Master of Science in Applied & Agentic AI

You want to build AI systems, not just use them. This degree teaches you how, from architecture and orchestration to deployment and production at scale. It's the only accredited master's built entirely around Agentic AI, designed specifically for engineers who are working full-time.

Type

Masters
Start Date

September 30, 2026
Duration

13 Months

San Francisco AI Ecosystem

Pathway to a Doctorate

FOUNDING COHORT — SEPTEMBER 2026

Golden Gate University

Master of Science in Applied & Agentic AI

You want to build AI systems, not just use them. This degree teaches you how — from architecture to deployment to production at scale. It's the only accredited master's built entirely around Agentic AI, and it's designed for engineers who are working full-time.

100% Online

30 Credits

13 Months Duration

Flexibility Study While You Work

+92%

Growth in AI Architect job postings, year on year

$37K

Average salary increase over a Senior ML Engineer in the US

4M

Projected AI specialist shortage by 2027

<3%

Of the AI workforce has production agentic AI experience

Why This Degree. Why Now.

The Jobs Are There. The People Who Can Do Them Aren't.

Companies are deploying AI agents in production right now, and demand is outpacing the supply of qualified talent. The skills this degree teaches, designing, deploying, and operating agentic AI systems at scale, are exactly what's missing in today's workforce.

$47.1B Agentic AI Market Size by 2030

That's up from $5.1B in 2024. Enterprise adoption isn't slowing down; it's accelerating every quarter.

Markets & Markets, 2025

68% Enterprises are deploying agentic AI in 2025–26

Salesforce, Microsoft, and Google all launched production-grade agent platforms in 2025. They need engineers who can build and run these systems, not just prompt them.

Gartner CIO Survey 2025

+92% Growth in AI Architect job postings, year on year

Four in ten new AI roles at Fortune 500 companies now specifically ask for LangGraph, AutoGen, or MCP/A2A experience. The job descriptions have changed. The question is whether your resume has, too.

LinkedIn Talent Insights, Q1 2026

127 days Average time to fill an AI Architect role

A software engineer role fills in 45 days. AI Architect roles sit open for nearly five months. That's not a slow hiring market; it's a skills gap.

Levels.fyi / Glassdoor, Q1 2026

4M Projected AI specialist shortage by 2027

The biggest gap isn't in model training or data science. It's in professionals who can take an AI system from prototype to production. That's exactly what this degree teaches.

McKinsey Global Institute, 2025

So we built something better.

Instead of waiting for someone to choose you, you’ll spend 7.5 weeks building work that speaks for itself.

Real Projects

Real Outputs

Real Portfolio

Where You Become an AI Architect

This is a working professional's degree. You'll study online across four terms, applying what you learn directly to the work you're already doing, and graduate with a credential and a portfolio that opens the next door in your career.

32 Units · 13 Months · Online Eleven courses in total: ten courses worth 3 units each and one course worth 2 units, with 30–40 contact hours per term. You don't need to take time off work to do this.

Learn from Faculty Working in AI Right Now Your instructors aren't career academics. They hold current industry roles and have shipped AI systems. What they teach is what they're doing.

Your Units Count Toward a Doctorate If you decide to keep going, your MS AAI units transfer into the DTech in Applied & Agentic AI. You won't have to start over.

AI Isn't a Course Here. It's the Foundation. Every course in this program connects to the agentic stack. It's not a GenAI module added to an existing ML degree; the entire curriculum was built around where AI is heading.

You'll Learn to Run AI in Production Most AI programs stop at building a model. This one goes further, covering LLMOps, evaluation frameworks, security, observability, and what it actually takes to keep an AI system running reliably in the real world.

You'll Graduate With a Portfolio A mini-Perplexity, a Netflix-style AI recommender, Agent Olympics results, and your own industry capstone. You'll graduate with tangible projects and proof of your capabilities, not just a transcript.

Who Should Enroll

Is This the Right Degree for You?

