Skip to main content
CodeSparring

Learn

Every lesson, on one page

All 364 CodeSparring lessons, grouped by course and level. Each one is free to read: the explanation, the worked example, and both exercise prompts are open to everyone. Sign in when you want to run your answer and have it graded.

Python

5 levels, 79 lessons

Level 1: Foundations

Reference-style basics: variables, types, loops, and functions.

Collections

Level 2: Idioms

Comprehensions, generators, classes, dataclasses, decorators, and the standard-library idioms for dates, text, files, and APIs.

Talking to Services

Level 3: Patterns

The production-shaped syntax: modules, imports, and working across real files.

Project Structure & Packaging

Working across files

Level 4: Engineering

Advanced OOP, decorators, concurrency, async, profiling, and packaging.

Advanced OOP & Design Patterns

Level 5: Judging Code You Did Not Write

Read it, break it, test it, repair it. The review skills that decide what ships.

SQL

6 levels, 77 lessons

Level 1: SQL Foundations (Reading Source Data)

SELECT, WHERE, ORDER BY, types: querying raw source tables the way a DE does on day one.

Module 1.1: Projecting Columns from a Source Table

Module 1.3: Shaping the Result Set

Module 1.4: Types, Casting, Strings, and Dates

Level 2: Aggregation & Joins (Combining Source Data)

Aggregates, GROUP BY/HAVING, every join flavor, subqueries, CTEs: building metrics.

Module 2.1: Aggregation and Grouping

Module 2.3: Set Operations and Subqueries

Module 2.4: Readability and Conditional Logic

Level 3: Data Modeling & Schema Design

DDL, keys, constraints, and normalization: designing schemas the database enforces.

Module 3.1: DDL, Types, and Loading Data

Module 3.4: ER Modeling, Relationships, and Indexes

Module 3.5: Dimensional Modeling Introduction

Level 4: Data Engineering with SQL

Window functions, recursive CTEs, SCD, idempotent merge, data-quality: warehouse transforms.

Module 4.2: Recursive CTEs

Module 4.4: Pipeline Correctness

Module 4.5: Quality, Performance, and Capstone

Level 5: Advanced & Company-Specific SQL for DE Interviews

Rehearse the four rounds of a Data Engineering loop as graded SQL: the power screen, the modeling round, the pipeline round, and the system-design round.

Level 6: Cloud & Data Engineering Foundations

Learn the platform your SQL runs on: object storage, columnar files, partitioning, and distributed pipelines, the way a DE interview asks about them. It is beginner-friendly and can be started right after Level 2, since its graded queries lean on GROUP BY and joins.

System Design

12 levels, 208 lessons

Level 0: Interview & Communication Method

Run a system-design round like a senior: scope, estimate, structure the walkthrough, and drive tradeoffs.

Level 1: Foundations & Mental Models

The networking, API-contract, and performance fundamentals every later design assumes.

Level 2: Data Storage & Modeling

Relational vs NoSQL, storage engines, indexing, and modeling for access patterns.

Blob Storage & Choosing a Store

Level 3: Scaling the Data Tier

Replication, sharding, caching, CDN/search, and keeping derived data in sync at scale.

Level 4: Scaling Compute & Traffic

Stateless scale-out, load balancing, gateways, rate limiting, autoscaling, and overload protection.

Level 5: Distributed Systems Core

CAP/PACELC, consistency, clocks, consensus, distributed transactions, and failure handling.

Level 6: Asynchronous & Event-Driven Systems

Messaging models, Kafka and the log, delivery guarantees, stream processing, and schema governance.

Level 7: Reliability, Resilience & Operations

SLOs and error budgets, observability, resilience patterns, redundancy and multi-region DR, and safe deploys and chaos.

Level 8: Security, Privacy & Multi-tenancy

Authentication and identity, authorization and tenancy, encryption and secrets, abuse and perimeter defense, and privacy, compliance, and audit.

Level 9: Modern Architecture & Delivery

Service architecture, containers and orchestration, serverless and edge, delivery and FinOps, and data-intensive analytics.

Level 10: Applied Case Studies

The full-length 'design X' interviews: foundational building blocks, social and feed, geo and media, storage and infra systems, and commerce, money, and analytics.

Level 11: Specialized & Frontier Systems

The frontier: ML systems, LLM and GenAI infrastructure, real-time analytics and globally consistent data, and IoT, edge, and time-series.