Teaching

Subjects currently handling at the Asian Institute of Management:

  • Mathematics for Data Science (MSc in Data Science program)

The module introduces the maths, including various techniques and formulations, necessary to implement data science models and algorithms as well as machine learning models. Students will familiarize themselves with the different concepts, notations, and rules where most data science techniques and models are based upon.

  • Machine Learning (MSc in Data Science program)

This course introduces students to the world of machine learning and predictive analytics. This will be a hands-on and an application-heavy module, looking at real-world data and cases from different fields. At the end of the course, students are expected to acquire needed machine learning skills involving both supervised and unsupervised learning. In addition, they will be exposed to the best practices in predictive analytics including how to properly evaluate models.

  • Deep Learning (PhD in Data Science program)

  • Deep Learning (MSc in Data Science program)

Students dive deeper into neural networks (NN), the bedrock of deep learning, and how variants are used for predictive analytics—from natural language processing to cancer detection (image processing) to predicting stock market performance. Students are tasked to construct their own single-layer artificial neural network in Python with numpy. This allows students to gain a deeper understanding of how neural networks work truly function. Participants are also introduced to other types of NNs including deep-NNs such as convolutional neural networks, recurrent neural networks, and GANs with Tensorflow/Keras, which are relevant packages/libraries in the field, among other tools. The course is hands-on and involves multiple real-world projects– business and/or industry-driven. The course culminates with students giving a public presentation of original and novel applications of deep learning methods.

  • Complexity Science (MSc in Data Science program)

  • Forecasting I and II (MSc in Innovation and Business program)

Subjects previously handled at the University of the Philippines Diliman:

  • Electromagnetic Theory (Physics 131 & 132)

  • Theoretical Mechanics (undergraduate [121, 122] , graduate [221] and advanced graduate level [212]);

  • General Physics (mechanics [71, 101, 71.1], electromagnetism[72, 72.1, 102], modern physics [73, 73.1], Physics and Astronomy for Pedestrians [10]);

  • Advanced methods in Experimental Physics (Physics 191 & 192);

  • Advanced methods in Computational Physics (Physics 212 & Physics 215)

  • Mathematical methods in Contemporary Physics (Physics 313)