SB
Spandana Bala
Full Stack Java Developer
Hyderabad · India
Now at · Infosys
Full Stack Java · Java 21 · Spring Boot 3 · React · Spring AI · MCP · Enrolling now
Full Stack Java
A career-focused, code-first program: build strong modern Java, Spring Boot 3, SQL and React foundations, then build microservices and AI features with Spring AI, LangChain4j and MCP — secure, observable and deployed to Kubernetes, with coding agents at your side.
100K+
alumni community
1,000+
hiring partners
4.8/5
avg class rating
12
partner centres
7
Edify Nuva centres
Where our Full Stack Java alumni work
Microsoft
Amazon
Salesforce
ServiceNow
Deloitte
Infosys
Accenture
TCS
Wipro
Capgemini
Cognizant
HCL
MicrosoftAmazonSalesforceServiceNowDeloitteInfosysAccentureTCSWiproCapgeminiCognizantHCL
Direct answer
What is the Full Stack Java program?
A full-stack Java engineer builds the enterprise systems most large organisations run on — Spring Boot services, relational data, React front ends — and now the AI features and agents inside them. Most Java courses end at a CRUD app on Spring Boot. This program ends only when you have shipped secured microservices with Kafka and observability, a Next.js front end with streaming AI chat, a Spring AI RAG feature exposed through MCP, and a CI/CD pipeline to Kubernetes.
The complete delivery chain
Twelve links, one owner — end to end.
01CORE
- •Modern Java 21 — records, streams, virtual threads
- •SQL, data modelling & PostgreSQL
- •Design patterns & clean architecture
- •JUnit, Mockito & TDD
02BUILD
- •Spring Boot 3, Spring Data & Spring Security
- •Microservices, Spring Cloud & Kafka
- •React, Next.js & streaming AI UIs
- •Spring AI, RAG & MCP tools
03SHIP
- •Docker, Kubernetes & CI/CD
- •OpenTelemetry, Prometheus & Grafana
- •Evals & guardrails for AI features
- •Coding-agent workflows with Claude Code & Cursor
Enterprise Java in 2026
Java runs the enterprise. Now it runs the enterprise's AI too.
Modern Java & Spring Boot 3Platform layer
Java 21 LTS with virtual threads, records and pattern matching, on Spring Boot 3 and Jakarta EE — the stack banks, insurers, telcos and SaaS companies keep hiring for.
Spring AI & LangChain4jNew '26
First-class AI in the Java ecosystem — ChatClient, structured outputs, tool calling, RAG advisors and vector stores — so AI features ship inside the same Spring services, with the same security and observability.
MCP Java SDKProtocol layer
Spring AI ships MCP client and server support built on the official Java SDK. Java services now expose governed tools to Claude, Cursor and enterprise agents, and consume MCP tools in return.
Coding agents for JavaDeveloper workflow
Claude Code, Cursor and Copilot understand large Java codebases, write tests and drive migrations. Engineers direct and review — and legacy modernisation became an AI-assisted job.
Cloud-native & observabilityOperations layer
Docker, Kubernetes, GitHub Actions, OpenTelemetry and Grafana are table stakes; GraalVM native images and virtual threads changed the performance conversation.
Security & governanceTrust layer
Spring Security with OAuth2 / OIDC, supply-chain security, prompt-injection defence and the EU AI Act — what enterprises audit before AI features reach production.
What this means for your career: Java roles now ask for Spring Boot 3, microservices and cloud alongside Spring AI and AI-assisted development — the differentiator is a deployed, secured system with an AI feature you can demo and evals behind it, not a CRUD portfolio.
Who should join
Built for people moving into enterprise Java engineering.
CS / IT graduates & career switchers
Java developers upgrading to Spring Boot 3 & AI
.NET, PHP or Python developers moving to Java
Support & QA engineers moving to development
Front-end developers going full stack
Engineers targeting banks, insurers & enterprise SaaS
Prior experience: none required — Java, SQL and JavaScript are taught from scratch. The program builds core Java and web foundations before Spring Boot, microservices, Spring AI and cloud delivery.
