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PyUVM Series 3: Python OOPs Basics

5 hours82 items Certificate
BestsellerSubtitlesEnglish
What you'll learn

5 skills you'll walk away with

Course content

82 items across 6 sections

45 lectures8 assignments5 hours total
Course details

Know what you're signing up for

Requirements
  • Fundamentals of Digital Electronics and Verilog
  • Completion of Python for VLSI Engineer P1, and P2 Course
Who this course is for
  • If you're excited about Python and DUT verification with Python, this is the place for you.
Why this course exists

This comprehensive course is designed to empower software engineers, developers, and verification engineers with advanced Python programming skills for effective Object-Oriented Programming (OOP) and hardware verification tasks. Participants will delve into the fundamentals of Python and explore advanced concepts, including classes, inheritance, copy mechanisms, randomization, inter-process communication with queues, and task synchronization with events. The course will also provide hands-on experience in building a verification environment, encompassing generators, drivers, monitors, and scoreboards for robust Design Under Test (DUT) verification. Key Topics Covered: Object-Oriented Programming (OOP) in Python: Understanding classes and objects Encapsulation, inheritance, and polymorphism Method overriding and operator overloading Copy Mechanisms: Shallow and deep copy in Python Best practices for efficient copying Copying complex data structures Randomization Techniques: Utilizing the 'random' module for pseudo-random number generation Randomizing data for diverse test scenarios Seed management for reproducibility Inter-Process Communication: Introduction to Python multiprocessing Communication using queues Synchronization and data exchange between processes Task Synchronization: Implementation of event-driven synchronization Coordinating tasks with events Avoiding race conditions and deadlocks Verification Environment: Designing a verification environment for a Design Under Test (DUT) Developing generators for stimulus creation Building robust drivers for interfacing with the DUT Monitoring and analyzing DUT behavior with monitors Scoreboarding techniques for result verification Hands-On Projects: Participants will engage in practical exercises and projects throughout the course, applying the learned concepts to real-world scenarios. This will include creating a complete verification environment for a sample DUT, incorporating OOP principles, copy mechanisms, randomization, and inter-process communication. By the end of this course, participants will possess advanced Python skills, enabling them to design and implement efficient and scalable verification environments for hardware designs, while incorporating best practices in OOP and software development. This course is ideal for professionals working in fields such as hardware verification who want to enhance their Python proficiency for building Class based Verification environment in Python.

Requirements

What you should know going in

  • Fundamentals of Digital Electronics and Verilog
  • Completion of Python for VLSI Engineer P1, and P2 Course
Description

Why this course exists

This comprehensive course is designed to empower software engineers, developers, and verification engineers with advanced Python programming skills for effective Object-Oriented Programming (OOP) and hardware verification tasks. Participants will delve into the fundamentals of Python and explore advanced concepts, including classes, inheritance, copy mechanisms, randomization, inter-process communication with queues, and task synchronization with events. The course will also provide hands-on experience in building a verification environment, encompassing generators, drivers, monitors, and scoreboards for robust Design Under Test (DUT) verification. Key Topics Covered: Object-Oriented Programming (OOP) in Python: Understanding classes and objects Encapsulation, inheritance, and polymorphism Method overriding and operator overloading Copy Mechanisms: Shallow and deep copy in Python Best practices for efficient copying Copying complex data structures Randomization Techniques: Utilizing the 'random' module for pseudo-random number generation Randomizing data for diverse test scenarios Seed management for reproducibility Inter-Process Communication: Introduction to Python multiprocessing Communication using queues Synchronization and data exchange between processes Task Synchronization: Implementation of event-driven synchronization Coordinating tasks with events Avoiding race conditions and deadlocks Verification Environment: Designing a verification environment for a Design Under Test (DUT) Developing generators for stimulus creation Building robust drivers for interfacing with the DUT Monitoring and analyzing DUT behavior with monitors Scoreboarding techniques for result verification Hands-On Projects: Participants will engage in practical exercises and projects throughout the course, applying the learned concepts to real-world scenarios. This will include creating a complete verification environment for a sample DUT, incorporating OOP principles, copy mechanisms, randomization, and inter-process communication. By the end of this course, participants will possess advanced Python skills, enabling them to design and implement efficient and scalable verification environments for hardware designs, while incorporating best practices in OOP and software development. This course is ideal for professionals working in fields such as hardware verification who want to enhance their Python proficiency for building Class based Verification environment in Python.

Who it's for

Who this course is for

  • If you're excited about Python and DUT verification with Python, this is the place for you.
Instructor

Taught by Kumar Khandagle

KK

Kumar Khandagle

Founder, Namaste FPGA · Mumbai, India

4.5 instructor rating60,000+ engineers34 courses15+ yrs silicon

15 years of production silicon — from high-frequency trading on Xilinx Alveo, to India's indigenous MRI machine, to training engineers at Mumbai University. Top 1K instructor on Udemy. Every course here comes from work he's actually shipped.

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$ 6.99One-time payment