| Python |
Interview_Python |
Python interview preparation — from core language features to advanced patterns |
| JavaScript / TypeScript |
Interview_JavaScript_TypeScript |
JS/TS interview preparation — modern ECMAScript, TypeScript type system, and runtime behaviour |
| Modern Web Technologies |
Interview_Web_Technologies |
Modern web platform interview prep — HTML5, CSS3, browser APIs, performance, and architecture |
| VHDL |
Interview_VHDL |
VHDL interview preparation — language features, synthesis patterns, and verification |
| Verilog |
Interview_Verilog |
Verilog interview preparation — RTL design, synthesis, and verification basics |
| SystemVerilog |
Interview_SystemVerilog |
SystemVerilog interview preparation — design, verification, UVM, and constrained random |
| Digital Hardware Design |
Interview_Digital_Hardware_Design |
Digital hardware design interview preparation — architecture, timing, FPGA/ASIC, and system design |
| C |
Interview_C |
C programming interview preparation — from fundamentals to systems programming |
| C++ |
Interview_CPP |
C++ interview preparation — modern C++ (C++17/20/23), templates, and idioms |
| Power Supply Design |
Interview_Power_Supply_Design |
Power supply design interview preparation — topologies, control, magnetics, and EMC |
| RTL Design for LLM Accelerators |
Interview_RTL_LLM_Accelerators |
RTL design and verification for LLM hardware accelerators — systolic arrays, attention engines, dataflow architectures, and FPGA/ASIC implementation |
| Agentic Frameworks (LangGraph, LangChain, CrewAI) |
Interview_Agentic_Frameworks |
Agentic AI frameworks interview preparation — LangChain, LangGraph, CrewAI, AutoGen, and the Model Context Protocol (MCP) |
| LangGraph |
Interview_LangGraph |
Interview preparation for LangGraph — graphs, state, persistence, tools, multi-agent patterns, streaming, and human-in-the-loop. |
| Transformer Architecture |
Interview_Transformer_Architecture |
The Transformer architecture interview preparation — from Attention Is All You Need through modern LLM architectures |
| Agentic AI |
Interview_Agentic_AI |
Agentic AI concepts interview preparation — agent architectures, reasoning patterns, planning, tool use, evaluation, and safety |
| Digital Signal Processing |
Interview_DSP |
Digital Signal Processing interview preparation — theory, algorithms, and implementation for both software and hardware roles |
| Signal Integrity and Power Integrity |
Interview_SI_PI |
Signal Integrity and Power Integrity interview preparation — transmission lines, S-parameters, PDN design, high-speed interfaces, and measurement techniques |
| FPGA Design |
Interview_FPGA |
FPGA design interview preparation: architecture, timing, design techniques, debug and bringup |
| SoC Architecture |
Interview_SoC_Architecture |
Interview preparation — SoC architecture, IP integration, AMBA, NoCs, and verification |
| Embedded Systems |
Interview_Embedded_Systems |
Embedded systems interview preparation — bare-metal C, RTOS, communication protocols, debugging, and safety-critical system design |
| RISC-V ISA |
Interview_RISC_V |
RISC-V ISA interview preparation — instruction formats, extensions, privilege architecture, microarchitecture, and ecosystem tools |
| Machine Learning |
Interview_Machine_Learning |
Interview preparation — classical ML, deep learning fundamentals, training, and evaluation |
| Linear Algebra for AI / ML |
Interview_Linear_Algebra_AI |
Linear algebra interview preparation for AI / ML engineers — vectors, matmul, rank, SVD, attention, FFN up/down projections, RoPE, LoRA / MLA, gradients, backprop, optimisation geometry |
| PCB Design and Electronics |
Interview_PCB_Electronics |
Interview preparation — PCB design, schematic capture, layout, EMC, and bring-up |
| Cryptography |
Interview_Cryptography |
Cryptography interview preparation: symmetric/asymmetric encryption, hash functions, ECC, finite fields, and more |
| Agentic Engineering |
Interview_Agentic_Engineering |
Interview preparation — Agentic Engineering |
| DevOps |
Interview_DevOps |
Interview preparation — DevOps |
| Security Engineering |
Interview_Security_Engineering |
