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Udacity

Master of Science in Artificial Intelligence

via Udacity

Overview

Earn an accredited AI degree—built on real projects, flexible to your schedule and designed with your career goals in mind.

The Udacity Institute of AI and Technology, a member college of Woolf, offers a pathway to a Master of Science in Artificial Intelligence. Students complete Udacity's hands-on, project-based curriculum while earning ECTS credits. Degrees are awarded by Woolf, a global collegiate Higher Education Institution recognized in 60+ countries.

The degree consists of 2,250 credit hours: seven required core modules (875 hours) covering the most in-demand topics in AI, from AI programming with Python to agentic AI; 625 hours of electives chosen from a large selection of Nanodegree programs; and a 750-hour, seven-project capstone. Most learners finish in 18–24 months, studying 100% online with mentor support. Up to 30% of the degree can be exempted through recognition of prior learning.

Prerequisites

  • Bachelor's degree (recommended) or equivalent experience
  • Foundational programming knowledge (Python recommended)
  • Basic math and statistics background
  • English proficiency
  • Udacity monthly subscription (required for application)
  • At least 18 years old at enrollment

Getting started requires a one-time $199 enrollment fee and a Udacity subscription.

Syllabus

Core Modules (875 hours, required)

  • Introduction to Artificial Intelligence (125 hours)
  • Intelligent Systems (125 hours)
  • Introduction to Machine Learning (125 hours)
  • Introduction to Deep Learning (125 hours)
  • Introduction to Computer Programming: Part 1 (125 hours)
  • Applied Data Analytics (125 hours)
  • Ethical Artificial Intelligence Practices (125 hours)

Elective Modules (625 hours)

  • Choose from a large selection of electives and complete 625 unique credit hours in the areas that interest you most.

Capstone (750 hours)

  • Complete a seven-project, industry-style AI capstone where you design, build, and justify real AI systems - from ML models to generative and agentic AI.

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