Python is one of the powerful programming languages in the world which continues to grow now. We are offering two workshops, ‘Basic Python’ and ‘Deep Learning with Python’, to provide students with a solid understanding of programming using Python and how to implement artificial neural networks and deep learning methods using Python, with practical examples.
To allow more flexibilities for students, there will be two options on the class timetable which are afternoon class in January and evening class in March. In the evening class, recorded videos will be arranged while facilitators will interact with participants real-time. Students can join the class convenient to them.
Basic Python
This workshop, consists of five online sessions, aims at helping participants to build a solid foundation in Python programming. Application of Python’s libraries in data manipulation and data acquisition, storage and visualization will be covered. This workshop is also a good preparation for participants who are interested in advanced machine learning. Students have basic programming concepts are welcome to join.
Timetable 1 (Afternoon class)
Date: 18 Jan (Tue), 25 Jan (Tue), 8 Feb (Tue), 15 Feb (Tue), 22 Feb (Tue)
Time: 14:30 – 17:00
Details & Registration: click here
Timetable 2 (Evening class)
Date: 1 Mar (Tue), 8 Mar (Tue), 15 Mar (Tue), 22 Mar (Tue), 29 Mar (Tue)
Time: 18:00 – 20:30
Details & Registration: click here
Deep Learning with Python
Deep learning is a subfield of machine learning based on the application of artificial neural networks which are comprised of artificial neurons that stimulate biological neurons. The use of multiple layers of neurons allows a model to learn much more complicated features compared with classical machine learning algorithms, therefore it is widely used in difficult tasks such as computer vision and speech recognition.
The workshop, consists of five online sessions, will focus on working with an open source AI library named Tensorflow, developed by Google Brain, to build neural networks that handle image recognition, speech synthesis and advanced time series prediction. The workshop will also cover various optimization algorithms and regularization techniques for fine tuning a neural network that utilizes model performance.
Students have basic programming knowledge in Python are welcome to join.
Timetable 1 (Afternoon class)
Date: 27 Jan (Thu), 10 Feb (Thu), 17 Feb (Thu), 24 Feb (Thu), 3 Mar (Thu)
Time: 14:30 – 17:00
Details & Registration: click here
Timetable 2 (Evening class)
Date: 28 Feb (Mon), 7 Mar (Mon), 14 Mar (Mon), 21 Mar (Mon), 28 Mar (Mon)
Time: 18:00 – 20:30
Details & Registration: click here