This program is for working technology professionals who want to move into AI engineering, AI architecture, or senior AI leadership. Select the tab that best describes where you are right now.

Making the Move into AI

The Engineer Making the Move into AI

Software Engineer · Solutions Architect · DevOps Engineer

Who You Are

You're a software, solutions, or DevOps engineer with solid technical skills, but no ML background.

What's Holding You Back

You've done the certificates. They didn't move the needle. Employers are filtering by degree level, and the AI roles you're applying for keep going to people with different credentials.

What You're Looking For

A degree you can afford, with a curriculum that aligns with what AI job postings actually ask for.

What You'll Gain

You'll get the accredited degree that clears the hiring screen — and the technical skills to back it up on day one.

You step into VP roles, found advisory boards, or launch independent strategy consulting, backed by both 20+ years of domain experience and a U.S. doctoral credential.

Advancing Beyond ML Engineering

The ML Engineer Ready to Level Up

Senior ML Engineer · Senior Data Engineer · Senior Data Scientist

Who You Are

You're a senior ML engineer, data engineer, or data scientist with solid classical ML skills.

What's Holding You Back

Your current skills are strong, but they're becoming table stakes. AI Architect and Lead AI Engineer roles now require agent orchestration, evaluation frameworks, and LLMOps experience.

What You're Looking For

Real depth. You'll check the syllabus carefully before you commit. You want to see LangGraph, RAG, eval frameworks, and LLMOps, not a survey of AI buzzwords.

What You'll Gain

You'll go from ML practitioner to AI Architect, with a curriculum that covers exactly what today's job descriptions are asking for.

Here's what Course 7 alone covers: MCP, A2A protocols, LangGraph, multi-agent orchestration, and non-deterministic testing. That's one course. There are nine others, and they go just as deep. If the role you want lists these skills, this is the degree that teaches them.

Leading AI at the Senior Level

The Senior Leader Building Technical Authority

Technical PM · IT Manager · Analytics Manager · Consulting Manager

Who You Are

You're a technical PM, IT manager, analytics manager, or consulting manager with 8–15 years of experience.

What's Holding You Back

Peers with AI credentials are getting promoted into roles you've been working toward. When an AI vendor presents a proposal, you can't challenge it on technical grounds. That's the gap this degree closes.

What You're Looking For

A credible, accredited degree from a recognized university, one that signals you can lead AI at the VP level.

What You'll Gain

You'll build the technical depth to lead AI strategy and compete for VP and Director roles on your own terms.

WASC-accredited. WES-recognized. A cohort of senior AI engineers. This program won't turn you into a researcher. It'll give you the technical grounding to evaluate AI proposals, lead architecture decisions, and walk into VP-level interviews with something concrete to say.

*GGU is WASC accredited, but check with your university to confirm that the credits can be transferred into your program.

About the Domains

Finance

Turn data into decisions that actually move money.

Instead of just learning theory, you’ll build AI agents that can analyze markets, track financial trends, and generate insights in real time. Think: automating equity research, building portfolio trackers, or creating tools that simulate investment strategies.

By the end, you’ll have projects that show you understand how finance works and how to use AI to make smarter, faster decisions—something most candidates can’t demonstrate.

Walk into finance interviews with proof that you can go beyond Excel and actually build intelligent systems.

Marketing

Go from “ideas” to campaigns that perform.

You’ll learn how to use Agentic AI to research audiences, generate high-converting content, and optimize campaigns automatically. Build tools that can analyze competitors, run A/B tests, and refine messaging without constant manual effort.

Instead of saying you “like marketing,” you’ll show how you can drive growth using AI—something every brand is actively looking for right now.

Your portfolio won’t just have mock campaigns—it’ll have systems that think, test, and improve on their own.

Analytics / Consulting

Solve real business problems with data + AI.

This is where structured thinking meets execution. You’ll build AI agents that can clean data, generate insights, and even recommend business strategies.

