From the course: Data-Centric AI: Best Practices, Responsible AI, and More
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Overview of the course objectives and agenda
From the course: Data-Centric AI: Best Practices, Responsible AI, and More
Overview of the course objectives and agenda
- [Lecturer] Before we dive into the exciting world of data-centric AI, let's go over the prerequisites of this course so we know that you're fully prepared. There are a few background skills you should have coming into the course. You need to have a solid understanding of Python programming, as we will be using Python in the code examples. If you don't have much experience in Python, I would recommend taking a course on Python for beginners from the library. In addition, you should be comfortable with basics of probability and statistics. We will be discussing things like data distribution, anomalies, and other statistical methods. Finally, you should have some experience with data science and machine learning terminologies, along with basic experience in data science modeling. Again, if you are new to the data science and AI journey, I would highly recommend taking a crash course here. All right, let's get started.
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