What you will be able to do
Build enterprise systems — and their AI features.
Write modern JavaJava 21, OOP, collections, streams, concurrency and virtual threads with JUnit and Mockito.
Build Spring Boot servicesREST APIs, Spring Data JPA, Spring Security with OAuth2, testing with Testcontainers.
Design microservicesSpring Cloud, Resilience4j, Kafka, sagas and OpenTelemetry observability.
Build React front endsTypeScript, React, Next.js and streaming AI chat UIs calling Spring APIs.
Add AI with Spring AIChatClient, structured outputs, tool calling, RAG with pgvector, MCP client and server.
Ship to the cloudDocker, Kubernetes, CI/CD, monitoring and AI-assisted development with Claude Code and Cursor.
Course curriculum
Twelve sections. 56 modules. Java → SQL → Spring Boot → Microservices → React → Spring AI → Cloud.
01
Fundamentals of IT & AI
How software, the web and AI systems fit together — and where a Java full-stack engineer works in the 2026 stack.
Client-server, HTTP, REST and JSON
Operating systems, terminals and Git
Databases and cloud basics
How enterprise Java systems are structured
Frontier models — Claude, GPT, Gemini — and open weights
From chatbots to agents: tool use and reasoning
MCP and agent interoperability
AI in the Java ecosystem — Spring AI and LangChain4j
JDK 21+, IntelliJ IDEA and Maven / Gradle
Git and GitHub workflows
Claude Code, Cursor and Copilot for Java
Reviewing AI-generated code
Privacy and PII in enterprise apps
Prompt injection and AI-specific risks
EU AI Act and NIST AI RMF overview
Secure-by-default habits
02
Core Java
Modern Java from first principles — the way it is written in 2026.
Types, variables, operators and control flow
Methods, arrays and strings
Records, var and text blocks
Compilation and the JVM
Classes, objects and encapsulation
Inheritance, interfaces and polymorphism
Sealed classes and pattern matching
SOLID principles
List, Set, Map and Queue
Generics and wildcards
Iteration and comparators
Immutable collections
Checked vs unchecked exceptions
try-with-resources
Files, NIO and date-time API
Logging
Lambdas and functional interfaces
Streams API and collectors
Optional
Functional patterns
JUnit 5 and assertions
Mockito
Test-driven development
Testing with coding agents
03
Advanced Java & Concurrency
Performance, concurrency and the JVM internals interviewers ask about.
Threads, executors and CompletableFuture
Virtual threads and structured concurrency
Synchronisation and concurrent collections
Common concurrency bugs
Memory model and garbage collection
JIT and profiling
Tuning flags and diagnostics
Performance testing
Creational, structural and behavioural patterns
Dependency injection
Hexagonal and layered architecture
Refactoring with AI assistance
Maven and Gradle in depth
Java modules
Dependency management and BOMs
Reproducible builds
04
Databases & SQL
Relational data done properly — the foundation of every Spring application.
SELECT, JOIN, GROUP BY and set operations
Subqueries and CTEs
Data types and constraints
PostgreSQL and MySQL
Window functions
Indexes and query plans
Transactions and isolation levels
Query tuning
Normalisation and relationships
Schema design for applications
Migrations with Flyway and Liquibase
pgvector for AI features
MongoDB and Redis basics
When to use NoSQL
Caching strategies
Polyglot persistence
05
Foundations of Web & TypeScript
Front-end fundamentals for Java engineers.
Semantic HTML and forms
Flexbox, Grid and responsive design
Tailwind CSS
Accessibility basics
ES modules and syntax
Arrays, objects and destructuring
Promises, async / await and fetch
DOM and events
Types, interfaces and generics
Typing API responses
Tooling and configuration
TypeScript for Java developers
npm / pnpm
Vite
Vitest and Playwright basics
Linting and formatting
06
React & Next.js
Modern React front ends — including AI chat and streaming UIs.
