Machine Learning Engineer

Teacher

admin

Level

Intermediate

Prerequisites

Intermediate Python programming knowledge, including:

At least 40 hours of programming experience
Familiarity with data structures like dictionaries and lists
Experience with libraries like NumPy and pandas
Supervised learning models, such as linear regression
Unsupervised models, such as k-means clustering
Deep learning models, such as neural networks

Course Duration

3 months

Udacity current price ( USD)

1017

Reseller price (USD)

775

Career Focus

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. The Intro to Machine Learning program is for students with Python experience, and covers foundational machine learning algorithms. The Machine Learning Engineer program is for students with some ML background, and covers production and deployment.

Target Audience

Machine learning is changing countless industries, from health care to finance to market predictions. Currently, the demand for machine learning engineers far exceeds the supply. In this program, you’ll apply machine learning techniques to a variety of real-world tasks, such as customer segmentation and image classification. This program is designed to teach you foundational machine learning skills that data scientists and machine learning engineers use day-to-day.

The Intro to Machine Learning program is for students with Python experience, and covers foundational machine learning algorithms. The Machine Learning Engineer program is for students with some ML background, and covers production and deployment.

General Curriculum)

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.
In LinkedIn’s 2020 Emerging Jobs report, AI Specialist, a role that includes machine learning, deep learning, TensorFlow, and Python as key skills, boasts 74% annual growth. All of the above skills are incorporated into Udacity’s Intro to Machine Learning with PyTorch Nanodegree program, which is a great way to get introduced to the fundamentals of machine learning, including areas like manipulating data, supervised & unsupervised learning, and deep learning. In this program, you will complete three hands-on projects including building an image classifier, and creating customer segments, that will prepare you for one of the 50,000 open roles in machine learning.

Tools

What They Need: Need a computer on which all of these programs can be installed, need an AWS account (we provide $100 in credit for this, they have to enter their credit card when they set up their account)
What They Use/Learn: Python, PyTorch (library in Python), Jupyter Notebook, NumPy, Anaconda, Pandas, Amazon SageMaker (online tool)