Udemy - High-Frequency Trading Mastery - 100 Labs (C + + and Rust...

High-Frequency Trading Mastery: 100 Labs (C++ & Rust)

https://WebToolTip.com

Published 8/2026
Created by Dar Al Taqniya
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 112 Lectures ( 13h 24m ) | Size: 1.1 GB

From software developer to production HFT engineer by building a complete ultra-low latency trading platform.

What you'll learn
⚡ Architect deterministic ultra-low latency trading systems using modern C++ and Rust.
⚡ Build production-grade FIX gateways, market data handlers, and matching engines from scratch.
⚡ Master Linux performance engineering including NUMA, HugePages, CPU isolation, real-time scheduling, and kernel tuning.
⚡ Implement lock-free data structures, cache-aware memory layouts, custom allocators, and zero-allocation execution pipelines.
⚡ Design and optimize kernel-bypass networking using DPDK, hardware timestamps, multicast, and zero-copy packet processing.
⚡ Engineer enterprise-grade pre-trade risk controls, audit logging, regulatory compliance, and operational resilience.
⚡ Deploy observable, measurable, and production-ready infrastructure using Prometheus, Grafana, Ansible, and automated CI pipelines.
⚡ Analyze latency at microsecond precision using profiling, benchmarking, telemetry, and deterministic replay techniques.
⚡ Understand how modern exchanges, proprietary trading firms, and market makers engineer reliable electronic trading infrastructure.
⚡ Deliver a complete enterprise-grade High-Frequency Trading Platform during the 100-Lab Capstone project that demonstrates production engineering skills from ope

Requirements
❗ You should have
❗ 1. Basic programming knowledge in any language (C++, Rust, Java, Go, Python, or C)
❗ 2. Basic Linux command-line familiarity
❗ 3. Understanding of variables, functions, loops, and data structures
❗ 4. Curiosity about systems programming and performance engineering
❗ Recommended Software
❗ 1. Ubuntu Linux 24.04 LTS (or compatible Linux distribution)
❗ 2. Modern C++ compiler (GCC or Clang)
❗ 3. Rust Stable Toolchain
❗ 4. Visual Studio Code or CLion (optional)
❗ Recommended Hardware
❗ 1. 64-bit x86 CPU with virtualization support
❗ 2. 16 GB RAM minimum (32 GB recommended)
❗ 3. Quad-core processor or higher
❗ 4. SSD storage