PyTorch and Deep Learning for Decision Makers

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This course introduces you to PyTorch, one of the most popular deep learning frameworks, revealing how it can be used in your company to automate and optimize processes through the development and deployment of state-of-the-art AI applications. The course will help you identify the most common use cases of AI in the industry and how PyTorch's ecosystem and the commoditization of deep learning models can help you integrate them into your business. You will also learn why ensuring data quality is critical for the successful deployment of AI applications, and why getting the right data should be the top priority for any AI project. The course will discuss several trade-offs involved in choosing the appropriate model for the task at hand: build vs. buy, black vs. white box, and the risk and cost of delivering wrong predictions.

Finally, the course will discuss what happens after an AI application is deployed, addressing topics such as the inherent limitations of AI models, the mitigation of risks and vulnerabilities, and the challenge of data privacy.

This course targets technical and non-technical individuals interested in understanding how deep learning and PyTorch can be used to create business value through the development and deployment of AI applications.

LFS116x provides an overview of the AI landscape, focusing on PyTorch's ecosystem, while giving you a solid understanding of AI's current capabilities and it will help you make informed decisions about the development and maintenance of AI projects while taking in consideration key aspects related to data quality, model performance, and security.

What you will learn

• Discuss typical use cases of AI across industries

• Understand the role and importance of PyTorch in the current AI landscape

• Discuss the importance of data quality and its overall impact on the performance of a model or application

• Understand the trade-offs involved in developing or buying a model or application

• Identify the challenges and risks involved in deploying an application: biases, attacks, privacy issues, and more

Skills you learn

• Machine Learning
• Artificial Intelligence
• Data Quality
• PyTorch (Machine Learning Library)
• Deep Learning
• Vulnerability
• Business Valuation
• Applications Of Artificial Intelligence

Syllabus

• Welcome to LFS116x!
• Chapter 1. Why PyTorch? AI Applications in the Real World
• Chapter 2. Take Good C.A.R.E. of Your Data
• Chapter 3. "All Models are Wrong, but Some are Useful"
• Chapter 4. Challenges in Deploying and Maintaining Applications
• Final Exam (Verified Track only)

Auto Summary

Unlock the potential of AI in your business with the "PyTorch and Deep Learning for Decision Makers" course, crafted for both technical and non-technical professionals. Delve into the world of PyTorch, a leading deep learning framework, and discover how to harness its power to automate and optimize business processes. This engaging course offered by edX spans 15 hours and provides a foundational understanding of AI applications in the industry. Throughout the course, you'll explore the most prevalent AI use cases, learn about the PyTorch ecosystem, and understand the importance of data quality in deploying successful AI solutions. You'll also navigate the critical decisions involved in AI model selection, such as build vs. buy and black vs. white box models, while assessing the risks and costs associated with inaccurate predictions. Post-deployment considerations, including model limitations, risk mitigation, and data privacy challenges, are also thoroughly covered. By the end of this course, you'll be equipped with the knowledge to make informed decisions about AI projects, ensuring they add tangible value to your business. Perfect for those at the foundational level, this course is part of the Starter subscription, making it an accessible entry point for anyone looking to understand and implement AI through PyTorch. Join now to start your journey into the future of AI-driven business solutions.