Professional studies · Digital Engineering certificate · SCHEV-certified

Software Engineering

Build software with AI as your pair, and prove everything you ship. Two AI tracks, one shared foundation, a capstone in your own field, and a named instructor. Self-paced milestones with live classes every week.

Start your applicationSee the path ↓
2 tracksAI Software Developer · AI QA Engineer
284 hoursDigital Engineering certificate
1st of every monthNew groups start
Your paceFaster with experience and time per week

Audience

Who this program is for

Designed for two groups of learners. Same path, same certificate; your experience sets your pace.

Working professionals staying competitive in the AI era

Testers, analysts, developers and coordinators whose job is changing under them. Add the AI skills teams now expect, on your schedule.

  • Live classes on evening and weekend schedules, recorded if you miss one
  • Leave with a deployed project, automated tests in CI, and a defended capstone

Starting a career in tech

Career changers, recent graduates and students. No technical background assumed: every topic is taught concepts first, with AI doing the typing and you doing the verifying.

  • Your first project ships in the first milestone; your capstone is built in an industry you already know
  • Roles you qualify for: QA Analyst, QA Engineer, Web Developer

The program

The path to your certificate

Stage 1Shared foundation4 milestones · 96 hours
Stage 2Engineering core5 milestones · 140 hours
Stage 3Your track1 milestone · 20 hours
Stage 4Capstone28 hours, defended to a panel
How long it takes is up to you. You complete every milestone; how quickly depends on your experience, what you already know, and the hours you put in each week.

How you'll learn

Learn it, practice it, prove it, move on

1

Learn

Self-paced modules: short recorded lessons and hands-on labs.

2

Practice

Real deliverables in your own field, reviewed by your instructor.

3

Prove it

A proctored exam or a rubric-graded project. Three attempts included, no retake fees.

4

Move on

Pass, and the next milestone unlocks. The capstone closes the program.

Named instructor of recordLive classes every week, recordedOffice hours by topicProgress check every two weeks

How it works →

Your path

Choose a track, see every milestone

Both tracks share the foundation and the core. Your track shapes your specialization milestone and your capstone. You declare it in the second milestone.

Not sure? Take the short career quiz →

AI Software Developer

For builders: career changers who want to make things, and developers who want an AI-first workflow with real engineering discipline.

You'll learn to

  • Turn a one-page spec into working software with AI as your pair
  • Read, verify and correct AI-generated code
  • Ship to a real URL, add one AI feature, test it all in CI

Your capstone

A live site or app in your own field, deployed, with one AI feature you evaluated, automated tests in a green CI run, and a recorded defense.

Roles you qualify for

Software DeveloperWeb DeveloperFront-End Developer

Stage 1 · Shared foundation 4 milestones

Milestone 1 · Shared foundation · F1How Software Gets BuiltHow the internet, the SDLC and delivery methods work, where AI sits in every phase, and your first live page.

What you'll learn

  • How the internet, cloud and applications actually work, and the SDLC from requirements to release
  • Agile, Waterfall and hybrid: when and why, and where AI now sits in each phase
  • The AI work loop, hands-on: frame, give context, prompt, verify, own, with one confident wrong answer you must catch

What you'll build

  • Your first ship: a one-page site prompted into existence with an AI assistant and published live from your GitHub repo
Milestone 2 · Shared foundation · F2Roles & the AI-Augmented TeamWho does what on a software team, how AI changes each seat without removing it, and the six tracks. You declare your track and passion domain here.

What you'll learn

  • Product owner, project manager, developer, QA, and the lenses around the build
  • The AI-augmented team: same roles, more output per person; the 2026 career landscape
  • How large language models actually work: tokens, context, why they are confidently wrong

What you'll build

  • A one-page role reflection plus your declared track and passion domain, the field every project from here to the capstone can live in
Milestone 3 · Shared foundation · F3Requirements CraftElicitation, user stories with testable acceptance criteria, feature mapping, and catching what AI gets wrong in a requirements draft.

What you'll learn

  • Elicitation: interviews, workshops, observation, on a scripted client with planted ambiguities
  • User stories and acceptance criteria specific enough that a test could be generated from them
  • AI-drafted requirements, and how to catch what the AI invented

What you'll build

  • Five polished user stories with acceptance criteria for a product in your passion domain, entered in Jira
Milestone 4 · Shared foundation · F4Agile in PracticeCeremonies, backlog grooming, estimation, PI planning, a recorded sprint simulation, responsible AI use at work, and your Passion Pitch in role.

What you'll learn

  • Sprint ceremonies, backlog grooming, prioritization and estimation
  • PI planning: how large organizations plan quarters
  • Responsible AI use at work: what never goes into an AI tool, disclosing AI use, verifying before trusting

What you'll build

  • A groomed Jira board with a sprint created, your personal AI-use policy, and a recorded readout delivered in your track role

Stage 2 · Engineering core 5 milestones

Milestone 5 · Engineering core · E1Testing Fundamentals & the Test CycleWhy testing exists, test types and design, the defect lifecycle in Jira, a full cycle on a demo app, writing test intent for AI to expand, and API testing basics.