Interview preparation — Security Engineering |
| SoC Packaging |
Interview_SoC_Packaging |
Interview preparation — SoC Packaging |
| SoC Power Delivery |
Interview_SoC_Power_Delivery |
Interview preparation — SoC Power Delivery |
| AI Accelerator Architecture |
Interview_AI_Accelerator_Architecture |
Interview preparation — AI Accelerator Architecture |
| High Speed Serial Links for AI |
Interview_High_Speed_Serial_Links |
Interview preparation — High Speed Serial Links for AI |
| LPDDRx Layout |
Interview_LPDDRx_Layout |
Interview preparation — LPDDRx Layout |
| Computer Architecture |
Interview_Computer_Architecture |
Interview preparation for Computer Architecture: ISA, pipelines, OoO execution, memory hierarchy, parallelism, accelerators |
| Operating Systems |
Interview_Operating_Systems |
Interview preparation for Operating Systems: processes, scheduling, synchronisation, memory, filesystems, modern I/O |
| CUDA |
Interview_CUDA |
Interview preparation for CUDA and GPU programming: SMs, warps, memory, streams, optimisation |
| Low Power Design |
Interview_Low_Power_Design |
Interview preparation for Low Power Design: power physics, clock/power gating, DVFS, UPF, verification |
| Compilers |
Interview_Compilers |
Interview preparation — compilers, parsing, IR, optimisation passes, codegen, and runtime |
| Distributed Systems |
Interview_Distributed_Systems |
Interview preparation — distributed systems, consensus, replication, partitioning, and CAP |
| Networking |
Interview_Networking |
Interview preparation — networking fundamentals, TCP/IP, routing, sockets, and modern protocols |
| Rust |
Interview_Rust |
Interview preparation — Rust ownership, lifetimes, traits, async, and unsafe |
| Model Context Protocol (MCP) |
Interview_MCP |
Interview preparation — Model Context Protocol: JSON-RPC, primitives, transports, building servers |
| Algorithms |
Interview_Algorithms |
Algorithms interview preparation — from complexity analysis to dynamic programming |
| Data Structures |
Interview_Data_Structures |
Data Structures interview preparation — from arrays and linked lists to advanced tree and hash structures |
| Databases |
Interview_Databases |
Databases interview preparation — from SQL and schema design to storage engines and distributed databases |
| System Design |
Interview_System_Design |
System Design interview preparation — from scalability fundamentals to real-world case studies |
| Design Patterns |
Interview_Design_Patterns |
Design Patterns interview preparation — from GoF patterns to SOLID principles and architectural design |
| Software Testing |
Interview_Software_Testing |
Software Testing interview preparation — from TDD and unit testing to performance and security testing |
| API Design |
Interview_API_Design |
API Design interview preparation — from REST and GraphQL to authentication and API evolution |
| Concurrency and Parallelism |
Interview_Concurrency |
Concurrency and Parallelism interview preparation — from threads and synchronisation to async patterns and debugging |
| CI/CD |
Interview_CI_CD |
CI/CD interview preparation — from build pipelines and deployment strategies to supply chain security |
| Cloud Computing |
Interview_Cloud_Computing |
Cloud Computing interview preparation — from compute and storage to multi-region architecture and FinOps |
| Containers and Kubernetes |
Interview_Containers_Kubernetes |
Containers and Kubernetes interview preparation — from Docker internals to Operators and GitOps |
| Observability and SRE |
Interview_Observability_SRE |
Observability and SRE interview preparation — from the three pillars to SLOs, incident response, and chaos engineering |
| Technical Leadership |
Interview_Technical_Leadership |
Technical Leadership interview preparation — code review, technical decisions, mentorship, and behavioural scenarios for Senior/Staff SWE roles |
| NVIDIA GenAI LLMs Certification (NCA-GENL + NCP-GENL) |
NVIDIA_GenAI_LLMs_Cert_Prep |
Study and interview-prep portfolio for NVIDIA's NCA-GENL (Associate) and NCP-GENL (Professional) generative-AI certifications — notes, mock interviews, exercises, presentations. |