A comprehensive repository documenting technical growth from foundational programming concepts to advanced systems engineering, containing 2000+ files across multiple programming paradigms and infrastructure technologies.
This repository represents a self-directed learning journey in software engineering by a 17-year-old developer, with particular emphasis on systems architecture, backend development, and infrastructure management. The collection spans multiple programming languages, frameworks, and infrastructure technologies, with a focus on understanding underlying mechanisms rather than surface-level implementation.
Current Focus Areas:
- Backend API development with Spring Boot
- Container orchestration and infrastructure automation
- Systems design and distributed computing concepts
- Open-source contribution (2 merged pull requests)
Primary Proficiency:
- Python (foundational language, 3+ years)
- JavaScript/Node.js (deep understanding of runtime internals)
- Java (current focus with Spring Boot framework)
Working Knowledge:
- C++ (systems programming and performance optimization)
- Go (concurrent systems and microservices)
- Rust (systems programming, learning phase)
- SQL (database design and query optimization)
Backend Development
- RESTful API design and implementation
- Spring Boot ecosystem (current specialization)
- Node.js and Express.js frameworks
- Database integration and ORM patterns
Infrastructure & DevOps
- Docker containerization and multi-container orchestration
- Virtualization technologies (Proxmox VE, VirtualBox, VMware)
- Linux system administration (Arch, Debian, Ubuntu)
- Infrastructure as Code concepts
Computer Science Fundamentals
- Data structures and algorithms (100+ problems solved)
- Object-oriented programming principles
- Computer architecture (transistors to instruction sets)
- Language compilation models (interpreters, compilers, JVM)
Web Technologies
- Browser rendering engines (V8, DOM/CSSOM)
- Frontend frameworks (React)
- Asynchronous programming patterns
- Client-server architecture
Machine Learning Foundations
- Data manipulation with NumPy and Pandas
- Transformer architecture understanding
- Supervised and unsupervised learning paradigms
- Statistical analysis fundamentals
Coding-Project/ (2000+ files)
│
├── Programming Languages/
│ ├── Python/ # Core language studies
│ ├── JavaScript/ # Runtime internals and async patterns
│ ├── Java/ # Spring Boot and enterprise patterns
│ ├── C++/ # Systems programming
│ ├── Go/ # Concurrent programming
│ └── Rust/ # Memory safety and systems work
│
├── Projects/
│ ├── Web Applications/ # Full-stack implementations
│ ├── Containerized Apps/ # Docker-based deployments
│ └── Backend APIs/ # RESTful service development
│
├── System Design and System Thinking/
│ ├── Architecture Patterns/
│ ├── Design Principles/
│ └── Scalability Concepts/
│
├── Workspace and Environment/
│ ├── VM Configurations/
│ ├── Linux Systems/
│ └── Infrastructure Setup/
│
└── Programming W3Schools/ # Structured learning exercises
Technologies: Python, HTML/CSS, basic programming concepts
Developed foundational understanding of programming paradigms through Python, establishing knowledge of syntax, control structures, and basic algorithms. Early exposure to virtualization technologies provided initial infrastructure experience.
Technologies: JavaScript, Node.js, React, Browser APIs
Progressed to frontend and backend web development, gaining deep understanding of JavaScript runtime behavior, event loop mechanics, and browser rendering processes. Studied V8 engine internals, DOM/CSSOM construction, and asynchronous programming patterns.
Technologies: Various languages for algorithmic problem-solving
Completed 100+ algorithmic challenges focusing on fundamental data structures, time complexity analysis, and problem-solving patterns. Developed systematic approach to technical problem decomposition.
Technologies: Docker, Linux, Proxmox, virtualization platforms
Discovered strong aptitude for infrastructure engineering and systems configuration. Mastered container concepts including image layering, networking, volume management, and orchestration. Established personal lab environment with Proxmox for hands-on experimentation.
Technologies: Low-level architecture, compilation theory
Studied computer architecture from transistors through instruction set design. Investigated various compilation models: interpreted languages (Python, JavaScript), bytecode compilation (Java/JVM), direct compilation (C++, Go), and systems-level programming (Rust). Explored Boolean algebra, logic gates, and computational theory.
Technologies: Spring Boot, Java ecosystem, enterprise patterns
Currently specializing in enterprise-grade backend development using Spring Boot. Focus areas include dependency injection, JPA/Hibernate ORM, RESTful service design, and scalable application architecture.
Technologies: NumPy, Pandas, ML theory
Acquired foundational knowledge of machine learning concepts including transformer architectures, world models, and statistical learning theory. Studied practical data manipulation and analysis techniques.
Implemented multi-container applications using Docker and Docker Compose, demonstrating understanding of microservices architecture, container networking, and persistent storage solutions.
