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
- 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.