Symbolic Connection Thu Ya Kyaw & Koo Ping Shung

We are back! For this episode, we discussed topics about generative AI. We actually used Google's Bard to generate the outline for this episode. It covers topics: What is generative AI? How does it work? What are some of the benefits of generative AI? Challenges of generative AI, the future of generative AI, and many more! Overall, this episode provides a comprehensive overview of this rapidly developing field. It could also explore the ethical implications of generative AI, and its potential impacts on society. Let us know what you think. You can reach us directly from our LinkedIn page.

Koo Ping Shung: https://www.linkedin.com/in/koopingshung/

Thu Ya Kyaw: https://www.linkedin.com/in/thuyakyaw/




---

Send in a voice message: https://podcasters.spotify.com/pod/show/symbolic-connection/message

It has been a while since we released an episode on this channel. Apologies, we were both busy with work and couldn't find a common dedicated time to record an episode. We also changed the intro and outro music. Let us know what you think?

In this episode, Koo Ping Shung and I discussed the nitty gritty things about AI ethics. We also voiced our opinions on the different aspects of AI ethics and whether having a governing body to control the ethics aspect of AI is a good thing or not. Have a listen!

If you have any feedback, you can send them our way from here: https://forms.gle/cdgUUtsmdnsrNUPMA

Want to appear in our podcast episode? Let us know from here: https://forms.gle/g9xoC12eEUSA6vhdA


---

Send in a voice message: https://podcasters.spotify.com/pod/show/symbolic-connection/message

This week, we invited Kelvin Tham, an MLOps Data Program Manager at ViSenze - AI for Visual Commerce. Kelvin has a wide range experience across ML Ops, data analytics, and business process improvement. He is currently working on design, development and shipping of ML Ops model management.

In this episode, he shared about how is it like to be working at an AI startup company and his war stories of wearing multiple hats at one go. He also talked about the differences between being a program manager and a developer, pros and cons of each role, and shed a light on what to look out for when you are exploring your future career options. Have a listen.

You can connect with Kelvin here: https://www.linkedin.com/in/kelvinthamkh/


---

Send in a voice message: https://podcasters.spotify.com/pod/show/symbolic-connection/message

This week, we invited Teck Liang Tan (PhD), a Senior Data Scientist @ NTUC Enterprise to have chat with us. He walked us through his unconventional career move from Physics to Data Science. Also, his reason of getting into the industry instead of continuing in academia.
By the way, do you know what is complexity science?  If you are curious, you should definitely give this episode a listen! He also shared learning resources for getting into the field as well as keeping the skills sharp.
We also talked about #MajulaGCP season 5 which is happening right now and many more! Teck Liang's profile: https://www.linkedin.com/in/teck-liang-tan-47a47327

---

Send in a voice message: https://podcasters.spotify.com/pod/show/symbolic-connection/message

This week we invited Ivan who is a Lead Data Scientist at Tech in Asia. Ivan has a unique set of technical competencies, project management, interpersonal skills and problem solving abilities. He is also experienced in deploying scalable machine learning systems, data engineering pipelines, dashboards and delivering actionable insights through the use of statistics and data visualization. In this episode, Ivan shared his career journey from being an undergraduate to leading a data science team. He also shared whether doing an internship is useful and many more interesting tips and tricks to land a job in the data industry. Check this out!


---

Send in a voice message: https://podcasters.spotify.com/pod/show/symbolic-connection/message

Data collection is a crucial step for any data related projects. So much so that you might have encountered something along the lines of the “GIGO” (garbage in, garbage out) concept. Some might even say having the right data is more important than having tons of data that can’t be used.

As web scraping being one of the ways to collect data, for this episode, we invited Cliff, a data consultant, back to discuss his personal experience with web scraping. He shared topics such as the basics of web scraping, web scraping tools, the challenges that he faced while trying to scrape web contents, ethics of web scraping, learning materials, and more!

Resources:


Cliff's medium post 1: https://medium.com/codex/scraping-singapore-libraries-f74c541f1f94
Cliff's medium post 2: https://cliffy-gardens.medium.com/iterations-for-my-nlb-scraper-github-code-provided-b4e1f1bd422e
Selenium: https://www.selenium.dev/
BeautifulSoup: https://www.crummy.com/software/BeautifulSoup/bs4/doc/
TagUI: https://github.com/kelaberetiv/TagUI
Web Scraping with Python: https://www.oreilly.com/library/view/web-scraping-with/9781491985564/


---

Send in a voice message: https://podcasters.spotify.com/pod/show/symbolic-connection/message