$240 / month
Regular calls, per agreement
Unlimited Q&A via chat
Expect responses in 24 hours or less
Cancel anytime
One-off sessions with Hui Xiang
One-off sessions are a great option if you’re looking for specific advice on a certain topic.
Having a good portfolio on hand is key for any designer in the job market. Even if you're not looking for a new position right now, having an impressive portfolio that presenty your experience to future potential employers is always good to have. In this …
Having a good resume on hand when going on the job hunt is crucial, and will make your search a lot easier. Even if you're not looking for a new position right now, having an up-to-date CV that sells your experience to future potential employers …
Not sure about your newest design? Not sure if your code is as good as it can be? Portfolio site looking a bit, meh? In this session, a mentor will sit down with you, and give you some inputs to make your work better, be …
Hui Xiang Chua is a Data Science for Social Good fellow and has over six years of experience solving problems using data in the public service. Combining her passion for education, data, and tech, she was a recipient of the KDD Impact Program award for bringing data science into a high school curriculum. She is also the #VizforSocialGood local chapter leader for Singapore and runs a data science blog called Data Double Confirm that was recognised as 2018 Top 100 Data Science Resources on MastersInDataScience.com. She was previously an instructor with General Assembly and is based in Singapore.
5 out of 5 stars
5 out of 5 stars
very good
5 out of 5 stars
Hui is a fantastic mentor. Very knowledgable and friendly, and she has already transformed the way I go about my machine learning projects after only one week. Could not recommend her enough!
Notify me when Hui Xiang has new spots
We will send you a quick email if Hui Xiang has new open spots for mentorship, and only in that case!
Book an intro call with Hui Xiang
Connect with Hui Xiang in a quick call (usually under 30 minutes)
