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This AI course is intended for students to learn the essential foundations of AI and gain the fundamental data science skills through hands-on exercises.

• Understand the foundational math behind data science and machine learning: linear algebra,
  probability, and statistics.
• Be able to do data preprocessing with the Python libraries (NumPy and Pandas) for the execution
  of optimal machine learning models and data visualization.
• Explore supervised and unsupervised learning and be able to apply the most suitable machine
  learning algorithm.
• Learn to process textual data to derive highquality information from text and apply new insights to
  real-world business (NLP).
• Build and train deep neural networks, use the deep learning libraries such as TensorFlow and Keras to gain proficiency, as well as handle various deep learning techniques.

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