Think: automating client reports, building dashboards that explain why something is happening, or creating tools that simulate business decisions.

You won’t just learn frameworks—you’ll apply them to real-world scenarios and show that you can break down messy problems and turn them into clear, actionable outcomes.

That’s exactly what consulting firms look for—but rarely see in fresh candidates.

Product / Project Management

Learn how to build, ship, and scale smarter.

You’ll use Agentic AI to plan products, prioritize features, automate workflows, and manage execution. From writing PRDs to building AI-powered prototypes, you’ll understand what it actually takes to take an idea from zero to launch.

Instead of just talking about “leadership” or “coordination,” you’ll show how you can use AI to move faster, make better decisions, and manage complexity.

By the end, you'll have completed real projects - not just case studies - which is what recruiters care about most.

HOW IT WORKS

Designed for your summer

Program Proposal, Teaching Plan, and Credit Hour Justification. Select one of the four tracks that aligns with your interests and career goals.

7.5 Weeks

Live Online

3 Semester Credits

4 Professional Tracks

Turn data into decisions that drive real financial impact by building AI agents for market analysis, trend tracking, and real-time insights. Create tools like equity research automation, portfolio trackers, and investment simulators.

Prove you understand finance with AI-driven projects and walk into interviews with real systems—not just Excel skills.

Agents automate market monitoring, earnings analysis, SEC filing extraction, and investment memo drafting, with a portfolio that mirrors tools used at Goldman Sachs, JPMorgan, and Schroders.

Week 1: Agent Architecture - How AI agents work, how to give them good instructions, and responsible use (agent architecture, prompt engineering, ethics)
Week 2: RAG + Tool Use - Connecting agents to documents and data sources, and measuring whether they work (tool use, RAG, APIs, evaluation)
Week 3: Market Monitoring Agent - Your industry’s data sources; build your first domain-specific AI tool
Week 4: Earnings Transcript Analyzer - Connecting multiple agents into a single workflow for your domain
Week 5: 10-K Summarizer + Extraction - Advanced builds + mid-course peer review across tracks
Week 6: Investment Memo + Stress-Test - Breaking your own agent: finding what fails and documenting why. Structured “break your own agent” stress-test with adversarial inputs before documenting failures. This week also covers SEC disclosure compliance and fiduciary duty considerations for AI-generated investment content.
Week 7: Deploy + Present - Publishing your portfolio and preparing your walkthrough
Week 8: Capstone - Final presentations, peer feedback, and program wrap-up

Go from “ideas” to campaigns that perform using Agentic AI to research audiences, create high-converting content, and optimize campaigns automatically. Build tools for competitor analysis, A/B testing, and messaging refinement.

Prove you can drive growth with AI through a portfolio of systems that test, learn, and improve—not just mock campaigns.

Agents automate SEO research, ad copy, reporting, and email sequences, aligned with the AMA 2025 Competency Model. 84% of campaign setup tasks may be automated by 2026.

Week 1: Agent Architecture - How AI agents work, how to give them good instructions, and responsible use (agent architecture, prompt engineering, ethics)
Week 2: RAG + Tool Use - Connecting agents to documents and data sources, and measuring whether they work (tool use, RAG, APIs, evaluation)
Week 3: SEO Brief + Keyword Agent - Your industry’s data sources; build your first domain-specific AI tool
Week 4: Ad Copy + A/B Variants - Connecting multiple agents into a single workflow for your domain
Week 5: Campaign Performance Agent - Advanced builds + mid-course peer review across tracks
Week 6: Email Sequence + Stress-Test - Breaking your own agent: finding what fails and documenting why. Stress-test, including FTC advertising disclosure, brand safety, and data privacy considerations for AI-generated campaigns.
Week 7: Deploy + Present - Publishing your portfolio and preparing your walkthrough
Week 8: Capstone - Final presentations, peer feedback, and program wrap-up

Solve real business problems with data + AI by building AI agents that clean data, generate insights, and recommend strategies. Create tools for automated reports, insightful dashboards, and business simulations.

