Status: In Progress (Phase 1: Deep Code Quality & Runtime) Goal: Achieve demonstrable mastery across all four domains required of a Mid-Level Software Engineer.
This repository documents my structured learning path, practice code, and major projects focused on transitioning from Junior to Mid-Level standing by mastering DSA, System Design, and Operational Excellence.
| Domain | Topics (Key Focus) | Status | Next Major Focus |
|---|---|---|---|
| I. Technical Mastery & Code Quality |
DSA (Optimal Selection, Complexity |
🟢 Phase 1 Focus | Complete Language Deep Dive & start advanced Graph Algorithms (e.g., Dijkstra's, A*). |
| II. Architecture & System Design | System Design (Micro/Macro), Idempotency, Data Modeling (Normalization vs. Denormalization), Advanced Indexing, Scaling Principles (Statelessness, Horizontal Scaling). | 🟡 Up Next (Phase 2) | Design an API with Versioning and implement a Caching Strategy (Cache-Aside). |
| III. Tools, Infrastructure & Operations | Advanced Git (rebase -i, bisect), Observability (Metrics, Structured Logging, Tracing), Docker Optimization (Multi-stage Builds), CI/CD flow, Cloud Basics (VPC, EC2/Functions). |
🟠 Integrated | Practice using git bisect to debug a self-introduced bug; Implement distributed Tracing in a microservice demo. |
| IV. Professionalism & Teamwork | Code Review Excellence (Architectural Feedback), Task Decomposition (Epics |
🔵 Ongoing | Propose 3 viable technical trade-offs for a complex feature in the LEARNING_LOG. |
All formalized notes and concept deep dives are stored here.
- NOTES/I_Technical_Mastery/ - Deep dives into DSA, language runtimes, Complexity Analysis, and performance optimization.
- NOTES/II_Architecture_Design/ - Principles of API Design, System Scaling, data persistence, and communication patterns.
Isolated, self-contained examples to prove mastery of a single concept.
- PRACTICE/DSA_Solutions/ - Optimized solutions for common problems (DP, Graphs, Trees).
- PRACTICE/Concurrency_Patterns/ - Examples of channels in Go,
asyncioin Python, etc. - PRACTICE/Design_Patterns/ - Implementations of common patterns like Strategy, Factory, and Observer.
Full-stack or distributed applications designed to integrate multiple mid-level concepts (System Design, Observability, Scaling).
- PROJECTS/Project_01_Distributed_System/ - A system using Go (performant core) and a Message Queue, integrating Tracing and Structured Logging. (TBD)
A diary of weekly learning, challenges faced, and successful implementations.
Next Step: Dive into the Python GIL and JavaScript Event Loop to complete the foundational understanding of runtime environments, then move immediately to Advanced DSA (Graphs/Trees).