What will you learn in Python Concurrency for Senior Engineering Interviews Course
Master concurrency fundamentals in Python including threads, processes, async/await, and coroutines
Understand Python’s Global Interpreter Lock (GIL) and how it impacts multi-threaded performance
Implement thread-safe code using locks, semaphores, queues, and condition variables
Write high-performance concurrent programs using
asyncioand asynchronous I/OSolve real-world interview-style problems involving multithreading and parallel processing
Prepare for senior engineering interviews by practicing concurrency scenarios, code challenges, and design discussions
Program Overview
Module 1: Introduction to Concurrency
⏳ 45 minutes
Topics: Concurrency vs. parallelism, CPU-bound vs. I/O-bound tasks, context switching
Hands-on: Compare execution times for concurrent vs. sequential function calls
Module 2: Multithreading in Python
⏳ 1.5 hours
Topics: Thread creation, joining, and daemon threads; thread lifecycle
Hands-on: Build a multithreaded downloader and use
threading.Threadfor parallel execution
Module 3: Synchronization Primitives
⏳ 2 hours
Topics: Locks, RLocks, Semaphores, Conditions, Events
Hands-on: Implement a producer-consumer queue, reader-writer lock, and race condition avoidance
Module 4: Multiprocessing & the GIL
⏳ 2 hours
Topics: The Global Interpreter Lock, multiprocessing module, process pools
Hands-on: Build a CPU-bound app using multiprocessing to bypass the GIL limitations
Module 5: Asynchronous Programming with asyncio
⏳ 2 hours
Topics: Event loops, coroutines, tasks, futures,
await,asyncHands-on: Use
asyncioto write an asynchronous web scraper and simulate parallel API calls
Module 6: Advanced Concurrency Patterns
⏳ 1.5 hours
Topics: Pipelines, fan-in/fan-out, task cancellation, deadlock prevention
Hands-on: Design and implement a multi-stage data pipeline using asyncio and queues
Module 7: Concurrency Interview Challenges
⏳ 2.5 hours
Topics: Classic interview questions (e.g., dining philosophers, bounded buffer, thread-safe counter)
Hands-on: Solve concurrency-specific questions with detailed step-by-step solutions
Get certificate
Job Outlook
Senior Python Engineers with concurrency experience earn between $130,000–$180,000/year in the U.S.
High demand in industries like finance, real-time systems, cloud services, and backend engineering
Roles include Backend Developer, Distributed Systems Engineer, Performance Engineer, and SRE
Concurrency knowledge is essential for designing scalable, low-latency applications in production environments
Explore More Learning Paths
Sharpen your Python programming and concurrency skills with these carefully curated courses designed to help you tackle advanced coding challenges and excel in technical interviews.
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Applied Machine Learning in Python Course – Apply Python programming in machine learning projects, integrating concurrency knowledge for scalable data processing.
Related Reading
What Is Python Used For? – Explore Python’s versatility in software development, automation, and data science, highlighting why concurrency skills are crucial for advanced engineering roles.
Specification: Python Concurrency for Senior Engineering Interviews Course
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FAQs
- Strong understanding of Python basics is required.
- Familiarity with data structures like lists, dictionaries, and sets is recommended.
- Prior experience with object-oriented programming helps in grasping concepts faster.
- Beginners in Python may struggle; this course targets experienced developers.
- Practical coding experience is essential for following advanced concurrency examples.
- Multi-threading and multi-processing in Python.
- Asynchronous programming using
asyncioand coroutines. - Synchronization primitives like locks, semaphores, and queues.
- Performance optimization and avoiding race conditions.
- Real-world problem-solving patterns often asked in interviews.
- Includes coding exercises simulating real concurrency scenarios.
- Focuses on handling I/O-bound and CPU-bound tasks efficiently.
- Teaches performance profiling and debugging multi-threaded code.
- Provides best practices for writing safe and maintainable concurrent code.
- Skills can be applied to backend services, web servers, and parallel processing.
- Expertise in Python concurrency is highly valued in senior engineering roles.
- Demonstrated skills can increase eligibility for high-paying software positions.
- Prepares candidates for challenging coding interviews at top tech companies.
- Concurrency knowledge is applicable in backend, cloud, and data engineering roles.
- Hands-on projects and exercises strengthen resumes and portfolios.
- The course is not suitable for beginners or non-technical learners.
- Prior Python and programming experience is mandatory.
- Focuses on advanced concepts, coding patterns, and problem-solving techniques.
- Step-by-step examples guide experienced developers through concurrency challenges.
- Motivated professionals with Python experience can benefit significantly.
