of Udacity’s School of AI, a set of free courses and Nanodegree programs designed by and for software developers. Our catalog covers a range of topics such as linear algebra and calculus, foundational machine learning models, and state-of-the-art deep learning. You’ll also be able to gain skills in domains such as computer vision, natural language processing, and deep reinforcement learning.

If you’re new to machine learning, we recommend our Intro to Machine Learning Nanodegree program so you can learn foundational machine learning algorithms such as data cleaning and supervised models.

If you already have machine learning skills, our updated Machine Learning Engineer Nanodegree program focuses on teaching you the latest in machine learning deployment technologies, and we’re excited for you to get started.

Enroll today to get practical experience deploying machine learning models at scale.

Cezanne Camacho
Cezanne Camacho
Cezanne is a Udacity Curriculum Lead. She is an expert in computer vision with a Masters in Electrical Engineering from Stanford University. As a former researcher in genomics and biomedical imaging, she has applied computer vision and deep learning to medical diagnostic applications.