MERN Engineering · AI Engineering · Interview-Ready DSA
Build the proof that turns "I'm learning full-stack" into "Here's what I shipped."
A six-month, weekend-live career program for graduates, career changers and early-career engineers who want production-minded MERN skills, professional AI fluency and the confidence to face technical interviews with evidence.
You will not finish with a folder of half-watched tutorials. You will build, test, deploy, document and defend software across an integrated 24-week journey.
240 structured hours 36 project builds Placement track from W13
type EngineerEvidence = {
projects: 36;
milestones: 7;
dsaProblems: "110+";
aiUsage: "reviewed";
capstone: "defended";
};
const candidate: EngineerEvidence =
buildWithDiscipline();AISuggestion reviewedaccepted after tests
"Generate faster" is not the finish line. Explainability, tests and evidence are.
portfolio-verification
$ npm run verify:evidence
✓ frontend capstone deployed
✓ API documented and tested
✓ AI decisions disclosed
✓ capstone ready to defend
W13placement track opens
7portfolio milestones
WHY THIS PROGRAM EXISTS
The job changed. Your preparation should too.
AI can generate code. Hiring teams still need engineers who can decide what is correct, secure, testable and worth shipping. That judgment is now the differentiator.
AI fluency is now baseline
You work with Claude, Claude Code, Cursor, Copilot and the modern AI application stack from the beginning—not as a last-week add-on.
Reward: faster execution without outsourcing your thinking.
Judgment matters more than output
Every AI-Native Lab requires a documented rejection. You learn to inspect suggestions, find failure modes and defend what you keep.
Reward: a credible answer when an interviewer asks, "Why this approach?"
Production discipline separates candidates
Tests, accessibility, security, observability, backups, rollback paths and honest limitation notes turn a demo into engineering evidence.
Reward: work that can survive scrutiny—not just a screen recording.
YOUR EXIT EVIDENCEYou do not finish with just a certificate.
You do not finish with just a certificate.
You finish with receipts.
Every reward below is attached to something you can open, run, explain, test or defend.
Portfolio proof01
A deployed frontend capstone and case study
React, TypeScript, forms, routing, deliberate state ownership, testing, accessibility and performance—presented as a coherent project story.
- Live deployment
- Repository and README
- Architecture explanation
Backend proof02
A documented, tested API
Typed Node and Express services, clear layers, structured logs, a verified OpenAPI contract and appropriate test coverage.
Full-stack proof03
A secure MERN beta
A complete user journey across React, API, database, authentication, authorization, validation and failure-state UX.
AI proof04
An auditable AI engineering record
Structured-output validation, RAG, tool calling, evaluation, cost and latency thinking, rejected suggestions and a disclosure log.
Interview proof05
A measured DSA progression
110+ problems, five level checkpoints, complexity explanations and three mock interviews under panel conditions.
Final proof06
An industry capstone you defend live
Architecture, trade-offs, tests, operations, limitations and AI use—released, documented and presented before a panel.
THE 24-WEEK JOURNEY
From first commit to defended capstone.
Three phases build on one another. Your projects become more integrated, your decisions more consequential and your evidence more valuable.
FRONTEND ENGINEERING & PLACEMENT READINESS
Build a frontend portfolio before backend complexity arrives.
Start with web foundations, responsive UI and Git. Progress through JavaScript, TypeScript, React, forms, routing, state, testing, accessibility and performance.
Your phase rewardA deployed frontend capstone and case study—the gate that opens the placement track.
Representative builds
- 01 Reusable UI System & Marketing Site
- 02 Typed JavaScript API Application
- 03 React Product Browser
- 04 Tested Accessible Dashboard
- 05 Deployed Frontend Capstone & Case Study
BACKEND ENGINEERING & MERN INTEGRATION
Turn a polished interface into a secure, persistent application.
Build typed Node and Express services, document and test APIs, model data with MongoDB, implement identity and authorization, then add production workflows, Redis or real-time features.
Your phase rewardA secure full-stack MERN beta with an end-to-end user journey you can demo and explain.
Representative builds
- 01 Typed Express REST API
- 02 Documented and Tested API
- 03 Persistent Data API
- 04 Secure Multi-User API
- 05 Full-Stack MERN Beta
PRODUCTION DELIVERY, CAPSTONE & CAREER ACCELERATION
Package, deploy, observe and defend what you built.
Containerize the stack, automate delivery, deploy to cloud, add observability and operational evidence, complete the capstone and rehearse the technical defence.
Your phase rewardA production-style capstone, final case study, technical presentation and complete portfolio narrative.
Representative builds
- 01 Dockerized MERN Stack
- 02 Automated Cloud Release
- 03 Capstone Vertical Slice
- 04 Operational Capstone Beta & AI Audit
- 05 Industry Capstone & Career Presentation
HOW THE WEEK WORKS
A schedule built for people who need structure—not more saved videos.
Weekdays build fluency. Weekends are protected for the decisions that are hard to learn alone: implementation, live debugging, architecture argument, interview practice and review.
