Software Engineer - Python 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 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 quick-revision companion to the DSA roadmap in nine chapters: complexity, arrays and hashing, linked lists, stacks and queues, recursion, sorting and searching, trees and heaps, graphs, coding patterns, dynamic programming and timed practice habits. Costs are stated for every structure and algorithm, in Python, Java, C++ or JavaScript editions. Use it after each roadmap stage and before a contest or coding round.

• Programming
• DSA
• Web

An eight-stage path from Big-O through arrays, hashing, recursion, trees, graphs, coding patterns and dynamic programming to timed, mixed practice, in Python, Java, C++ or JavaScript. It suits students and developers who can write code but freeze on problems with no obvious library call. By the end you can pick the right data structure, recognise common problem shapes and solve a medium problem in about 35 minutes with edge cases tested.

• Programming
• DSA
• Web

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