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
Udacity current price ( USD)
Reseller price (USD)
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.
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.
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.
- 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)
- Build a Python Package
- Deploy a Sentiment Analysis Model
- Plagiarism Detector
- Machine Learning Capstone
Resources (blog posts, other)
- Lectures 0
- Quizzes 0
- Duration 3 months
- Skill level All levels
- Language English
- Students 27
- Assessments Yes