Associate Applied AI, Rotational Program, London

A structured learning path through coding interview preparation that brings together data structures and algorithms fundamentals, recursion and the pattern-based approach to coding questions in one order. It totals 77 chapters and 1,054 lessons, with quizzes, flashcards and a certificate. Use it when you have plenty of material but no clear plan for what to study first.

• Job search
• DSA
• Career

A bundle of five company-specific question courses covering the problems most often reported from Meta, Microsoft, Amazon, Google and Oracle coding rounds, each split into easy, medium and hard sets with worked solutions. It suits candidates who already know the core patterns and have a loop booked at one of these companies, and want to rehearse on the questions those interviewers are known to ask.

• Job search
• DSA
• Career

On-demand mock interviews with an AI interviewer for coding and system design rounds. It asks questions, follows up on your reasoning the way a real interviewer would, and ends with detailed feedback and a custom improvement plan. It suits software engineers preparing for technical interviews who want to practise whenever they are free and repeat sessions until their answers feel natural.

• AI
• Job search
• Career

A course on AI system design interviews, from classic ML systems such as recommendations, ranking and fraud detection to LLM serving costs, RAG, generative AI products and agentic systems, with a repeatable framework and full case studies. It takes about 20 hours across 9 chapters. It suits engineers who can write code and know what a model, an API and a database are, and are facing design rounds that now include AI.

• AI
• System design
• Job search

A six-stage path into paid remote AI data work, with a version for data annotation and one for AI trainers. It covers why models need people, the honest picture of pay, project gaps and scams, the guideline and quality skills platforms test, getting accepted, getting paid and keeping records, and moving up into reviewer, evals, data or ML roles. It suits students and graduates who want flexible remote income and read instructions carefully.

• Career
• AI
• Remote work
• Job search

A revision reference for paid AI data work, in 9 chapters and 64 to 66 concepts per edition: what labels, demonstrations, preference data and evals are, the honest picture of pay and contractor work, scam red flags, the guideline and quality skills tests check, annotation types and tools or the AI trainer's craft, getting accepted, a platform comparison, getting paid and moving up. It follows the Sefism AI data and training work roadmap chapter by chapter.

• Career
• AI
• Remote work
• Job search