"Syntax can be learned alone; judgment cannot."
MON–FRI~4 hrs
Self-paced foundation
- Concept micro-videos and reading notes
- Interactive coding and guided labs
- Weekly quiz and debugging challenge
- DSA problem sets with complexity notes
- Readiness check before the live studio
SATURDAY3 hrs live
Implementation Studio
Readiness & blockersClear the ground before building.
Live implementationBuild from empty, decision by decision.
Learner build sprintExtend the work with instructor support.
Debug clinicDiagnose deliberately introduced failures.
SUNDAY3 hrs live
Applied Engineering Studio
DSA Live ClinicPattern teaching and timed practice.
Sprint projectBuild the second integrated artifact.
AI-Native LabUse the sprint tool on your own codebase.
Sprint reviewDemo, PR review, evidence and retrospective.
CURRICULUM EXPLORER
Five capability tracks. One connected engineer.
The curriculum does not teach isolated tools. Each technology arrives when a project needs it and is assessed at a stated depth.
FRONTEND ENGINEERING
Build interfaces that work beyond the happy path.
Move from semantic HTML and responsive design to strict TypeScript, React architecture, validated workflows, deliberate state ownership, accessibility, testing and measured performance.
HTMLModern CSSJavaScriptTypeScriptReactViteReact Hook FormTanStack QueryRedux ToolkitPlaywright
You will be able to showA deployed frontend capstone with tests, accessibility evidence and a written case study.
BACKEND & DATA
Build the systems behind the interface.
Design typed services, document API contracts, model data by access pattern, enforce identity and authorization, and implement production workflows with explicit failure behaviour.
Node.jsExpressOpenAPIMongoDBMongoosePostgreSQLRedisSocket.IOAuthenticationAuthorization
You will be able to showA documented API, persistent data layer, secure account lifecycle and integrated MERN beta.
PRODUCTION DELIVERY
Ship through a repeatable path, not a last-minute upload.
Containerize the stack, automate linting, testing, build and deployment, add health checks, logs, backups and rollback, then rehearse release decisions under pressure.
DockerComposeGitHub ActionsCloud deploymentCI/CDHealth checksObservabilityBackupsRollbackSecurity review
You will be able to showA Dockerized application, automated cloud release and operational evidence for your capstone.
AI ENGINEERING
Build AI features with boundaries, evaluation and fallback.
Use assistants responsibly, validate model output, implement RAG and tool calling, design bounded agents, measure quality and cost, and keep humans in control of consequential actions.
ClaudeClaude CodeCursorVercel AI SDKZodMCPRAGAtlas Vector SearchPromptfooLangfuse
You will be able to showA typed AI feature, retrieval-quality evidence, a bounded tool workflow and an auditable AI decision record.
DSA & CAREER
Turn knowledge into interview behaviour.
Progress through five DSA levels with weekly problems, live timed practice and checkpoints, while the placement track converts your technical evidence into a resume, project narrative and interview story.
Arrays & stringsHash mapsTwo pointersSliding windowTreesGraphsDynamic programmingMock interviewsPortfolioTechnical storytelling
You will be able to showFive checkpoint results, three mock-interview feedback records and a placement-ready project narrative.
Want the sprint-by-sprint specification?The brochure maps all 18 sprints and 36 projects.
AI-NATIVE, NOT AI-DEPENDENT
Work with AI like an engineer—not a copy-paste machine.
Generated code is treated as untrusted until it is reviewed, tested, understood and disclosed. The program rewards the quality of your judgment, not the volume of generated output.
01
18 AI-Native Labs—one inside every sprint.
02
One documented rejection per lab with written reasoning.
03
An AI Disclosure Log from first sprint to final capstone.
04
Bounded agents with schemas, permissions, retries, audit logs and human approval.
AI
illustrativeReview LabInspect the suggestion before you keep it.
Model output
- const result: any = await model.generate(prompt);
+ const raw = await model.generate(prompt);
+ const result = OutputSchema.parse(raw);Would you accept this change?
Choose an action to see the engineering rationale.
React + TypeScriptNode.js + ExpressMongoDBClaude CodeCursorMCPRAGDockerGitHub ActionsPromptfooReact + TypeScriptNode.js + ExpressMongoDBClaude CodeCursorMCPRAGDockerGitHub ActionsPromptfoo
INTERVIEW-READY DSA
Interview confidence is trained under a clock.
DSA runs in parallel from Week 3 to graduation. It is taught live, practised weekly and assessed five times—without an assistant during checkpoints and mock interviews.
110+problems
5checkpoints
3mock interviews
45live minutes / Sunday
FoundationsWeeks 3–5 · arrays, strings, hash maps
15 problemsCore patternsWeeks 6–9 · two pointers, window, search
20 problemsRecursion & treesWeeks 10–13 · BFS, DFS, heap
20 problemsGraphs & searchWeeks 14–18 · traversal, backtracking, greedy
25 problemsDP & interviewWeeks 19–24 · mixed timed problems and mocks
30 problems// AI assistance: disabled
function solve(input) {
// explain the pattern
// implement under time
// justify complexity
}
status: "ready to reason aloud"THE MILESTONE LADDER
Seven moments where your work has to survive scrutiny.
