📕 Hard Level - Advanced Track

📕 Hard Level - Advanced Track#

Welcome to the Hard Level! Master advanced topics and cutting-edge technologies.

What You’ll Learn#

  • Advanced Python patterns (decorators, generators, async)

  • Deep learning and neural networks

  • Natural language processing

  • Computer systems and theory

  • High-performance computing ⚡

  • GPU/CUDA programming 🎮

  • Competitive programming

  • Cybersecurity (CTF challenges)

Track Overview#

This level contains 11 comprehensive notebooks:

Core Advanced Topics (1-7)#

  1. Advanced Functions & Decorators - Metaprogramming patterns

  2. Generators and Iterators - Memory-efficient programming

  3. Algorithms and Complexity - Computational theory

  4. Deep Learning & Neural Networks - AI model building

  5. Advanced ML and NLP - Language understanding

  6. Computer Systems and Theory - How computers really work

  7. Project Ideas & Implementation - Production systems

Problem-Solving (8-9)#

  1. Classic Problems Collection - LeetCode and interview prep

  2. CTF Challenges - Hacker training and security

High-Performance Computing (10-11) ⚡ NEW!#

  1. Performance Computing - Optimization, profiling, Numba, async I/O

  2. CUDA & GPU Computing - Parallel programming, 1000x+ speedups

Time Commitment#

  • Estimated Time: 100-150 hours

  • Prerequisites: Medium Level or intermediate Python

  • Difficulty: ⭐⭐⭐⭐⭐

Content Statistics#

  • 539KB of comprehensive material

  • 200+ exercises with solutions

  • 100+ quiz questions

  • 1,000+ code examples

  • Production-quality implementations

Special Features#

🆕 NEW in v2.0.0#

Notebook 10: Performance Computing (40KB)

  • Profile and optimize Python code

  • 10-100x speedups with NumPy and Numba

  • Multiprocessing and async I/O

  • Production optimization techniques

Notebook 11: CUDA & GPU Computing (38KB)

  • GPU architecture and CUDA

  • CuPy (NumPy for GPUs)

  • PyTorch GPU acceleration

  • Multi-GPU programming

  • Real-world GPU applications

Learning Path#

Fundamentals → Deep Learning → Systems → Performance → GPU Computing
     ↓              ↓             ↓           ↓            ↓
  (1-3)          (4-5)          (6)       (10)         (11)

Interview Prep#

Perfect preparation for:

  • ✅ FAANG interviews (Google, Meta, Amazon, Apple, Netflix)

  • ✅ Competitive programming

  • ✅ Cybersecurity careers

  • ✅ ML/AI engineering roles

  • ✅ High-performance computing positions

What’s Next?#

After completing Hard Level:

  • 🎯 Build production projects

  • 🎯 Contribute to open source

  • 🎯 Apply for senior engineering roles

  • 🎯 Specialize in GPU/HPC or ML/AI

Ready for the challenge? From Hello World to CUDA kernels starts here! 🚀

Contents