Enhancing Python Performance

Our Enhancing Python Performance training course covers the following Modules.

Module 1: Profiling

• Measuring execution time
• CProfile
• Py-spy

Module 2: Concurrency

• Concurrency in Python
• Threading
• Asyncio
• Multiprocessing

Module 3: Improving performance

• Basic optimisations
• NumPy
• Numba
• JAX
• PyPy
• Cython

Our Enhancing Python Performance training course will benefit several individuals and organisations including but not limited to:

• Python Developers
• Data Scientists and Analysts
• Web Developers
• Scientific Computing Professionals
• Machine Learning Engineers
• Software Engineers
• System Administrators

Our Enhancing Python Performance training course contains the following:

• 1-day instructor-led training course
• Hands-on labs for enhancing practical skills
• One-on-one after-course instructor coaching
• Pre-reading
• Course Manual
• Quizzes
• Exercises

Our Enhancing Python Performance training course requires attendees to have experience at the level of our three-day Introduction To Python training course.

There is no recommended reading for our Enhancing Python Performance training course.

Enhancing Python Performance Exam:

• Format: Multiple Choice
• Questions: 40
• Pass Mark: 70%

Attendees may enjoy our four-day Advanced Python: Best Practices And Design Patterns training course.

Our four-day Advanced Python: Best Practices And Design Patterns training course will teach you the importance of Advanced Python programming and the accompanying concepts and methods of Best Practices and Design Patterns. Understand the methods and following the principles of this course will help you write efficient, maintainable, and scalable code.

• Best practices in advanced Python programming refer to a set of guidelines and recommendations that experienced Python developers follow to write high-quality code. These practices encompass various aspects of coding style, organisation, error handling, testing, documentation, and performance optimisation.

• Design patterns, on the other hand, are reusable solutions to common software design problems. They provide a blueprint or template for solving recurring issues in software architecture and design.

Our Enhancing Python Performance training course offers several benefits to individuals and organisations including but not limited to:

• Improved Code Performance: The training equips participants with the knowledge and skills to identify and address performance bottlenecks in Python code.
• Faster Execution: Through the course, participants learn various strategies to optimise computations, reduce redundant calculations, and leverage efficient data structures and algorithms.
• Resource Efficiency: Participants learn techniques for optimising memory usage, reducing unnecessary object creation, and managing system resources effectively.
• Scalability and High-Load Handling: By understanding parallel processing, concurrency, and asynchronous programming techniques, participants can develop Python applications that can efficiently handle high user loads and scale with increasing demands.
• Enhanced User Experience: Faster and more responsive applications result in an improved user experience
• Increased Productivity: Optimised code execution leads to faster development cycles and reduced time spent on code optimisation and troubleshooting.
• Competitive Advantage: Companies and developers who have undergone enhancing Python performance training gain a competitive edge by delivering high-performance applications.
• Knowledge and Skill Enhancement: Participants acquire in-depth knowledge and skills in performance optimisation techniques specific to Python.
• Access to Optimisation Tools and Libraries: The training often introduces participants to various optimisation tools, libraries, and frameworks available in the Python ecosystem.
• Network and Collaboration Opportunities: Participating in the training course provides opportunities to connect with like-minded professionals, trainers, and experts in the field.