Every sprint produces a project. These seven milestones receive deeper portfolio review and create the strongest checkpoints in your story.
01
Milestone 1 · Week 2
Reusable UI System and Marketing Site
Responsive design, accessibility, reusable styling and deployment—your first polished visual portfolio evidence.
Portfolio valueEarly visual proof
PLACEMENT TRACK
Career preparation starts when you have something credible to show.
The placement track opens in Calendar Week 13, immediately after the frontend capstone gate. It runs alongside backend and full-stack development rather than waiting until graduation.
Clear expectation: the program provides evidence, coaching, applications, mock interviews and employer access. It does not guarantee employment.
Lead with frontend proof
Resume and profile alignment, frontend applications, JavaScript, React and DSA interview practice.
Add backend credibility
Recruiter conversations, take-home practice, accessibility questions, data and security stories.
Expand to full-stack roles
Node, API, MongoDB and security interviews supported by a demonstrable MERN beta.
Defend the capstone
Employer events, capstone pitch, system-design fundamentals, final interview rehearsal and follow-up.
FIT CHECK
Is this the right six-month commitment for you?
The program moves quickly. A clear fit saves you time, money and frustration.
You are likely a strong fit if…
- You are a graduate or early-career engineer pursuing junior frontend or full-stack opportunities.
- You are a career changer with some programming exposure and need structure, live accountability and portfolio evidence.
- You can protect Saturday and Sunday live sessions plus weekday self-study.
- You already use AI assistants casually and want professional discipline around them.
- You intend to sit technical interviews and want DSA assessed—not merely mentioned.
×
This is probably not the right fit if…
- You are looking for guaranteed placement rather than a demanding evidence-building program.
- You cannot commit roughly 10–15 hours per week, rising after placement activity begins.
- You want to skip fundamentals because an assistant can generate code.
- You want a passive video course with no camera-on live work or project defence.
- You need deep foundation-model training or robotics hardware specialization.
70/100
6/10minimum capstone score
80%minimum live attendance
5/5DSA checkpoints attempted
7/7milestones submitted
EVIDENCE-BASED CERTIFICATION
The certificate is earned through the work.
There is no single final exam that wipes away six months of evidence. Your score is assembled continuously from projects, milestone reviews, the capstone, DSA and studio participation.
25%
Implementation projects
25%
Major milestones
20%
Industry capstone & presentation
15%
DSA checkpoints & mocks
10%
Live studio participation
5%
Self-paced completion
THE FULL PROGRAM Brochure
Want the complete sprint-by-sprint picture?
Download brochure with all 18 sprints, 36 projects, tool depth codes, AI usage charter, five-level DSA track, placement journey and certification criteria.
Full curriculum map Project evidence Assessment rules
Complete the short contact form to unlock the PDF.QUESTIONS, ANSWERED
Know what you are signing up for.
A serious career program should make the commitment, outcome and limits clear before you apply.
Who is this program designed for?
It is a strong fit for graduates, early-career engineers and career changers with some programming exposure who want junior frontend or full-stack readiness, live accountability and a portfolio that can survive technical scrutiny.
How much time should I commit each week?
Plan for roughly 10–15 hours per week: about four hours of weekday self-paced learning, six live weekend hours and independent project work. From Week 13, placement activity can raise the commitment to roughly 13–18 hours.
Are the weekend sessions live?
Yes. Saturday is a three-hour Implementation Studio. Sunday is a three-hour Applied Engineering Studio with DSA, a sprint project, an AI-Native Lab and review. Sessions are recorded and published to the platform within 24 hours.
What does "AI-Native" mean here?
AI capability is threaded through the engineering program rather than replacing it. You use coding assistants, model APIs, RAG, MCP, agents and evaluation while following a strict review, testing, verification and disclosure discipline.
Is DSA genuinely included?
Yes. The track runs from Week 3 to graduation and includes 110+ problems, a 45-minute live clinic every Sunday, five checkpoints and three panel mock interviews. Checkpoints and mocks are completed without an assistant.
When does placement support begin?
The placement track opens in Week 13, after the deployed frontend capstone gate. It begins with frontend opportunities and expands toward junior full-stack roles as backend and MERN evidence is added.
Does the program guarantee a job?
No. The program provides technical evidence, portfolio reviews, coaching, application activity, mock interviews and employer access. Employment depends on demonstrated capability, interview performance and the market.
How is the certification awarded?
Assessment is continuous. Certification requires at least 70/100 overall, a minimum capstone score of 6/10, at least 80% live attendance, all five DSA checkpoints attempted and all seven major milestones submitted.
MAKE THE NEXT 24 WEEKS COUNT
Build a body of work you can demo, explain and defend.
Start with the full brochure or tell us where you are in your engineering journey. The application form takes less than two minutes.