Principal Full Stack Developer

A foundations course that builds eleven core data structures from the ground up (arrays, matrices, stacks, queues, linked lists, trees and BSTs, hash tables, hash sets, heaps, graphs and tries), then covers sorting, searching, greedy and divide and conquer. Every chapter has practice problems, flashcards and an assessment. It suits students and career switchers whose foundations came from tutorials and who find pattern courses move too fast.

• Job search
• DSA
• CS fundamentals

A short text course on algorithm analysis: all five asymptotic notations, time and space complexity, best, worst and average cases, and three methods for recursive complexity including the master theorem. It suits students and self-taught developers who can write working code but freeze when an interviewer asks for the time and space complexity, or who want to understand why one solution is faster than another.

• Job search
• DSA
• CS fundamentals

A text-based course on how databases work underneath: storage and page layout, indexing, transactions and ACID, concurrency control, partitioning and sharding, replication and consistency, consensus and leader election, recovery, and the main NoSQL families. It ends with case studies designing the databases behind Quora, TikTok, Airbnb and Snapchat. It suits engineers who want their database choices in system design answers to be defensible rather than hand-waved.

• System design
• Databases
• Backend
• Job search

The second volume of Grokking the System Design Interview, aimed at senior and staff (L5/L6) design rounds. It works through harder case studies such as a payment system, flash sale, notification service, unique ID generator, Gmail, Reddit, Google Calendar and a code judging system, then goes beneath them with patterns like quorum, write-ahead logs and vector clocks and deep dives into Dynamo, Cassandra, Kafka, Chubby, HDFS, GFS and BigTable.

• System design
• Backend
• Job search

The companion to the MongoDB roadmap in JavaScript, Python and Java editions: documents and setup, CRUD and query operators, arrays and nested documents, schema design patterns, indexes and explain plans, the aggregation pipeline, MongoDB from your code, and transactions, replication and operations. Each of its 77 concepts is a line or two with the syntax and the classic mistake to avoid.

• Web
• Programming
• Backend
• Databases

An eight-stage roadmap for using MongoDB properly from JavaScript, Python or Java: documents and setup, queries and updates, arrays and nested documents, data modelling and schema design patterns, indexes and explain plans, the aggregation pipeline, MongoDB from application code, and transactions, replication and operations. It suits students and early-career engineers who want to model around their queries and prove performance with numbers.

• Web
• Programming
• Backend
• Databases