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Course Description

Good Old-Fashioned AI (GOFAI) is effective for many tasks but has limitations when dealing with complex data patterns. Neural networks (NN), inspired by the human brain, offer a powerful alternative by learning from data patterns and relationships. This course will introduce you to the foundations and architectures of neural networks, enabling you to train, evaluate, and optimize these models to improve performance. You will explore the impact of data volume and model complexity on predictions, ensuring you select the most suitable NN models for various business scenarios. The course also delves into ethical considerations, such as model bias and data privacy, to ensure responsible AI implementation.

By examining real-world applications and engaging in hands-on exercises, you will develop practical skills in configuring neural networks and evaluating their performance. This course will equip you with the knowledge to apply these techniques effectively and create an action plan to address ethical concerns, ensuring your AI projects are both effective and responsible.

You are required to have completed the following courses or have equivalent experience before taking this course: 

  • Creating Business Value With AI
  • Exploring Good Old-Fashioned AI
  • Leveraging Data for AI Solutions

Faculty Author

Lutz Finger

Benefits to the Learner

  • Optimize the configuration of a neural network
  • Evaluate the impact of data and complexity on model performance
  • Identify, create, and assess a neural network suitable for a specific business use case
  • Create an action plan for model bias and data privacy

Target Audience

  • Professionals seeking fundamental AI skill development
  • Product managers and leaders
  • Early-career AI specialists
  • Data scientists 
  • Tech enthusiasts
  • Entrepreneurs
  • Venture capitalists
  • C-suite leaders 
  • Innovators and design thinkers
  • Anyone interested in applying AI and automation in their industry 

Applies Towards the Following Certificates

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Cornell SC Johnson College of Business
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