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Overview: The course content is divided into six parts, beginning with an introduction to Python programming and progressing to mathematical concepts needed for Artificial Intelligence, Data manipulation, and visualization libraries and techniques, an Introduction to Artificial Intelligence, and an in-depth exploration of Python frameworks and libraries required for the entire Artificial Intelligent agent development life cycle. Students learn about machine learning algorithms, deep learning concepts, neural network algorithms, natural language processing, computer vision, and reinforcement learning.
There are hands-on practical assignments to be given after each module, as well as tangible capstone projects completed after each part. It is assumed that the students have no prior experience with Python or AI, but understand the fundamentals of mathematics and statistics.
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