Udacity

AI Fundamentals (Udacity)

Offered by Udacity, Microsoft Azure,
AI Fundamentals (Udacity)

Learn the AI skills top companies are looking for. This course is an entry point into the world of AI using Microsoft's cloud-based solutions, such as Azure Machine Learning and Azure Cognitive Services. You will have the chance to learn and experience firsthand how to train and deliver machine learning models and use Azure Cognitive Services for typical AI workloads such as Computer Vision, Natural Language Processing and Conversational AI.

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

AI is a growing field and as more companies are adopting these strategies, the skills gap widens and job openings skyrocket. With Udacity, you will learn the basics of AI without needing any background knowledge in AI or machine learning. This course can be a stepping stone to further AI training and a high-paying career.

What you will learn

Introduction to AI Fundamentals with Azure

  • Meet your instructors, get an overview of the course, check out the prerequisites and get an introduction to the development of AI and ML.

AI and ML Core Concepts

  • Review the key terms and concepts related to artificial intelligence and machine learning, including responsible AI and responsible ML.

Machine Learning

  • Train and evaluate models using Azure Machine Learning, using its automated machine learning capabilities as well as the Azure Machine Learning designer.

Computer Vision

  • Use Azure Cognitive Services to handle key workloads in computer vision: object detection, image classification, face detection, text analysis and processing forms.

Natural Language Processing

  • Analyze text and speech for intent and translate text and speech between languages.

Conversational AI

  • Create a knowledge base in question-and-answer format and create a bot based off of that knowledge base.

Prerequisites and requirements
No prior experience with ML or AI is required, but a student taking this course should already:

  • Be familiar with basic concepts of linear algebra, probability and statistics
  • Be familiar with basic Python
  • Have experience setting up Azure compute resources (recommended but not required)
  • Understand basic programming skills, such as writing conditional and loop statements in any language, preferably Python
  • Have basic statistics knowledge, such as calculating standard deviation and using linear regression methods
  • Have basic knowledge of machine learning (recommended but not required)
Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Spark (Udacity) Udacity
Udacity,Insight

Spark (Udacity)

Data Science

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
Python Debugging Machine Learning
Details
Azure Infrastructure Fundamentals (Coursera) Coursera
LearnQuest

Azure Infrastructure Fundamentals (Coursera)

Security & Networking

Microsoft Azure is a service created by Microsoft to provide cloud computing for creating and managing applications and services using a cloud environment. Azure provides software as a service (SaaS), platform as a service (PaaS) and infrastructure as a service (IaaS). The platform supports many programming languages and frameworks and can be used alone or in a multi-vendor cloud environment.

Nov 9th 2026
5-12 Weeks
SaaS Cloud Computing Microsoft Azure
Details
Machine Learning Interview Preparation (Udacity) Udacity
Udacity

Machine Learning Interview Preparation (Udacity)

Personal and Professional Development Data Science

Prove your qualifications in your machine learning interviews. In this course, you’ll learn exactly what to expect during a machine learning interview. You’ll cover all the common questions and technical strategies, and review a range of important topics, from machine learning algorithms to image categorization. You’ll also learn best practices for data structure questions and whiteboard problems, and at the end of the course, you’ll get unlimited access to mock interviews on Pramp.

Self Paced
Self-Paced
Machine Learning Career Interview
Details
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera) Coursera
DeepLearning.AI

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)

CS: Software Engineering Computer Science

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Nov 9th 2026
4 Weeks
Artificial Intelligence Machine Learning Neural Networks
Details
Segmentation and Clustering (Udacity) Udacity
Udacity

Segmentation and Clustering (Udacity)

Statistics & Data Analysis Data Science

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
Machine Learning Clustering Segmentation
Details
Machine Learning: Unsupervised Learning (Udacity) Udacity
Georgia Institute of Technology,Udacity

Machine Learning: Unsupervised Learning (Udacity)

Robotics & Computer Vision

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
Machine Learning Clustering Information Theory
Details
Introduction to Generative AI with Google Cloud (Udacity) Udacity
Udacity,Google Cloud

Introduction to Generative AI with Google Cloud (Udacity)

Robotics & Computer Vision

Learn what Generative AI is, how it is used, and how it differs from traditional machine learning methods. This is an introductory level course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps. This course is estimated to take less than an hour to complete.

Self Paced
Self-Paced
Artificial Intelligence Machine Learning AI
Details
Encoder-Decoder Architecture with Google Cloud (Udacity) Udacity
Udacity,Google Cloud

Encoder-Decoder Architecture with Google Cloud (Udacity)

Robotics & Computer Vision

Learn about the main components of the encoder-decoder architecture and how to train and serve these models. This course gives you a synopsis of the encoder-decoder architecture, which is a powerful and prevalent machine learning architecture for sequence-to-sequence tasks such as machine translation, text summarization, and question answering.

Self Paced
Self-Paced
Artificial Intelligence Machine Learning AI
Details
Create Image Captioning Models with Google Cloud (Udacity) Udacity
Udacity,Google Cloud

Create Image Captioning Models with Google Cloud (Udacity)

Robotics & Computer Vision

Learn how to create, train, and evaluate an image captioning model by using deep learning. This course teaches you how to create an image captioning model by using deep learning. You learn about the different components of an image captioning model, such as the encoder and decoder, and how to train and evaluate your model.

Self Paced
Self-Paced
Artificial Intelligence AI Deep Learning
Details