Python Full stack Bootcamp with DSA & System Design

You can write idiomatic Python code, build robust object-oriented modules, and manage virtual environments reliably.

1. Python syntax and data types90 min
   • lists, dictionaries, and sets
   • list comprehensions and generator expressions
   • type hinting with typing module
2. Functions, modules and OOP2 hrs
   • magic methods (__init__, __str__)
   • inheritance and method resolution order
   • package structure and imports
3. Files, errors and testing2 hrs
   • context managers with 'with' statement
   • custom exception classes
   • Pytest test runner basics
4. Virtual environments and tooling90 min
   • venv and pip package management
   • requirements.txt vs pyproject.toml
   • ruff linter and black code formatter
5. Writing clean, readable Python90 min
   • PEP 8 style guidelines
   • docstrings and type annotations
   • refactoring procedural code into objects
6. Git and GitHub workflow2 hrs
   • git branch, merge, and rebase
   • pull request workflows
   • resolving merge conflicts

Hands-on project: Build a command-line expense tracker in Python that persists transactions to disk, validates inputs with custom exceptions, and includes a full Pytest suite with over 90 percent coverage.

You can build responsive React single-page applications that consume REST APIs and manage complex client-side state.

1. HTML, CSS and responsive layout2 hrs
   • semantic HTML5 elements
   • CSS Flexbox and Grid layouts
   • Tailwind CSS utility classes
2. Modern JavaScript essentials2 hrs
   • arrow functions and destructuring
   • promises and async/await syntax
   • ES modules import/export
3. React components and hooks2 hrs
   • functional components and props
   • useState and useEffect hooks
   • custom hooks creation
4. Consuming APIs from the UI90 min
   • Fetch API and Axios configuration
   • handling loading and error states
   • bearer token injection in request headers
5. Forms, state and routing2 hrs
   • controlled components and form validation
   • React Router DOM configuration
   • client-side route protection
6. Connecting front-end to back-end90 min
   • CORS handling in development
   • environment variables with Vite
   • API client service modules

Hands-on project: Build a dashboard interface in React with Vite and Tailwind CSS that fetches analytics from an API, renders dynamic charts, and handles user authentication state.

You can build robust server-side web applications using Django models, views, templates, and built-in authentication.

1. Django project structure90 min
   • django-admin startproject command
   • settings.py configuration
   • WSGI and ASGI application entry points
2. Models and the ORM2 hrs
   • ForeignKey, OneToOneField, and ManyToManyField
   • Django ORM querysets and filters
   • database migrations with makemigrations and migrate
3. Views, templates and URLs2 hrs
   • class-based views (ListView, DetailView)
   • Django template engine inheritance
   • URL dispatcher and path converters
4. Forms and the admin90 min
   • ModelForm validation
   • admin site customization
   • inline model admin panels
5. Authentication2 hrs
   • Django built-in user model and groups
   • login, logout, and password hashing
   • login_required decorators and mixins
6. Clean project organisation90 min
   • splitting settings into base, local, and production
   • service layer pattern in Django
   • reusable app architecture

Hands-on project: Build a content management web app with Django featuring custom user models, relational database tables, administrative dashboards, and secure session authentication.

You can design and build high-performance REST APIs using Django REST Framework and asynchronous FastAPI endpoints.

1. Django REST Framework2 hrs
   • APIView and ModelViewSet classes
   • pagination and filtering backends
   • custom permission classes
2. Building APIs with FastAPI2 hrs
   • FastAPI app instance and path operations
   • Pydantic v2 data validation models
   • dependency injection system
3. Serialisers and schemas90 min
   • ModelSerializer fields and validation
   • nested serializers
   • Pydantic model validation errors
4. Auth and permissions90 min
   • JWT authentication with SimpleJWT
   • OAuth2 password bearer in FastAPI
   • role-based access control checks
5. API documentation (OpenAPI)90 min
   • Swagger UI and ReDoc configuration
   • customizing OpenAPI schema metadata
   • response status codes and error payloads
6. Versioning and best practices90 min
   • URL path and header versioning
   • rate limiting with Django-Ratelimit
   • idempotency keys in API requests

Hands-on project: Develop a dual-API service featuring a DRF backend with token authentication and a FastAPI asynchronous microservice for real-time telemetry data processing.

You can optimize relational database queries, implement Redis caching, and execute background tasks using Celery and WebSockets.

1. Relational modelling and SQL2 hrs
   • PostgreSQL database configuration
   • complex JOINs and aggregations
   • EXPLAIN ANALYZE query planning
2. Queries, joins and indexing2 hrs
   • select_related and prefetch_related in Django
   • B-tree and GIN indexes
   • preventing N+1 query problems
3. Caching with Redis90 min
   • Redis key-value store operations
   • Django cache backend integration
   • cache invalidation strategies
4. Background jobs with Celery2 hrs
   • Celery worker configuration
   • defining asynchronous tasks
   • task retries and error handling
5. Realtime with WebSockets90 min
   • ASGI server setup with Uvicorn
   • Django Channels consumers and routing
   • broadcasting messages to groups
6. Scheduling tasks90 min
   • Celery Beat periodic tasks
   • cron job scheduling equivalents
   • monitoring background task queues

Hands-on project: Implement an asynchronous notification pipeline using Celery, Redis as a message broker, and Django Channels for real-time WebSocket client updates.

