Concepts that move.
Animated tutorials across 10+ career tracks — Data Engineering, AI/ML, DevOps, Frontend, Backend, QA, and more. Every tutorial is a 3Blue1Brown-style animation with live sandboxes + AI Q&A.
80+ stacks across 10 career tracks.
Data Engineering
Spark, Kafka, Airflow, dbt — the modern data stack
Databases & Warehouses
SQL, PostgreSQL, Snowflake, BigQuery, and data lakes
AI / Machine Learning
LLMs, NLP, PyTorch, TensorFlow, vector databases
Programming Languages
Scala, Python, Go, Java for data & backend engineering
DevOps & SRE
Kubernetes, Docker, Terraform, monitoring, CI/CD
Frontend & Web
React, Next.js, Vue, Angular, CSS frameworks
Backend & API
APIs, microservices, message queues, serverless
Cloud Platforms
AWS, Azure, GCP — deploy, scale, manage
QA & Testing
Automation, performance testing, quality assurance
System Design & Architecture
Distributed systems, microservices, design patterns
Start watching.
View all →How Spark Repartitions a DataFrame Across 4 Executors
Kafka Consumer Groups & Partition Rebalancing Visualised
Spark AQE: Adaptive Query Execution Deep Dive
Building a Real-Time Pipeline with Kafka Streams
Window Functions, CTEs & Slowly Changing Dimensions
Recursive CTEs and Hierarchical Data Models
Polars vs Pandas: Why Data Engineers Are Switching
Building RAG Pipelines with LangChain
Scala Implicits & Type Classes Demystified
Deploying Spark on Kubernetes with Operators
React Hooks: A Deep Dive for Production Apps
Building High-Performance APIs with FastAPI
End-to-End Testing with Playwright
How Spark's Catalyst Optimizer Rewrites Your Query Plan
Structured learning journeys.
Data Engineer — Junior to Senior
Kafka Streams in Production
Spark Performance Engineering
dbt + SQL Data Modelling
Full-Stack Web Developer
DevOps Engineer Path
AI/ML Engineer Track
Backend API Development
Earn verifiable certifications.
Complete a learning path, pass the assessment, get a verifiable PDF + public URL to share on LinkedIn.