PATHS // PREPARATION_TRACKS
Learning Paths
Choose your target role and follow a structured preparation path. Each path is curated with the exact topics and problems you need for your specific interview loop.
Free tier: one learning path at a time.
AI Engineer
Focused preparation for AI and GenAI engineering roles. Heavy emphasis on LLM systems, RAG pipelines, and modern AI architecture.
0%
0 / 65 problems
120 hours estimated
4 categories
Python DSAML FundamentalsRAG PipelinesLLM ServingEmbedding Systems
Data Structures & AlgorithmsML TheoryML CodingGenAI & LLMs
Machine Learning Engineer
Complete preparation for ML Engineer roles at top companies. Covers DSA, system design, ML theory, ML coding, and ML system design.
0%
0 / 85 problems
142 hours estimated
5 categories
DSA FundamentalsSystem DesignML TheoryML CodingML System Design
Data Structures & AlgorithmsHigh-Level System DesignML TheoryML CodingML System Design
ML Infrastructure Engineer
Preparation for ML infrastructure and platform engineering roles. Combines system design with ML serving and data pipelines.
0%
0 / 70 problems
130 hours estimated
4 categories
Data PipelinesModel ServingFeature StoresGPU OrchestrationMLOps
Data Structures & AlgorithmsHigh-Level System DesignML System DesignGenAI & LLMs
Software Engineer (SDE)
Traditional software engineering interview preparation. Strong focus on DSA and system design with foundational ML knowledge.
0%
0 / 130 problems
180 hours estimated
3 categories
Arrays & StringsTrees & GraphsDynamic ProgrammingOOP DesignDistributed Systems
Data Structures & AlgorithmsLow-Level DesignHigh-Level System Design