Components, props and JSX
State, events and lists
Hooks
Component design
Context and reducers
TanStack Query
React Hook Form and Zod
Optimistic updates
Routing and layouts
Server components and actions
Calling Spring Boot APIs
Deployment on Vercel
Vercel AI SDK and useChat
Streaming from Spring Boot back ends
Generative UI patterns
Handling errors and cancellation
Testing Library and Playwright
shadcn/ui and component libraries
Accessibility
Performance
07
Spring Boot & REST APIs
The enterprise back end — Spring Boot 3, Spring Data and Spring Security.
Spring Boot 3 and dependency injection
Configuration and profiles
Auto-configuration and starters
Actuator
Controllers, DTOs and validation
Exception handling
OpenAPI with springdoc
Versioning
Entities, repositories and relationships
Queries and projections
Transactions
N+1 and performance
Authentication and authorisation
JWT and OAuth2 / OIDC
Method security
Securing AI endpoints
Spring Boot Test and MockMvc
Testcontainers
Integration tests
Contract testing basics
Spring Cache and Redis
Scheduling and async
Spring for Apache Kafka
Event-driven patterns
08
Microservices & Spring Cloud
Distributed systems with Spring — resilient, observable and deployable.
Monolith vs microservices
Service boundaries and domain-driven design
API gateways and service discovery
Data ownership
Spring Cloud Gateway and Config
Resilience4j — circuit breakers and retries
Service-to-service communication
Distributed tracing
Kafka and messaging patterns
Sagas and outbox pattern
Idempotency
Schema evolution
Micrometer and OpenTelemetry
Prometheus and Grafana
Structured logging
Alerting
09
Spring AI & LLM Engineering in Java
Build AI features natively in the Spring ecosystem.
How LLMs work — tokens, context, cost
Structured outputs and tool calling
Hallucination and grounding
Model selection
ChatClient and model providers — Anthropic, OpenAI, Azure, Ollama
Prompts, templates and structured outputs
Function / tool calling
Streaming responses
Embeddings and vector stores — pgvector, Redis, Pinecone
Document readers and ETL pipeline
Advisors and retrieval
Evaluating retrieval
LangChain4j overview
AI services and tools
Comparing Spring AI and LangChain4j
Calling Python agent services from Java
Token accounting and budgets
Caching and batching
Streaming and timeouts
Observability for AI calls
10
AI Agents & MCP in Java
Agents that act — built in Java and connected through MCP.
The agent loop
Planning, reflection and multi-agent patterns
Human-in-the-loop
When not to build an agent
Tool-calling agents with ChatClient
Memory and advisors
Multi-step workflows
Testing agent behaviour
MCP fundamentals — tools, resources, prompts
Spring AI MCP client and server
Exposing Spring services as MCP tools
Security and permissions
Claude Agent SDK and Spring AI services
Java to Python interop over HTTP and MCP
Polyglot agent architectures
Deployment considerations
Eval datasets and LLM-as-judge
Guardrails and prompt-injection defence
Tracing with OpenTelemetry
Regression testing
11
Cloud, DevOps & AI-Native Development
Ship Java to the cloud — with coding agents on the team.
Dockerising Spring Boot
Kubernetes deployments and services
Helm basics
Configuration and secrets
GitHub Actions and Jenkins
Deploying to AWS, Azure or GCP
Blue-green and canary releases
Infrastructure as code basics
Managed databases and queues
Object storage
Serverless Java (overview)
Cost management
Claude Code workflows for Java projects
Cursor and Copilot agent mode
Spec-first and test-first with agents
Code review of AI-generated code
Understanding legacy codebases with AI
Migration strategies — Java 8 to 21, Spring Boot upgrades
Refactoring safely with tests
Documentation generation
12
Capstone, Portfolio & Career
An enterprise-grade Spring Boot and React product with AI features — verifiable by employers.
Spring Boot microservices with Spring Security and PostgreSQL
Next.js front end with streaming AI chat
Spring AI RAG feature and an MCP tool
CI/CD to Kubernetes with observability and a public verification URL
Add an agent to an existing Java application
Evals and guardrails
Cost and latency budget
Demo and write-up
Oracle Java SE certification
Spring Certified Professional
AWS or Azure developer associate
Study plan
GitHub portfolio with READMEs and demos
Resume rewrite around shipped systems
Java interview practice — DSA, Spring, system design
Warm introductions to hiring partners
Tools you'll master
32+ Full Stack Java tools, one production project.
Real-time projects
You don't watch videos. You ship software.
Three portfolio projects and a partner capstone, each threaded through the entire curriculum — Java, Spring Boot, React, Spring AI and cloud all land in real deliverables.
Hero project
Enterprise platform — Spring Boot microservices + React + Spring AI
Build an end-to-end enterprise platform — Spring Boot 3 microservices with Spring Security and PostgreSQL, a Next.js front end with streaming AI chat, a Spring AI RAG feature exposed as an MCP tool — shipped to Kubernetes with CI/CD, observability and cost guardrails.
01Live React + Next.js app on Kubernetes with shadcn/ui, real-time streaming chat UI, optimistic state, and full a11y/keyboard nav.
02Spring Boot backend wired to a Spring AI supervisor topology, Postgres+Pinecone storage, OpenTelemetry, and replay-capable state.
03MCP server that exposes your agents as tools to Claude/ChatGPT desktop, with auth, scopes, rate-limit, and audit logging.
04Eval + safety harness — golden dataset, regression suite on every PR, hallucination + cost guardrails on a public dashboard.
Outcome: 5,000+ users on staging
p95 chat latency: <1.2s
Reviewer: Senior staff engineer panel
Spring BootReactSpring AIMCPKubernetes
Enterprise
Event-driven order system with Kafka
Ship an event-driven order-to-fulfilment system — Spring Boot services communicating over Kafka with the outbox pattern, sagas and idempotent consumers, Resilience4j circuit breakers, and OpenTelemetry tracing across every hop.
KafkaResilience4jSpring CloudOpenTelemetry
Real-time
Spring AI assistant with RAG and MCP
Build an internal assistant on Spring AI — RAG over company documents with pgvector, tool calling into existing Spring services, an MCP server so Claude and Cursor can use it, and an eval harness with guardrails.
Spring AIpgvectorMCPEvals
Project
Your enterprise Java product in a controlled project environment.
Pick a real partner workflow. Ship a production Java platform — Spring Boot microservices, React front end, Spring AI feature, MCP server, evals — to a partner team that's running it for real users.
Download the real world project
Full scope, sample deployment contexts, project milestones, and grading rubric — PDF, 14 pages.
Production-style capstoneCareer support included
Your instructor
Taught by engineers who ship enterprise Java to production.
MK
Manikanta Kona
Founder, Edify Nuva · Full Stack Java Architect
Java · Spring Boot · Microservices · Kafka · React · Spring AI · MCP
"Enterprise Java today means Spring Boot 3 services that are secured, observable and deployed to Kubernetes — with Spring AI features and an MCP surface built in from day one. That's the bar I teach to, every class."
15 yrs
ENTERPRISE JAVA
2,400+
LEARNERS
4.8 /5
RATING
Manikanta is the founder of Edify Nuva and brings 15 years of enterprise Java architecture from AT&T, Salesforce, Cox Communications, and Broadcom — where he led Spring-based platform engineering, microservices migrations and React front ends at Fortune-500 scale. Most recently he architected production Spring AI and MCP features inside existing Java estates, bringing agents into systems that banks and telcos already run.
His classes get you two things other programs don't give you: a founding architect who's still shipping production Java from inside the Fortune 500, and a curriculum rewritten every release — so when hiring managers ask about virtual threads, Spring Security with OIDC, Kafka sagas, Spring AI or MCP, you've already built it. M.S. in Engineering, Purdue University.
RK
Ravi Krishna
Chief Technologist, Edify Nuva · Java Platform & Cloud Lead
Spring Boot · Spring Cloud · Kafka · Kubernetes · OpenTelemetry · Spring AI
"Shipping Java to production is where tutorials die — security, transactions, Kafka
retries, observability, and an AI feature with evals and cost guardrails that doesn't fall over at 3 AM.
That's what I teach, end to end."
10 yrs
ENTERPRISE JAVA
1,800+
LEARNERS
4.8 /5
RATING
Ravi is Chief Technologist at Edify Nuva, where he leads the Java Platform & Cloud practice. After 8 years building production Spring Boot, Kafka and Kubernetes platforms, he stepped into the Chief Technologist seat to wire Spring AI, MCP and evals into the way enterprise Java teams actually ship — secured services with replayable events, observability that on-call engineers trust, and AI features that pass a bank's review.
His platform modules are built from real production post-mortems, not slide decks. Expect to leave with working Spring Boot microservices on Kafka, a Next.js reference front end, a Spring AI feature with an MCP server behind auth and audit, and a CI/CD pipeline to Kubernetes you can stake an SLA on. Holds Spring Certified Professional and AWS Solutions Architect; ten years at Edify Nuva, hands-on, and known for the unglamorous parts of enterprise Java that everyone else skips.
HIRING PARTNERS · INDUSTRY VOICES
What enterprise Java employers say about Edify Nuva grads.
Real feedback from talent leaders at AI-first product orgs and the firms hiring our Full Stack Java graduates.
Edify Nuva grads ramp 40% faster on Spring Boot + React platforms than typical hires. Best enterprise Java pipeline in India.
Aakash Mehta, AI Partner Programme Lead, Microsoft
We've onboarded 80+ Edify Nuva alumni in 18 months. Lowest ramp time we've seen for Next.js + Spring AI agent practices.
Anita Sharma, Senior Manager, Deloitte
The Full Stack Java programme is comprehensive — Spring Boot 3, Kafka, React, plus Spring AI and MCP. Grads come pre-trained for enterprise production.
Rahul Bhatt, Solutions Lead, Anthropic Partner
Their Spring Boot + React track produces engineers who ship streaming Spring AI endpoints to production on day one. Genuinely rare.
Deepak Pillai, Senior Architect, TCS
What sets Edify Nuva apart is the MCP + evals layer baked into the Java track. Our enterprise clients ask for exactly this profile.
Suresh Menon, Practice Lead, Accenture
Their Spring Boot + Spring AI prep is rigorous, and the project platform deployed on Kubernetes is what closes interviews for us.
Vikram Iyer, Director, Infosys
Edify Nuva's Java grads ship production Spring AI features twice as fast in the first 90 days. Our internal metrics back this up clearly.
Lakshmi Nair, VP Engineering, Wipro
Best Spring Boot + React pipeline we've sourced from in India. Their projects are production Spring systems, not toy demos.
Karthik Subramanian, Engineering Director, Cognizant
Strong Spring Boot and React foundations. Their Java grads need almost zero ramp time on enterprise agent engagements.
Arun Joshi, Practice Director, Capgemini
We've placed 40+ Edify Nuva alumni across our Java, Spring and watsonx platform teams. Strong fundamentals, sharp on the eval stack.
Sanjay Verma, Talent Director, IBM
MCP servers + observability and cost guardrails is exactly the talent gap we've been struggling to close. Edify Nuva is filling it for us reliably.
Anjali Desai, Practice Head, LTIMindtree
Their Java track delivers engineers who navigate React server components, Spring Boot, and Spring AI supervisors on customer engagements unsupervised.
Ramesh Iyer, Senior Manager, Tech Mahindra
Hired 25+ Edify Nuva graduates for our Java platform team. Strong Spring + Kafka depth, and they actually understand observability.
Geetha Pillai, Talent Acquisition Lead, Hugging Face
Edify Nuva grads who blend Spring Boot with Spring AI + MCP land production-ready on day one. Rare combination, well-trained.
Priya Reddy, Talent Lead, LangChain
03Program certifications
An Enterprise‑Ready credential, not a participation trophy.
Edify Nuva · Institute Certificate
Enterprise‑Ready Full Stack Java Engineer
Presented to
Spandana Bala
For the successful design, build, and production deployment of an enterprise Java platform — Spring Boot microservices, React/Next.js front end, Spring AI feature with MCP, and CI/CD to Kubernetes — graded against the 2026 Enterprise‑Ready rubric.
Manikanta Kona
CEO · Edify Nuva
AGENT
READY
2026
READY
2026
01
Industry‑recognized
Co‑branded with our partner ecosystem and mapped to LangChain Academy badges, AWS
Solutions Architect, and Spring Certified Professional credentials — names that hiring managers already scan for on resumes.
02
Project artifact included
Every certificate carries your project project name, the partner org, and a link to
the deployed React app + Spring Boot backend + Spring AI/MCP server + eval harness — proof, not a promise.
03
Enhanced skill validation
Graded against the 2026 Enterprise‑Ready rubric: Spring Boot architecture, React/Next.js design,
Spring AI orchestration, MCP integration, evals, and cost guardrails. No pass/fail — a level 1‑5 band.
04
Verifiable on a public URL
Each credential has a public verification page recruiters can check in 10 seconds — no PDF
back‑and‑forth.
Job roles
Roles this program prepares you for.
Full Stack Java Developer
Spring Boot back ends and React front ends for enterprise products.
Java Backend Engineer
Spring Boot, Spring Data and Spring Security services.
Microservices Engineer
Spring Cloud, Kafka and cloud-native distributed systems.
Java AI Application Engineer
AI features with Spring AI, LangChain4j and MCP.
Software Engineer (Banking & Insurance)
Enterprise Java in regulated industries.
React / Frontend Engineer (Java shops)
Front ends for Spring-based platforms.
DevOps-minded Java Engineer
Docker, Kubernetes and CI/CD for Java services.
Application Modernisation Engineer
Java and Spring upgrades with AI-assisted refactoring.
Solutions Engineer (Java / Spring)
Prototype and integrate for enterprise customers.
Java Tech Lead / Architect (career path)
Grow toward leading enterprise Java teams.
What employers should see in your portfolio: that you can take a requirement to a deployed enterprise system — Spring Boot microservices with Spring Security, Kafka and PostgreSQL, a Next.js front end with streaming AI chat, a Spring AI RAG feature exposed through MCP, evals and observability, shipped through CI/CD to Kubernetes.
04Job placement support
Your first Full Stack Java offer isn't a lottery ticket. It's a built process.
GitHub, LinkedIn, resume — and most importantly, warm intros into AI-first product orgs and
services that staff enterprise Java teams. Our placement team works your search like an account, not a helpdesk.
01 / GITHUB PROFILE
A portfolio, not a graveyard.
Guidance on building a GitHub that showcases your React/Next.js app, Spring Boot + Spring AI backend, MCP server, eval harness, and a working production link — reviewed 1:1, not via template.
02 / RESUME PREP
Rewrite, don't proofread.
A one-page resume rebuilt around the Java platform you shipped (Spring Boot, ReactPI, Spring AI, MCP, evals) and the business outcome. Reviewed by engineers who've read 10,000+ resumes.
03 / LINKEDIN + INTROS
Where most opportunities actually live.
Profile tuning plus direct warm introductions into AI-first SaaS & product orgs — Microsoft, Oracle, Red Hat, JPMorgan, Goldman Sachs, HSBC, Wells Fargo, PayPal, Walmart, Razorpay, Freshworks, Zoho, plus services that staff enterprise Java teams (Deloitte, Accenture, Cognizant). You leave with recruiter contacts, not a generic "good luck."
Full Stack Java alumni
Hundreds of enterprise Java careers launched — here are eight.
NV
Naveen Vedala
Senior Java Engineer (Microservices)
Hyderabad · India
Now at · TCS
TA
Tejashwini Addla
Spring AI Backend Lead
Hyderabad · India
Now at · Deloitte
TD
Tharunesh Dillikar
Staff Java Engineer (Platform & AI)
Seattle · United States
Now at · Microsoft
MM
Mujahed Mohammed
Principal Engineer (Agent Platforms)
Hyderabad · India
Now at · Accenture
BK
Bhargav Kumar Murala
Agent UX Engineer
Hyderabad · India
Now at · Capgemini
SL
Sai Manasa Leburi
Lead React Engineer (AI)
New York · United States
Now at · JPMorgan
RD
Rahul Dhamma
AI Product Engineer
Hyderabad · India
Now at · Cognizant
Our locations
Come chat with us — over coffee, or over Zoom.
One flagship campus in Hyderabad, plus online Full Stack Java classes running on Indian and US timezones.
Flagship campus
Hyderabad
2nd Floor, Hitech City Road · Above Domino's · Opp. Cyber Towers, Jai Hind Enclave ·
Hyderabad, Telangana
Call
+91 8142998866
US desk
+1 256 388 7766
Hours
Mon–Sun · 7 AM–9 PM
Online class
Global
Weekend and evening Full Stack Java classes running on IST and PST. Every online class
ships the same React app + Spring Boot backend + Spring AI/MCP server + eval harness project as the
on‑campus track.
Timezones
IST & PST
Format
Live + 1:1 mentorship
Admissions
ENROLLING NOW
FAQ
Questions we actually get — answered honestly.
Straight answers on prerequisites, the stack, evals, and placement. If something's missing, book a 20-minute advisor call — no slides, no pitch.
Do I need a CS background or prior Java experience?
No on both counts. Roughly 40% of every class comes from non-CS streams — mechanical, electrical, BCom, BBA — and zero React or Python exposure is assumed. The opening modules cover JavaScript/TypeScript, Python, and the web platform from scratch. What you do need is consistency and regular practice.
Will I actually ship a production app, or only build toy demos?
You ship a real one. Every learner deploys a project enterprise Java platform — a React/Next.js app, a Spring Boot + Spring AI backend, an MCP server with auth, and an eval harness — to a live URL on Kubernetes. Every lab, project, and the project are live artifacts you can demo to recruiters, not slide decks.
Which framework + AI stack will I use?
Frontend: React 19, Next.js App Router, TypeScript, Tailwind, server components, streaming UI. Backend: Java 21, Spring Boot 3, Spring Data JPA, Spring Security, Kafka, PostgreSQL, Redis. AI layer: Spring AI for agent orchestration, MCP servers for tools, evals + observability, plus cost & safety guardrails.
Will I learn evals, observability, and cost guardrails?
Yes — they're a first-class section, not a footnote. You build an eval harness for your agent flows, wire tracing + observability dashboards, and ship cost & safety guardrails (token budgets, rate limits, prompt-injection defenses) before you're allowed to call the project done.
How is the learning workload structured?
The program combines live mentor-led classes, guided labs, project work, and optional support sessions. An advisor can explain the current class format before enrolment.
Is placement support really 1:1, and which companies hire Full Stack Java engineers?
Yes. Career support includes portfolio and profile preparation, interview practice, and role-fit introductions where available. Edify Nuva does not guarantee an interview, offer, salary, employer, location, or timeline.
Online, weekend, or on-campus?
All three. On-campus at the Hyderabad flagship, live online (IST and PST classes), and a weekend track for working professionals. Every format ships the same three projects and the same enterprise Java project — only the schedule changes.
What if I fall behind, or can't continue mid-class?
Freeze your seat for up to 90 days and rejoin the next class — no extra fee. TAs run catch-up sessions every Saturday for learners needing additional support, and recordings of every live session are available for the lifetime of your account.
Still have a question? Talk to an advisor — no slides, no pitch.
One million AI‑native professionals by 2027.
Let's put you in that number.
Book a 20‑minute advisor call. We'll map your current role to the right program, talk honestly about timelines, and walk you through a real class's project.
