Python Concurrency for Senior Engineering Interviews Course Syllabus

Overview: This course is designed for senior Python engineers preparing for technical interviews and building high-performance applications. You'll master Python concurrency concepts including threads, multiprocessing, and asyncio through hands-on coding exercises and real-world problems. The curriculum spans approximately 12 hours of content, divided into seven comprehensive modules that progress from fundamentals to advanced patterns and interview challenges. Each module combines theory with practical implementation to ensure deep understanding and readiness for system design discussions.

Module 1: Introduction to Concurrency

Estimated time: 0.75 hours

• Concurrency vs. parallelism
• CPU-bound vs. I/O-bound tasks
• Context switching
• Compare execution times for concurrent vs. sequential function calls

Module 2: Multithreading in Python

Estimated time: 1.5 hours

• Thread creation, joining, and daemon threads
• Thread lifecycle management
• Using threading.Thread for parallel execution
• Building a multithreaded downloader

Module 3: Synchronization Primitives

Estimated time: 2 hours

• Locks and RLocks
• Semaphores and Conditions
• Events and thread coordination
• Implementing producer-consumer queues and reader-writer locks
• Avoiding race conditions

Module 4: Multiprocessing & the GIL

Estimated time: 2 hours

• Understanding the Global Interpreter Lock (GIL)
• Using the multiprocessing module
• Process pools and inter-process communication
• Building CPU-bound applications to bypass GIL limitations

Module 5: Asynchronous Programming with asyncio

Estimated time: 2 hours

• Event loops and coroutines
• Tasks and futures in asyncio
• Using async and await keywords
• Writing an asynchronous web scraper
• Simulating parallel API calls

Module 6: Advanced Concurrency Patterns

Estimated time: 1.5 hours

• Concurrency pipelines and fan-in/fan-out patterns
• Task cancellation and cleanup
• Deadlock prevention strategies
• Designing multi-stage data pipelines with asyncio and queues

Module 7: Concurrency Interview Challenges

Estimated time: 2.5 hours

• Classic concurrency problems: dining philosophers, bounded buffer
• Designing thread-safe counters
• Solving race condition scenarios
• Step-by-step solutions to interview-style challenges

Prerequisites

• Strong working knowledge of Python programming
• Familiarity with basic data structures and algorithms
• Experience with software engineering principles and system design

What You'll Be Able to Do After

• Explain concurrency vs. parallelism and identify appropriate use cases
• Implement efficient multithreaded and multiprocessing solutions in Python
• Write thread-safe code using synchronization primitives
• Develop high-performance asynchronous applications using asyncio
• Solve complex concurrency interview problems with confidence