Apply structured thinking to real scenarios and show you can turn messy problems into clear, actionable outcomes—a key skill consulting firms look for.

Agents replicate SQL retrieval, data cleaning, predictive insight interpretation, and slide generation, aligned with CRISP-DM and McKinsey BA workflows.

Week 1: Agent Architecture - How AI agents work, how to give them good instructions, and responsible use (agent architecture, prompt engineering, ethics)
Week 2: RAG + Tool Use - Connecting agents to documents and data sources, and measuring whether they work (tool use, RAG, APIs, evaluation)
Week 3: Ask-Your-Database Agent - Your industry’s data sources; build your first domain-specific AI tool
Week 4: Data Cleanup + Insight Narrative - Connecting multiple agents into a single workflow for your domain
Week 5: Predictive Insight Agent - Advanced builds + mid-course peer review across tracks
Week 6: Slide Deck + Stress-Test - Breaking your own agent: finding what fails and documenting why. Stress-test, including model fairness, bias auditing, and data governance for AI-generated insights.
Week 7: Deploy + Present - Publishing your portfolio and preparing your walkthrough
Week 8: Capstone - Final presentations, peer feedback, and program wrap-up

Learn to build, ship, and scale smarter using Agentic AI to plan products, prioritize features, and automate execution. From PRDs to AI-powered prototypes, take ideas from zero to launch.

Show how you drive decisions, speed, and execution with AI—not just talk about leadership. Graduate with real projects, not just case studies.

Agents streamline user research synthesis, PRD generation, competitive intelligence, and metrics definition, aligned with Reforge PM foundations and Lenny Rachitsky’s hiring framework.

Week 1: Agent Architecture - How AI agents work, how to give them good instructions, and responsible use (agent architecture, prompt engineering, ethics)
Week 2: RAG + Tool Use - Connecting agents to documents and data sources, and measuring whether they work (tool use, RAG, APIs, evaluation)
Week 3: User Research Synthesizer - Your industry’s data sources; build your first domain-specific AI tool
Week 4: PRD + User Story Generator - Connecting multiple agents into a single workflow for your domain
Week 5: Competitive Intelligence Agent - Advanced builds + mid-course peer review across tracks
Week 6: Metrics/OKR + Stress-Test - Breaking your own agent: finding what fails and documenting why. Stress-test, including user research ethics, consent frameworks, and responsible AI design considerations.
Week 7: Deploy + Present - Publishing your portfolio and preparing your walkthrough
Week 8: Capstone - Final presentations, peer feedback, and program wrap-up

Curriculum

10 Courses. All of Them Built Around Agentic AI.

Each course builds on the last. You'll start with the foundations and work your way through to production, evaluation, deployment, security, and scale.

32 Units

The Journey From Prototype to Production

Design → Build → Evaluate → Operate → Scale

These are the five things AI Architects can do that ML Engineers typically can't. Every course in this program maps to one or more of them.

Design
Make the right architectural call

You'll learn to take a business problem and decide whether it needs prompting, RAG, fine-tuning, or a full agentic system, based on cost, speed, and reliability, not what's trending.

Build
Ship production-grade AI end to end

You'll build predictive ML, LLM/RAG, and multi-agent systems from scratch, including the data layer underneath: pipelines, vector retrieval, knowledge structures, and agent memory.

Evaluate
Test before you deploy

You'll design evaluation frameworks for models, RAG systems, and agents, including automated approaches like LLM-as-judge. Evaluation is what stops hallucinations, regressions, and expensive production failures.

Operate
Keep it running reliably

You'll cover MLOps and LLMOps, observability, incident response, cost management, prompt injection prevention, and what it takes to keep an AI system secure and compliant over time.

Scale
From one user to millions

You'll learn to architect systems that hold up as traffic, data, and usage grow, including distributed infrastructure, scalable serving, and capacity planning that keeps costs predictable.

