Building on the fundamental principles of data analytics, this course advances to modern machine learning techniques such as neural network, deep learning, and reinforcement learning as well as NLP and text analysis. Application activities will be structured to provide an introductory level of how machine learning techniques are applied to big data analytics. Learners should have a strong level of data analytics for this course. DAT 203 Predictive Modelling and Data Mining is recommended prior to registering in this course.
Saturday, January 14 - April 15: 1:00 p.m. - 4:00 p.m. (Virtual)
Location:
ONLINE
Instructor:
Quang Nguyen Luong
Notes:
This course is offered as a virtual classroom with classes held, as per the scheduled day/time. Classes will be held online, using a combination of synchronous, real-time, instructor led sessions, supplemented with asynchronous activities. You should expect to attend class at the same time, each week, although not every session will be a full 3 hours of live instruction. Rather, classes will provide learners the opportunity to apply what has been covered by your course facilitator. Laptop computer required; No class Feb 18, April 8. Please note registering after the course start date may delay course access and does not permit exceptions to coursework due dates, late textbook purchases, or the refund policy
Instructors
Quang Nguyen Luong
Quang Nguyen is a data scientist with experiences working for IBM Canada in Advanced Analytics and AI practice as well as IBM Quantum Computing Ambassador team. He also did several postdoc research in academic institutes such as Korean Astronomical and Space Institute, National Astronomical Observatory of Japan, Canadian Institute for Theoretical Astrophysics. He finished his post and undergrad in Europe.
