Required Courses: 53 - Agentic AI 56 - Generative AI 52 - AI Programming with Python 43 - Data Analyst 61 - Deep Learning 49 - Introduction to Machine Learning with Pytorch 64 - Statistics for Data Analysis

378 hours

Earn up to 33% of your degree credits from your experience Don’t start from scratch. Your professional and learning history can earn you credits needed to graduate.

58 elective courses 378

Artifical Intelligence Machine Learning DevOps Engineer AI Engineer using Microsoft Azure Azure Generative AI Engineer Agentic AI Engineer with LangChain and LangGraph Machine Learning Engineer with Microsoft Azure

Data Architect (73) Data Engineering with Microsoft Azure (56)

Full Stack Javascript Developer (70) Backend Developer with Python Front End Web Developer (39) Intermediate Python (35) React (39) Data Structures and Algorithms (47) Intermediate Javascript (41)

Cloud Developer using Microsoft Azure (51) Cloud DevOps Engineer

Introduction to Cybersecurity (69)

GitHub Copilot with JavaScript (6) https://www.udacity.com/course/github-copilot-with-javascript--cd15089

AWS Certified Solutions Architect - Associate

I would like to know more about the AI masters. I've asked UdaBot about the credit hours and discovered that tier 1 has 750 credit hours of foundation courses. The website list 7 courses, what are the remaining foundation courses for tier 1? And for the capstone project, are there requirements for the topic? Does it have to involve AI or can it be a programming project? Lastly, will you be adding more courses?

The Master’s degree in Artificial Intelligence is organized into three tiers, each consisting of 750 hours of learning, totaling 2250 hours. Here's how the program is structured: Tier 1: Foundational courses, which are mandatory for completing the full Master’s degree. Tier 2: Elective or specialization courses, allowing you to tailor your learning path. Tier 3: Capstone or project-based courses, designed to apply your knowledge in practical scenarios.

Hi,

I'm very eager to get started. Thank you for your response and screen recording. In the screen recording, the Foundational/Core courses totaled 378 credit hours.So would I select 1500 - 378 = 1122 credit hours worth of elective courses? 1500 is from Tier 1 + Tier 2 credit hours.

On the AI master website, I read the following: Earn up to 33% of your degree credits from your experience Don't start from scratch. Your professional and learning history can earn you credits needed to graduate. I have 20 years of software development experience. Would I be able to use that towards credit hours? Do I get 750 credit hours credit after proof of employment or would I have to challenge the courses? In other words, how does the degree credits work from my experience?

Thanks, Jebb

For the capstone project, it becomes available after you complete Tier 1 and Tier 2. The Capstone project enables students to apply their learning to solve a technically challenging real-world problem. It is at the same time an academic project in which the student’s work is thoroughly documented in a technical report.

For example, if you are receiving a specialization in AI, your project should clearly describe the AI models, datasets, experimental results, evaluation metrics, and ethical considerations. It emphasizes hands-on experience across the entire software development lifecycle, from requirement analysis to deployment and maintenance, and forms part of your professional portfolio that will showcase the knowledge, skills, and competencies you have developed. The course culminates in a presentation that you will have to submit at the end. You would get more details about capstone projects and requirements as you progress in the program later on.