Introduction to Image Generation with Google Cloud (Udacity)

Offered by Udacity, Google Cloud,
Introduction to Image Generation with Google Cloud (Udacity)

Learn what diffusion models are, how they work, and real use-cases for them. This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space.

Class Deals by MOOC List - Click here and see Udacity's Active Discounts, Deals, and Promo Codes.

Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.

What you will learn
Introduction to Image Generation with Google Cloud

  • How diffusion models work.
  • Real use-cases for diffusion models.
  • Unconditioned diffusion models.
  • Advancements in diffusion models (text-to-image).

Why take this course?
This course will familiarize you with diffusion models, a promising family of machine learning models widely used in image generation. Diffusion models serve as the foundation for numerous cutting-edge image generation models and tools available on Google Cloud. Throughout the course, you will gain a comprehensive understanding of diffusion model theory, along with practical knowledge on training and deploying these models on Vertex AI.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Introduction to Machine Learning (Coursera) Coursera
Duke University

Introduction to Machine Learning (Coursera)

This course will provide you a foundational understanding of machine learning models (logistic regression, multilayer perceptrons, convolutional neural networks, natural language processing, etc.) as well as demonstrate how these models can solve complex problems in a variety of industries, from medical diagnostics to image recognition to text prediction.

Jun 19th 2026
5-12 Weeks
Knowledge-Based AI: Cognitive Systems (Udacity) Udacity
Georgia Institute of Technology,Udacity

Knowledge-Based AI: Cognitive Systems (Udacity)

The Core of Artificial Intelligence. This is a core course in artificial intelligence. It is designed to be a challenging course, involving significant independent work, readings, assignments, and projects. It covers structured knowledge representations, as well as knowledge-based methods of problem solving, planning, decision-making, and learning.

Self Paced
Self-Paced
Using Machine Learning in Trading and Finance (Coursera) Coursera
New York Institute of Finance,Google Cloud

Using Machine Learning in Trading and Finance (Coursera)

This course provides the foundation for developing advanced trading strategies using machine learning techniques. In this course, you’ll review the key components that are common to every trading strategy, no matter how complex. You’ll be introduced to multiple trading strategies including quantitative trading, pairs trading, and momentum trading.

Jun 19th 2026
4 Weeks
Machine Learning: Unsupervised Learning (Udacity) Udacity
Georgia Institute of Technology,Udacity

Machine Learning: Unsupervised Learning (Udacity)

Conversations on Analyzing Data. Ever wonder how Netflix can predict what movies you'll like? Or how Amazon knows what you want to buy before you do? The answer can be found in Unsupervised Learning! Closely related to pattern recognition, Unsupervised Learning is about analyzing data and looking for patterns. It is an extremely powerful tool for identifying structure in data. This course focuses on how you can use Unsupervised Learning approaches -- including randomized optimization, clustering, and feature selection and transformation -- to find structure in unlabeled data.

Self Paced
Self-Paced
Introduction to Machine Learning using Microsoft Azure (Udacity) Udacity
Udacity,Microsoft Azure

Introduction to Machine Learning using Microsoft Azure (Udacity)

Gain a high-level introduction to the field of machine learning and prepare to use Azure Machine Learning Studio to train machine learning models. Plus, learn how to perform a variety of tasks on Azure Machine Learning labs — from data import, transformation and management to training, validating and evaluating models. Access to the Azure Machine Learning Labs will close after a predetermined number of students have completed the course.

Self Paced
Self-Paced
Practical Machine Learning (Coursera) Coursera
Johns Hopkins University

Practical Machine Learning (Coursera)

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates.

Jun 15th 2026
4 Weeks
Segmentation and Clustering (Udacity) Udacity
Udacity

Segmentation and Clustering (Udacity)

Use machine learning to create segments. The Segmentation and Clustering course provides students with the foundational knowledge to build and apply clustering models to develop more sophisticated segmentation in business contexts. In this course, you'll learn how to use an advanced analytical method called clustering to create useful segments for business contexts, whether its stores, customers, geographies, etc. You'll learn this through improving your fluency in Alteryx, a data analytics tool that enables you prepare, blend, and analyze data quickly.

Self Paced
Self-Paced
Introduction to Machine Learning Course (Udacity) Udacity
Udacity

Introduction to Machine Learning Course (Udacity)

This class will teach you the end-to-end process of investigating data through a machine learning lens. Learn online, with Udacity. Machine Learning is a first-class ticket to the most exciting careers in data analysis today. As data sources proliferate along with the computing power to process them, going straight to the data is one of the most straightforward ways to quickly gain insights and make predictions.

Self Paced
Self-Paced
Spark (Udacity) Udacity
Udacity,Insight

Spark (Udacity)

Master how to work with big data and build machine learning models at scale using Spark! In this course, you’ll learn how to use Spark to work with big data and build machine learning models at scale, including how to wrangle and model massive datasets with PySpark, the Python library for interacting with Spark. In the first lesson, you will learn about big data and how Spark fits into the big data ecosystem. In lesson two, you will be practicing processing and cleaning datasets to get comfortable with Spark’s SQL and dataframe APIs. In the third lesson, you will debug and optimize your Spark code when running on a cluster. In lesson four, you will use Spark’s Machine Learning Library to train machine learning models at scale.

Self Paced
Self-Paced
Learn to code with AI (Coursera) Coursera
Scrimba

Learn to code with AI (Coursera)

Imagine waking up tomorrow as a web developer. What would you want to build? With AI tools like ChatGPT, you're already a developer, regardless of your experience, if you know how to work with them. So in this course, you'll build functional, interactive front-end projects while learning how to write effective prompts and debug and refine your code with the help of AI.

Jun 17th 2026
2 Weeks