Your Portfolio & Proof of Skill

Graduate With Work You Can Show, Not Just Grades

Employers in AI want to see what you've built. Every student leaves with a portfolio of real projects, not assignments, but systems you designed, built, and can talk through in an interview.

An AI Portfolio Based on Real Products

You'll build a mini-Perplexity, a Netflix-style recommendation engine, and an agentic coding assistant — modeled on real systems at industry-leading companies. Real code, real architecture decisions, real trade-offs.

Agent Olympics

A recurring competition where your agents go up against your classmates' across real challenges — research speed, accuracy, planning, coding, and multi-agent collaboration. Results are public, which means your performance is verifiable.

Your Own Capstone Project

You pick the industry, the problem, and the context. Your capstone is publicly defended — so when you interview, you're not describing a class project. You're walking through a system you designed for your own career.

AI Business Creation Track

A masterclass series and startup guide for students who want to launch something. If you're going to build AI systems, the most direct proof is shipping one to market.

Annual Technology Symposium

Five days in Singapore or San Francisco. You'll present your capstone in front of industry practitioners, attend fireside chats and industry tours, and spend time with your cohort in person. It's where the network becomes real.

A Global Peer Network

Your cohort includes AI professionals from 70+ countries. You'll study together in weekly learning pods throughout the program — and stay connected through the alumni network well after graduation.

Your Cohort & Alumni Network
You Won't Be Studying Alone

The program is cohort-based. You'll study alongside a group of engineers and leaders at similar career stages, meet weekly in learning pods, and stay connected through the alumni network long after you graduate.

70+

Countries represented in the AI pioneer community

5 Days

Annual Golden Gate Technology Symposium duration

Weekly

Cohort learning pods with peers at the same career stage

Founding Alumni Program

If you enroll in Cohort 1, you'll graduate as a Founding Alumni, with a named distinction, early access to the faculty network, and a priority speaking slot at the annual Symposium. Being in the first cohort of a brand-new credential carries weight that later cohorts simply can't claim.

Annual Golden Gate Technology Symposium

Five days in Singapore or San Francisco. You'll present your capstone in front of people who work in AI, not just academics. It's also when your cohort comes together in person for the first time.

• Industry-specific capstone presentations
• Fireside chats with AI practitioners and investors
• Industry tours - AI labs, cloud providers, startups
• City program - Singapore or San Francisco
• Alumni network meetup - 70+ countries represented

TUITION FEE
Program Tuition
$768 USD/month after merit scholarship
Pay as You Progress
$768/month
30 equal monthly installments • no interest
Upfront Payment
$20,727
One-time • up to 10% additional fee waiver
Most candidates receive a merit scholarship on the $65,800 program fee — you'll know your exact amount before you commit. Less than one year's tuition at a traditional MBA, for a terminal doctoral degree.

Accreditation & Recognition

Your Degree Is Recognized Globally

Before you look at curriculum or tuition, it's worth knowing your degree will hold up, with employers, immigration authorities, and licensing bodies, wherever you're building your career.

WASC / WSCUC Accredited

Golden Gate University has been regionally accredited by WASC since 1959, the same body that accredits Stanford, UC Berkeley, and USC. This affects how employers verify your degree, how your units transfer, and your academic standing for visa and immigration purposes.

WES Recognized Globally

WES recognition means your degree can be evaluated for employment, immigration, professional licensing, and further study in Canada, the GCC, Southeast Asia, APAC, and Africa. If you're planning a career that crosses borders, this matters.

Based in San Francisco

Golden Gate University is located at the center of the global AI industry, close to the startups, cloud companies, and practitioners who are actually building what you'll learn to build. That proximity shapes who teaches here.

Faculty Working in AI Today

Every instructor is named and has a current role in the industry. Their faculty profiles are published on the program website, so you can check exactly what they've built before you enroll.

How to Apply?

There are 4 simple steps in the Admission Process which are detailed below: