Build strong problem-solving skills through arrays, strings, recursion, trees, graphs, dynamic programming, and essential algorithmic patterns. Learn time complexity, optimization techniques, and how to approach problems systematically—with AI as your pair programmer.
AI-Assisted Full-Stack Engineering
Become a Full-Stack Software Engineer for the AI era.
Built for working professionals ready to level up in the AI era. Learn DSA, frontend & backend development, databases, system design, and CI/CD. Build real-world applications and gain the skills to land Full-Stack Developer and Forward Deployed Engineer (FDE) roles.
The Skills
With This Program You’ll Master
Learn to build complete applications from frontend to backend and database. Work with React, Node.js, Python, FastAPI, and PostgreSQL while learning how different layers work together in a real application.
Learn to design software from components to scalable systems. Cover LLD, HLD, API design, database modelling, caching, load balancing, message queues, concurrency, and the trade-offs behind real-world architecture decisions.
Learn how to use AI throughout the software development workflow—from understanding requirements and writing code to debugging, testing, refactoring, and documentation—while keeping engineering decisions, quality, and verification in your hands.
Learning in the AI era
AI can
write the code.
So what should developers learn?
Developers don't need to chase every ephemeral tool. While AI rapidly accelerates implementation, syntax generation is only one facet of shipping great products. Lasting competence comes from mastering problem framing, principled architecture, and engineering judgment alongside AI.
AI can help with
- Writing code
- Generating tests
- Explaining & refactoring
- Creating documentation
- Generating SQL & APIs
- Assisting with CI/CD
- Debugging & troubleshooting
- Accelerating implementation
But software engineering is more than code.
Great engineers uncover root problems, balance architectural trade-offs, design dependable systems, and take full ownership of what they ship. That end-to-end craft is what this program trains.
- Understand the problem, its context, and the needs behind it.
- Decide the right approach, guided by needs and constraints.
- Design System architecture, data flow, and component boundaries.
- Build Use AI effectively, reviewing generated code as you go.
- Verify the result against requirements and expected behavior.
Learn by Doing
Learn the
fundamentals.
Spend most of your time building.
We teach you what you need to understand, then give you most of the course to use it through real projects, practical challenges and case studies.
Foundations
Essential fundamentals, system design and problem-solving.
Hands-on
Build real projects, work through case studies, solve practical problems and improve your implementation.
The learning cycle
- LearnUnderstand the concepts and principles.
- PracticeApply them to smaller problems.
- BuildUse them in projects and case studies.
- ReviewReflect, test, improve and learn from the outcome.
Curriculum
From
fundamentals
to full-stack engineering.
A structured 120-day journey that takes you from core problem-solving and development fundamentals to system design, AI-assisted engineering, production, and a complete capstone project.
Understand
- How software moves from idea to requirements, implementation and delivery
- How applications are structured
- Where AI fits into the development workflow
Learn
- Terminal, VS Code and development environment
- Git & GitHub - commits, branches, pull requests and code review
- HTML and CSS fundamentals
- JavaScript fundamentals
- Basic debugging and developer workflow
Build
- Set up a real project and Git repository
- Build a simple web interface
- Create your first branch and pull request
Understand
- How to decompose problems into smaller, solvable parts
- Algorithms, inputs, outputs and edge cases
- Time and space complexity
Learn
- Big-O fundamentals
- Arrays / Lists and Strings
- Hash Maps / Dictionaries and Sets
- Stacks and Queues
- Linked Lists
- Searching and Sorting
- Two Pointers and Sliding Window
- Recursion
- Tree and Graph fundamentals
Build
- Solve structured problem sets
- Apply common problem-solving patterns
- Explain the reasoning behind your solutions
Understand
- How modern web interfaces are structured
- How data flows through a frontend application
- How frontend applications communicate with APIs
Learn
- Semantic HTML
- Modern CSS and responsive design
- JavaScript and asynchronous programming
- DOM and browser fundamentals
- React components, props and state
- Forms and validation
- Routing and API integration
- Loading, error and empty states
Build
- Build a responsive React application
- Connect the frontend to a real backend API
- Build interactive features and forms
Understand
- Python's programming model and core language concepts
- How Python is used to build backend applications
Learn
- Variables and data types
- Strings, Lists, Tuples, Sets and Dictionaries
- Conditions and loops
- Functions and modules
- Exceptions and error handling
- Classes and objects
- Type hints
- Packages, pip and virtual environments
- Basic async / await
Build
- Build small Python programs and utilities
- Solve practical problems using Python
- Structure a small Python application
Understand
- How servers, HTTP and APIs work
- How backend applications process requests and business logic
- What makes an API reliable and maintainable
Learn
- HTTP methods, status codes, headers and JSON
- REST API design
- Python + FastAPI
- Routing, request validation and Pydantic models
- Dependencies and middleware
- Async API development
- Authentication and authorization
- Error handling and API documentation
- Node.js and Express fundamentals
- Node.js routing, middleware and REST APIs
Build
- Build a complete REST API with FastAPI
- Connect API endpoints to the frontend
- Build a smaller API using Node.js + Express
- Add authentication, validation and error handling
Understand
- How applications store, relate and retrieve data
- Why data modelling matters before writing queries
- How database design affects application performance
Learn
- SQL fundamentals
- PostgreSQL
- Tables, relationships and constraints
- Primary and foreign keys
- Data modelling and normalization
- CRUD operations and joins
- Transactions
- Migrations
- Indexes and query optimization
- Connecting PostgreSQL with APIs
Build
- Design a relational database
- Build schemas and migrations
- Connect PostgreSQL to your FastAPI application
- Query and manage real application data
Understand
- How to translate requirements into architecture
- Functional and non-functional requirements
- Engineering trade-offs
Learn
- LLD and object-oriented design
- Classes, interfaces and composition
- SOLID principles and design patterns
- Component and service boundaries
- HLD and architecture diagrams
- API architecture
- Caching
- Load balancing
- Message queues
- Concurrency and asynchronous processing
- Scalability, availability and reliability
Build
- Design real-world systems
- Create architecture diagrams
- Define APIs and data flows
- Explain architectural decisions and trade-offs
Understand
- What AI is good at - and where human judgment is essential
- How to verify AI-generated code and recommendations
- How AI changes the software development workflow
Learn
- AI-assisted planning and implementation
- Developer prompting and context engineering
- GitHub Copilot
- AI-assisted debugging and refactoring
- AI-generated tests and documentation
- Code review with AI
- Spec-driven development
- LLM APIs
- RAG fundamentals
- Agentic AI concepts
- Evals, guardrails and verification
Build
- Use AI throughout a real development workflow
- Build an AI-powered feature
- Review, test and verify AI-generated output
Understand
- What changes when software moves from development to production
- Environments, configuration, deployment, and production concerns
- How applications are packaged, deployed, monitored, and maintained
- Basic cloud concepts and how cloud platforms support modern applications
Learn
- Environment variables and secrets
- Docker and containers
- Application build and deployment
- Cloud fundamentals
- AWS fundamentals
- AWS services commonly used for application deployment
- Deploying applications to AWS
- CI/CD pipelines
- Domains and HTTPS fundamentals
- Logging and monitoring
- Security essentials
- Production debugging
- Basic cloud infrastructure concepts
Build
- Containerize a full-stack application
- Set up a CI/CD deployment workflow
- Deploy the application to AWS
- Configure environment variables and production settings
- Connect the deployed application to a production database
- Set up basic logging and monitoring
- Troubleshoot and resolve a production issue
Understand
- Identify a real problem and define requirements
- Break requirements into features and user stories
- Plan the architecture, database and APIs
Learn
- Architecture and technical trade-offs
- Guided development sprints
- AI-assisted implementation
- Testing and code review
- Iteration and refinement
Build
- Build a complete React + FastAPI + PostgreSQL application
- Integrate authentication and APIs
- Use AI throughout the development workflow
- Test, deploy and document the application
- Demo the finished product
The curriculum is indicative. The final module plan and session schedule are shared with enrolled participants before the program begins.
Tools of the Trade
A
focused stack,
understood end to end.
A practical stack covering the technologies, tools, and AI capabilities used throughout the program — with deeper focus on the core technologies and practical exposure to the rest.
Frontend Engineering
- HTML
- CSS
- Bootstrap
- Tailwind CSS
- JavaScript
- TypeScript
- React
- Next.js
Backend & Data Engineering
- Python
- FastAPI
- Node.js
- Express.js
- REST APIs
- GraphQL
- PostgreSQL
- SQL
- MongoDB
Cloud, DevOps & Dev Tools
- Git
- GitHub
- Docker
- Nginx
- Kafka
- AWS
- CI/CD
- VS Code
AI & AI-Assisted Engineering
- GitHub Copilot
- OpenAI
- Claude Skills
- MCP
- Spec Kit
- RAG
- Agentic AI
Core technologies are learned by building. Supporting tools and emerging AI technologies are covered at a practical level, so you understand where they fit and how to work with them.
Learn from someone who builds
Hi, I'm Mukunda
I'm a full-stack developer, frontend architect, technology educator, and co-founder with 14+ years of experience building software and mentoring developers. I've trained 500+ students in software development, with a focus on practical skills and strong engineering foundations.
My teaching philosophy is simple: understand first, then learn, then build. This program is built around that idea—helping developers understand the why behind the technology, develop independent problem-solving skills, and use AI effectively without losing the engineering thinking behind the work.
This program is designed for working professionals who want to upgrade their
software engineering and full-stack development skills; junior frontend developers with around
1–6 years of experience who want to become stronger full-stack engineers; and junior backend
developers who want to strengthen their frontend, system design, and end-to-end application
development skills.
It is especially suited for developers who want to understand how modern
software is designed, built, deployed, and developed effectively with AI.
Knowing basic programming concepts is helpful, such as variables, functions,
conditions, loops, and basic problem-solving. However, you don't need to be an expert or
already know the technologies covered in the program.
We cover the required fundamentals as
part of the course and build from there.
The program runs for 120 days and follows a structured learning journey covering software engineering foundations, problem-solving and DSA, frontend and backend development, databases, system design, AI-assisted development, production, and a final capstone project.
There are 4 classes each week, with each class lasting 2 hours.
The
detailed class schedule and batch timings will be shared before enrollment.
There are 8 hours of structured classes each week.
To get the most out of
the program, we recommend an additional 2–3 hours each week for practice and project
work.
Much of the practice follows a group project and sprint-based approach, where
you'll work with others, take on tasks, build features, review your work, and experience a
practical software development workflow.
You'll work across the full application stack, including React, JavaScript,
TypeScript, Python, FastAPI, Node.js, Express, PostgreSQL, SQL, Git, Docker, AWS, and AI-assisted
development tools.
The program goes deeper into the core technologies used to build
applications, while supporting frameworks, infrastructure tools, and emerging AI technologies are
introduced at a practical level.
Yes.
Python + FastAPI is the primary backend development path, where
you'll build a complete REST API.
You'll also learn Node.js + Express fundamentals
and build a smaller API to understand the ecosystem and how it fits into modern backend development.
Yes.
System Design is a dedicated module covering both Low-Level Design
(LLD) and High-Level Design (HLD).
You'll work with object-oriented design, SOLID
principles, design patterns, APIs, architecture, caching, load balancing, message queues,
concurrency, scalability, availability, and reliability.
AI is integrated throughout the development workflow rather than treated as a
separate tool.
You'll learn AI-assisted planning, implementation, debugging, testing,
refactoring, documentation, code review, and spec-driven development — while also exploring
LLM APIs, RAG fundamentals, and agentic AI concepts.
The focus is on using AI effectively
while keeping engineering decisions, quality, and verification in your hands.
Yes.
You'll build applications throughout the program and finish with
a complete capstone using React, FastAPI, and PostgreSQL.
The capstone includes
authentication, APIs, AI-assisted development, testing, deployment, documentation, and a final
demonstration.
You'll receive guidance during the learning sessions, feedback on practical
work, and structured review throughout the project-based learning process.
Capstone work
includes code review, testing, refinement, and feedback.
The goal is to help you develop practical software engineering capability —
from understanding requirements and solving problems to designing, building, testing, deploying, and
working effectively with AI.
The program does not guarantee a job, salary, or specific career
outcome.
Program fees and batch details will be shared when enrollment
opens.
Register your interest through the form or contact hello@humanplusai.academy to receive the latest program details.
Next step
Ready to become a
Full-Stack Software Engineer
for the AI era?
Batch details — dates, format and fees — are being finalised. Register your interest and be the first to know when enrollment opens.
No spam, no pressure. Just the details — the moment they're ready.