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Roadmaps + interview preparation

Learn with direction. Prepare with confidence.

A practical roadmap for learning technology. Follow focused learning paths and return to well-organized interview questions whenever you need to test your understanding.

Explore the roadmapPractice questions

Python Developer Roadmap

Follow the sequence from foundations to leadership. Every topic has a dedicated page that we will expand with practical lessons, examples, and projects over time.

01

Foundations

Build the tools and habits every Python developer needs first.

01Computer Fundamentals02Linux & Command Line03Bash Scripting04Git & GitHub
02

Programming

Move from Python syntax into confident, production-minded programming.

01Python Basics02Python Intermediate03Object-Oriented Programming (OOP)04Python Advanced05Testing (pytest)06Debugging & Profiling
03

Computer Science Core

Develop the reasoning skills behind efficient software and systems.

01Time & Space Complexity02Data Structures03Algorithms04Recursion & Backtracking05Dynamic Programming06Graph Algorithms07Operating Systems08Computer Networking09Computer Architecture (basics)
04

Databases

Learn how application data is modeled, queried, scaled, and maintained.

01Database Fundamentals02SQL03Advanced SQL04PostgreSQL05Query Optimization & Indexing06ORMs & Migrations07NoSQL08Vector Databases
05

Career Options

Understand the paths available and choose a direction deliberately.

01Career Tracks Overview02Choosing Your Track
06

Backend Development

Create secure, reliable APIs and services with the Python ecosystem.

01Web Fundamentals02FastAPI03Django04Flask05Authentication & Authorization06Web Security (OWASP)07Caching08Background Jobs & Task Queues09Message Brokers10API Design11Basic Frontend
07

DevOps & Cloud

Ship and operate software with repeatable infrastructure and observability.

01Docker02CI/CD03Cloud Fundamentals (AWS)04Web Servers05Kubernetes06Infrastructure as Code (Terraform)07Monitoring & Observability08Logging
08

Engineering Practices

Build the collaboration and quality practices that make teams effective.

01Clean Code & Refactoring02Code Reviews03Agile & Scrum04Technical Documentation05AI-Assisted Development
09

Software Design

Learn to shape maintainable codebases and communicate design decisions.

01SOLID Principles02Design Patterns03Low-Level Design (LLD)04UML & Diagrams05Clean & Hexagonal Architecture06Domain-Driven Design (DDD)07Python Performance Optimization
10

Architecture

Progress toward designing scalable, distributed, and resilient systems.

01High-Level Design (HLD) / System Design02Scalability & Load Balancing03Database Scaling04Distributed Systems05CAP Theorem & Consistency Models06Microservices & Event-Driven Architecture07Reliability Engineering08Security Architecture
11

Specializations

Choose one or more tracks for deeper work in data, AI, or platform engineering.

01Data Engineering02Data Science03Machine Learning04Deep Learning05LLMs, RAG & AI Agents06MLOps07SRE & Platform Engineering
12

Interview & Career Prep

Turn your learning into evidence, confidence, and strong interview performance.

01Resume & Portfolio02DSA Interview Practice03Machine Coding Rounds04Behavioral Interviews (STAR Method)05Mock Interviews06Salary Negotiation
13

Soft Skills

Strengthen the communication and ownership skills behind sustainable careers.

01Communication02Time Management & Ownership03Giving & Receiving Feedback04Working with Stakeholders
14

Senior Engineer Skills

Grow from executing tasks to leading technical outcomes across teams.

01Technical Ownership02Design Docs & RFCs03Architecture Decision Making04Production Support & Incident Management05Mentoring06Cross-Team Collaboration07Project Planning & Delivery08Product & Business Thinking09Cost Optimization10Compliance & Privacy Awareness
15

Beyond Senior

Explore leadership, architecture, consulting, and founder paths.

01Staff / Principal Engineer02Engineering Manager03Solutions Architect04Consultant / Specialist05Founder / CTO
16

AI Foundations

Build a practical mental model for modern AI, machine learning, and language models.

View section overview
01AI, ML & Generative AI Overview02How LLMs Work03Strengths & Limitations of AI04Choosing the Right Model
17

AI-Assisted Development

Use AI coding tools thoughtfully while keeping engineering judgment in the loop.

View section overview
01AI Coding Assistants02Prompting for Code03Reviewing & Verifying AI-Generated Code04Agentic Coding Workflows05Context Engineering
18

Building with AI

Learn the building blocks for reliable applications powered by language models.

View section overview
01Prompt Engineering02LLM APIs03Structured Outputs & Function Calling04Streaming Responses05Embeddings & Semantic Search06Vector Databases07RAG (Retrieval-Augmented Generation)
19

Agents & Automation

Understand the tools and patterns behind AI agents and workflow automation.

View section overview
01AI Agents02MCP & Tool Integration03Agent Frameworks04AI Workflow Automation
20

Production AI

Operate AI systems with measurable quality, reliability, performance, and cost.

View section overview
01LLM Evaluation02AI Observability & Monitoring03Cost & Latency Optimization04AI Reliability (Retries, Fallbacks, Rate Limits)05Deploying AI Apps
21

AI Security & Responsibility

Build AI features with privacy, security, safety, and responsible use in mind.

View section overview
01Prompt Injection & AI Security02Data Privacy & Sensitive Data03Guardrails & Safety04Compliance & Copyright Awareness
22

AI for Your Own Track

Choose the AI applications that fit your existing engineering path.

View section overview
01AI for Backend02AI for Frontend (Chat UIs, AI UX)03AI for DevOps (LLMOps)04AI for Testing & QA05AI for Data Engineering
23

AI Developer Track

Follow a deeper path for machine learning and AI engineering careers.

View section overview
01Math for AI02Machine Learning03Deep Learning04Transformers & Hugging Face05Fine-Tuning06Open-Source Models & Local Inference07MLOps08Multimodal AI09Multi-Agent Systems
24

Durable Skills for the AI Era

Strengthen the durable reasoning and learning habits that stay valuable as tools change.

View section overview
01Problem Decomposition02Critical Thinking & Code Review03Knowing When to Use AI and When Not To04Staying Current with AI05Building AI Side Projects