Technical Stack: Docker, Docker Compose, Linux
Key Learnings: Container orchestration, network isolation, volume management
Developing production-grade backend services with comprehensive CRUD operations, database integration, and authentication mechanisms.
Technical Stack: Spring Boot, Maven, JPA/Hibernate, MySQL
Focus Areas: API design, database modeling, security implementation
Self-hosted virtualization environment for development and testing, including VM provisioning, resource allocation, and network configuration.
Technical Stack: Proxmox VE, Linux, networking protocols
Purpose: Infrastructure learning, environment isolation, system administration
Built various web applications demonstrating full-stack capabilities, including real-time data integration and responsive design patterns.
Technical Stack: JavaScript, React, Node.js, REST APIs
Implementations: Weather applications, calculation utilities, data visualization
Merged Pull Requests:
- FastAPI Ecosystem - Contributed to API tooling and documentation
- Matplotlib (pyplot) - Documentation improvement for visualization library
Currently seeking additional contribution opportunities in systems tools, infrastructure projects, and developer utilities.
Source Code Execution Paths:
Interpreted Bytecode + VM Compiled Direct Compilation
(Python, JS) → (Java) → (C++, Rust) → (Go)
↓ ↓ ↓ ↓
Runtime JVM/CLR Assembly Machine Code
Interpretation Intermediate Instructions Direct
Representation
- Hardware Layer: Transistors, logic gates, CPU architecture
- Instruction Set: Assembly language, machine code
- System Software: Operating systems, runtime environments
- High-Level Abstractions: Programming languages, frameworks
- Application Layer: User-facing software and services
- JavaScript Engine (V8): JIT compilation, optimization pipeline
- Document Object Model (DOM): Tree structure and manipulation
- CSS Object Model (CSSOM): Style computation and application
- Rendering Pipeline: Parse → Style → Layout → Paint → Composite
- Master Spring Boot framework for enterprise application development
- Deploy production-ready full-stack applications
- Expand open-source contributions to infrastructure projects
- Deepen understanding of distributed systems patterns
- Secure backend engineering or DevOps internship
- Advance systems programming skills with Rust
- Study container orchestration with Kubernetes
- Develop reusable developer tooling
- Specialize in backend infrastructure and distributed systems
- Contribute meaningfully to major open-source infrastructure projects
- Build developer productivity tools
- Bridge expertise from hardware architecture to application design
- Understand fundamentals - Study underlying mechanisms and design decisions
- Hands-on experimentation - Build, test, break, and rebuild systems
- Documentation - Maintain comprehensive notes and code examples
- Iterative refinement - Continuous improvement through feedback and testing
- Knowledge sharing - Contributing to open-source and technical communities
Emphasis on proper configuration, system optimization, and thorough understanding of infrastructure components. Comfortable with extended configuration periods to ensure optimal system performance and reliability.
Prioritize depth of understanding over breadth of exposure. Focus on comprehending architectural decisions, trade-offs, and implementation details rather than surface-level feature usage.
Total Files: 2000+
Total Commits: 285+
Languages: 8+
Projects: 15+
DSA Problems: 100+
Open Source PRs: 2 (merged)
Years of Learning: 3+
Current Age: 17
Backend Development
- RESTful API design and implementation
- Database modeling and optimization
- Authentication and authorization systems
- Microservices architecture concepts
Infrastructure & Systems
- Container orchestration (Docker)
- Virtualization management (Proxmox, VMware)
- Linux system administration
- Configuration management
Computer Science Foundations
- Algorithm design and complexity analysis
- Object-oriented design patterns
- Computer architecture understanding
- Compilation and runtime systems
Development Tools
- Version control (Git, GitHub)
- Command-line proficiency (Bash, Vim)
- Development environments (VS Code, Linux)
- CI/CD concepts
GitHub: @SaisakthiM
LinkedIn: Connect with me
Open to: Backend engineering internships, open-source collaborations, technical discussions on systems architecture and infrastructure engineering.
Areas of Interest: Distributed systems, container orchestration, backend scalability, infrastructure automation, systems programming.
This repository serves as:
- Technical Portfolio - Demonstrating practical skills and projects
- Learning Documentation - Comprehensive record of technical growth
- Reference Library - Code examples and implementation patterns
- Open Source Base - Foundation for contributions and collaboration
- Knowledge Base - Structured collection of technical concepts
Grateful to the open-source community, particularly maintainers of FastAPI and Matplotlib projects, for providing opportunities to contribute and learn from production codebases. Special appreciation to educational content creators and technical documentation authors who facilitate self-directed learning.
Maintained by Saisakthi M • 2000+ files • 285+ commits • 8+ languages
Committed to understanding systems from transistors to distributed architectures