Overall Python has a standard library in development, and a few for AI. Thus It has an intuitive syntax, basic control flow, and data structures. In turn It also supports interpretive run-time, without standard compiler languages. This makes Python especially useful for prototyping algorithms for AI.
Course Objectives.
All in all Learn the essential fundamentals of AI: the programming tools (Python, NumPy, PyTorch), the math (calculus and linear algebra), and the key techniques of neural networks (gradient descent and backpropagation).
By the end of the AI Programming with Python Fundamentals, students will have usable knowledge of the following:
- Overall Introduction to Python.
- Learn how to use all the key tools for working with data in Python: Jupyter Notebooks, NumPy, Anaconda, pandas, and Matplotlib.
- Thus Learn the foundational linear algebra you need for AI success: vectors, linear transformations, and matrices.
- Learn the foundations of calculus to understand how to train a neural network: plotting, derivatives, the chain rule, and more. See how these mathematical skills visually come to life with a neural network example.
- Furthermore Gain a solid foundation in the hottest fields in AI: neural networks, deep learning, and PyTorch.
None
5- 10 Days