You can analyze algorithm complexity and solve foundational array, string, and hash map problems efficiently in Python.

1. What an algorithm is and why efficiency matters (Python)90 min
   • measuring execution time with time module
   • memory footprint of Python objects
   • worst-case vs average-case analysis
2. Big-O time & space complexity, in plain language2 hrs
   • O(1), O(N), O(N log N), and O(N^2) growth
   • dropping constants and lower-order terms
   • auxiliary space complexity analysis
3. Arrays and strings2 hrs
   • Python lists memory allocation
   • string immutability and slicing
   • in-place array manipulation
4. Hashing: maps and sets2 hrs
   • hash functions and collision handling
   • Python dict and set internals
   • frequency counting patterns
5. The two-pointer and sliding-window patterns2 hrs
   • left and right pointer convergence
   • fixed and dynamic sliding windows
   • subarray sum optimization
6. Your first guided coding problems90 min
   • Two Sum and Valid Anagram implementations
   • debugging edge cases with print statements
   • writing clean submission code

Hands-on project: Solve 25 curated LeetCode problems covering two pointers, sliding windows, and hash maps in Python, with accompanying unit tests verifying time and space complexities.

You can implement linked lists, stacks, queues, and search algorithms to solve complex data-manipulation interview questions.

1. Linked lists, explained simply2 hrs
   • singly and doubly linked list nodes
   • pointer manipulation techniques
   • fast and slow pointer cycle detection
2. Stacks and queues2 hrs
   • LIFO and FIFO data access
   • implementing stacks using lists and collections.deque
   • monotonic stack pattern
3. Recursion made intuitive2 hrs
   • base cases and recursive steps
   • call stack visualization
   • tail recursion optimization concepts
4. Binary search90 min
   • search space reduction on sorted arrays
   • handling duplicates and boundary conditions
   • binary search on answer range
5. Sorting algorithms and when to use them90 min
   • merge sort and quicksort mechanics
   • Python's Timsort algorithm
   • stability in sorting
6. Choosing the right data structure (guided practice)90 min
   • matching problem constraints to data structures
   • time-space trade-off decisions
   • mock coding practice

Hands-on project: Implement a custom LRU Cache data structure backed by a doubly linked list and hash map in Python, passing comprehensive edge-case test suites.

You can traverse trees, explore graphs, and solve optimization problems using dynamic programming techniques.

1. Trees and binary search trees2 hrs
   • binary tree node structure
   • BST insertion and search properties
   • tree depth and height calculation
2. Tree traversals (DFS & BFS)2 hrs
   • pre-order, in-order, and post-order traversals
   • level-order traversal using queues
   • recursive vs iterative traversal approaches
3. Graphs and how to search them2 hrs
   • adjacency list and matrix representations
   • Breadth-First Search and Depth-First Search
   • detecting cycles in directed graphs
4. Dynamic programming from first principles2 hrs
   • overlapping subproblems and optimal substructure
   • memoization (top-down) approach
   • tabulation (bottom-up) approach
5. Common interview patterns90 min
   • Knapsack and coin change problems
   • longest increasing subsequence
   • backtracking state space trees
6. Company-style problem sets and mock rounds2 hrs
   • timed coding challenge simulations
   • explaining solutions clearly under interview conditions
   • code review and optimization feedback

Hands-on project: Build an algorithmic pathfinding visualizer and solver in Python implementing BFS, DFS, and Dijkstra's algorithm on weighted grid graphs.

You can decompose monolithic applications into communicating microservices using REST and asynchronous message brokers.

1. Monolith vs microservices, in plain terms90 min
   • coupling and cohesion in software architecture
   • scaling monoliths vs scaling services
   • organizational drivers for microservices
2. Splitting an application into services (Domain-Driven Design)2 hrs
   • bounded contexts and domain entities
   • identifying service boundaries
   • database-per-service pattern
3. How services communicate: REST and async messaging2 hrs
   • synchronous HTTP communication with httpx
   • asynchronous event publishing
   • eventual consistency patterns
4. Message queues and the API gateway2 hrs
   • RabbitMQ exchange and queue bindings
   • API gateway routing with Nginx
   • request aggregation at the gateway
5. Caching, resilience and circuit breakers2 hrs
   • circuit breaker pattern with pybreaker
   • retry with exponential backoff
   • distributed caching strategies
6. Deploying and testing microservices90 min
   • contract testing with Pact
   • service discovery basics
   • distributed logging across services

Hands-on project: Refactor a monolithic e-commerce application into independent FastAPI and Django microservices communicating via RabbitMQ message queues and an API gateway.

