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 Duration 21 hours

Course Outline

Introduction to AI in Semiconductor Design Automation

  • Overview of AI applications in EDA tools
  • Challenges and opportunities in AI-driven design automation
  • Case studies of successful AI integration in semiconductor design

Machine Learning for Design Optimisation

  • Introduction to machine learning techniques for design optimisation
  • Feature selection and model training for EDA tools
  • Practical applications in design rule checking and layout optimisation

Neural Networks in Chip Verification

  • Understanding neural networks and their role in chip verification
  • Implementing neural networks for error detection and correction
  • Case studies on the use of neural networks in EDA tools

Advanced AI Techniques for Power and Performance Optimisation

  • Exploring AI techniques for power and performance analysis
  • Integrating AI models to optimise power efficiency
  • Real-world examples of AI-driven performance enhancement

EDA Tool Customisation with AI

  • Customising EDA tools with AI for specific design challenges
  • Developing AI plugins and modules for existing EDA platforms
  • Hands-on practice with popular EDA tools and AI integration

Future Trends in AI for Semiconductor Design

  • Emerging AI technologies in semiconductor design automation
  • Future directions in AI-driven EDA tools
  • Preparing for advancements in AI and the semiconductor industry

Summary and Next Steps

Requirements

  • Experience in semiconductor design and EDA tools
  • Advanced knowledge of AI and machine learning techniques
  • Familiarity with neural networks

Target Audience

  • Semiconductor design engineers
  • AI specialists within the semiconductor industry
  • EDA tool developers

Number of participants


Price per participant

Open Training Courses require 5+ participants.

Testimonials (2)

Getting people that never used AI some repetition in prompting and people that do use AI to consider different methods to using it.

Matthew Gay - Tarsus Pharmaceuticals
Course - Artificial Intelligence (AI) Overview

Working from first principles in a focused way, and moving to applying case studies within the same day

Maggie Webb - Department of Jobs, Regions, and Precincts
Course - Artificial Neural Networks, Machine Learning, Deep Thinking

Upcoming Courses

Advanced AI Techniques for Semiconductor Design Automation

2026-12-01 09:30
21 hours
Mirobod
33,896,260 UZS (Online)
36,896,260 UZS (Classroom)

Advanced AI Techniques for Semiconductor Design Automation

2026-12-15 09:30
21 hours
Mirobod
33,896,260 UZS (Online)
36,896,260 UZS (Classroom)

Advanced AI Techniques for Semiconductor Design Automation

2026-12-29 09:30
21 hours
Mirobod
33,896,260 UZS (Online)
36,896,260 UZS (Classroom)

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