Data Analyst II

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 browsable practice library of coding problems that can be filtered by pattern, data structure, difficulty and company, so you can drill exactly the weakness you found this week. Patterns include two pointers, sliding window, hash maps, stacks, backtracking and greedy algorithms, with company filters for Google, Meta, Microsoft, Amazon, Oracle and LinkedIn. Free to browse, with an in-browser editor and solutions.

• Job search
• DSA

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

A very large site of articles on data structures, algorithms and core CS subjects such as operating systems, DBMS, computer networks and OOP, usually with code in several languages, plus practice problems and paid courses. It is handy for revising a university topic or finding a worked example of a specific algorithm. Quality varies because much is community written, so cross-check anything surprising against a textbook or official documentation.

• DSA
• CS fundamentals
• Databases

MIT's full undergraduate algorithms course from Spring 2020, free on OpenCourseWare with lecture videos, notes, problem sets, quizzes and exams with solutions, taught in Python by Erik Demaine, Jason Ku and Justin Solomon. It covers data structures, sorting, hashing, trees, graph search, shortest paths and dynamic programming with the reasoning behind each, which is what lets the ideas transfer to new problems.

• DSA
• CS fundamentals
• Programming