You can design extensible, maintainable codebases applying object-oriented design principles and classic design patterns.

1. What 'design' really means for code90 min
   • managing change and reducing technical debt
   • coupling and cohesion metrics
   • code readability and extensibility
2. Object-oriented thinking90 min
   • encapsulating behavior alongside state
   • composition over inheritance
   • interfaces and abstract base classes in Python
3. SOLID principles in plain English2 hrs
   • Single Responsibility and Open-Closed principles
   • Liskov Substitution and Interface Segregation
   • Dependency Inversion principle
4. Common design patterns2 hrs
   • Singleton and Factory creational patterns
   • Adapter and Strategy structural patterns
   • Observer and Command behavioral patterns
5. UML and modelling a problem90 min
   • class diagrams and relationships
   • sequence diagrams for object interactions
   • translating requirements to class models
6. Designing a real object model (e.g., a booking or parking system)2 hrs
   • identifying core entities and use cases
   • handling concurrency and thread safety
   • writing unit tests for designed classes

Hands-on project: Design and implement a multi-threaded parking lot management system in Python adhering to SOLID principles and utilizing factory and strategy design patterns.

You can architect large-scale distributed systems, evaluate scaling bottlenecks, and design reliable cloud infrastructures.

1. The building blocks: servers, databases, caches, queues90 min
   • DNS resolution and CDN caching
   • stateless vs stateful application servers
   • message brokers and log aggregators
2. Load balancing and horizontal scaling2 hrs
   • round-robin and least-connection load balancing
   • Layer 4 vs Layer 7 load balancers
   • horizontal vs vertical scaling trade-offs
3. Database replication and sharding2 hrs
   • leader-follower replication and failover
   • horizontal sharding strategies and hash functions
   • CAP theorem and eventual consistency
4. Designing real systems (URL shortener, chat app, news feed)2 hrs
   • estimation calculations for bandwidth and storage
   • fan-out on write vs fan-out on read
   • handling real-time chat message delivery
5. Trade-offs, bottlenecks and reliability90 min
   • identifying single points of failure
   • rate limiting algorithms (token bucket, leaky bucket)
   • graceful degradation under high load
6. How to answer a system-design interview, step by step2 hrs
   • clarifying functional and non-functional requirements
   • high-level design sketching
   • deep diving into bottlenecks and scaling solutions

Hands-on project: Create a comprehensive high-level system design document and architecture diagram for a global URL shortening service supporting 100 million daily active users.

You can secure web applications against common vulnerabilities, write comprehensive test suites, and containerize services for deployment.

1. Unit and API testing with Pytest2 hrs
   • fixtures and parameterized tests in Pytest
   • mocking external API calls with unittest.mock
   • testing FastAPI endpoints with TestClient
2. OWASP security basics2 hrs
   • preventing SQL injection and XSS attacks
   • CSRF protection in Django
   • secure password hashing with bcrypt
3. Secrets and configuration90 min
   • environment variables with python-dotenv
   • managing secrets securely in production
   • preventing credential leakage in Git repositories
4. Containerising with Docker2 hrs
   • writing efficient multi-stage Dockerfiles
   • Docker Compose multi-service orchestration
   • volume mounting and network management
5. CI/CD pipelines90 min
   • GitHub Actions workflow syntax
   • automated testing on pull requests
   • linting and security scanning steps
6. Deploying to the cloud (AWS)2 hrs
   • provisioning an AWS EC2 instance
   • configuring Nginx reverse proxy and SSL with Certbot
   • deploying containerized apps with Docker on cloud VMs

Hands-on project: Write a multi-stage Dockerfile to containerize a FastAPI and Django application, secure endpoints against OWASP Top 10 vulnerabilities, and establish a GitHub Actions CI pipeline.

You can architect, build, test, and deploy a production-grade full-stack Python application while mastering technical interview communication.

1. Plan and build a full-stack capstone3 hrs
   • defining product requirements and user stories
   • database schema design and API contract drafting
   • setting up the repository and project boilerplate
2. Add DSA-backed features2 hrs
   • integrating optimized algorithms into backend services
   • caching query results for high-frequency endpoints
   • profiling memory and execution performance
3. Document your system design2 hrs
   • writing a comprehensive README.md
   • creating architecture diagrams
   • documenting API endpoints with OpenAPI specs
4. Coding + system-design mock interviews3 hrs
   • live coding interview simulation
   • system design whiteboard walkthrough
   • personalized feedback on communication and problem-solving
5. Resume, portfolio and LinkedIn2 hrs
   • tailoring resumes for Python full-stack roles
   • showcasing capstone projects on GitHub and LinkedIn
   • highlighting engineering impact and metrics
6. Certification and next steps90 min
   • completing final project reviews
   • receiving the Squarebrackets certification
   • ongoing career support and alumni network access

Hands-on project: Build, containerize, and deploy a full-stack production application featuring a React frontend, FastAPI/Django backend, PostgreSQL database, Redis cache, and CI/CD pipeline on AWS.