What you'll learn

  • Test types from milestone to UAT, test design techniques, Given/When/Then, and the defect lifecycle
  • Test intent vs. test steps: write the intent, let AI generate the cases, judge them against the requirement
  • API testing basics with Postman: send a request, assert status and body, save a collection

What you'll build

  • An executed test cycle on the demo app: 20 cases run, defects logged with reproduction steps, a summary report, and your first API collection
Milestone 6 · Engineering core · E2SQL for Backend ValidationSQL in a testing context: does the database agree with what the UI claims? Queries are AI-drafted and hand-verified against a number you already know.

What you'll learn

  • SELECT, WHERE, ORDER BY, aggregates, and joins in a testing context
  • "UI says X, does the database agree?" validation patterns
  • AI-assisted query writing, verified against a row count or value you already know

What you'll build

  • Ten queries proving or disproving stated UI behavior against the case database
Milestone 7 · Engineering core · E3Build → Verify: Code with AISet up the team's AI coding tools, direct AI to build a small program from your own spec in JavaScript, read every line, test it, and pass a proctored no-AI practical.

What you'll learn

  • VS Code with GitHub Copilot, Cursor and Claude Code set up the way a team would, agent mode used once with you reviewing every change
  • Code concepts through the build, in JavaScript: types, control flow, loops, functions
  • Reading AI code line by line, hallucination patterns, and writing tests against your own build

What you'll build

  • An AI-built mini program from your own spec, a log of three AI errors you caught and fixed, a reviewed pull request, and a passed no-AI practical
Milestone 8 · Engineering core · E4Build → Verify: Front-End with AIHTML, CSS and JavaScript and the DOM, a real page built with AI and modified by hand, deployed to a real URL, one AI feature added and evaluated, and testing a peer's build.

What you'll learn

  • HTML/CSS/JS structure and reading the DOM (it feeds your locators later)
  • Deploy to a real URL on Vercel with a preview per pull request, plus a short tour of where a backend actually lives
  • Add one AI feature through a faculty-hosted proxy, evaluate ten outputs against a rubric, and try one prompt-injection input

What you'll build

  • A live passion-domain page on Vercel with one AI feature and its evaluation sheet, plus a defect report on a classmate's build
Milestone 9 · Engineering core · E5Automation: Playwright, Git & CIBrowser automation in Playwright with JavaScript, Git for teams, one Selenium literacy session, a CI run you built, and agentic testing as awareness.

What you'll learn

  • Playwright in JavaScript: locators, auto-waiting, codegen from acceptance criteria, reviewing generated tests
  • Git for teams: branch, pull request, review, merge; one Selenium literacy session so enterprise stacks are familiar
  • CI built, not shown: a GitHub Actions workflow that runs your tests and API collection on every push

What you'll build

  • Five Playwright tests on your own build and the demo app, your API collection wired into CI, and one green CI run on your repo

Stage 3 · Your track 1 milestone

Milestone 10 · Your track · T-DEVAI for Software DevelopersThe spec-first build loop as the job, front-end depth, and a deployed app with a template backend endpoint and your AI feature carried forward.

What you'll learn

  • The spec-first build loop end to end; reading and correcting AI code as the job
  • Front-end depth: components, responsive layout, accessibility basics; prompt discipline
  • A faculty backend template you add one endpoint to, and an agentic coding workflow with you as the reviewer

What you'll build

  • Two complete build-loop artifacts (spec, build, tests, "what AI got wrong" log), one deployed on Vercel

Stage 4 · Capstone defended to a faculty panel

Milestone 11 · Capstone · CapstoneThe Builder CapstoneBuild it, deploy it, defend it: a recorded presentation and a faculty panel, then resume, portfolio and mock interviews.

What you'll learn

  • Written spec, the build (AI-directed, hand-modified), test plan, Playwright checks in a green CI run
  • A README with an "AI tools used and what I changed" section
  • Presenting in role: demo plus three decisions where you overrode the AI; mock interviews with a live code-reading screen

What you'll build

  • Your deployed capstone, its recorded defense (a portfolio asset), a polished resume and a live portfolio

One milestone at a time, in order. Milestone content is maintained by faculty and may be refined between cohorts. Clock hours, assessments and program requirements are stated in the school catalog and your enrollment agreement.

Questions

Questions people ask

How long does it take?

You complete every milestone; how quickly depends on your experience, what you already know, and the hours you put in each week.

Do I have to attend classes at set times?

No, but live instruction is there for you every week. Join live or watch the recording, and drop into topic office hours whenever you need help. The required commitments are a short progress check every two weeks, proctored assessments you book when you're ready, and your capstone presentation.

When can I start?

New groups begin the first of every month. Enroll anytime, pick your start month, and complete guided onboarding before your start date.

Upon completion you receive a certificate that names both your Digital Engineering program and your chosen specialization, recognized by the State Council of Higher Education for Virginia (SCHEV). Track names describe the specialization focus and career positioning of each concentration; approved outcome roles are QA Automation Engineer, QA Analyst, SDET and Full-Stack Developer. Program outcomes, hours and credentials are listed in the school catalog. Individual employment results vary; no specific job title or salary is guaranteed.