Symbolic Connection

This week we invited Leo Tay who is also an AIAP graduate like Thu Ya and currently working as a Data Science Engineer at Allianz. He shared his interesting journey of becoming a Data Science Engineer without having a comp science degree, alongside with learning materials and useful tips and tricks to get into the fields. He also mentioned his struggles and how he overcame them in a short period of time. Lastly, we end the session by talking about a non-data related but useful topic for our listeners as always.

Materials:

Questions for our Guest: https://forms.gle/YhEtzQ3W7JVTNbHN9 

This episode, we have Cliff Chew, a Data Analyst with Grab. He will be sharing his transition from economist-by-training into a data analyst. He also shares some tips on how economics major can be working on data, what are the tools they can start with. Give a listen to understand his career journey and his unique perspective of life. :)

LinkedIn Profile: https://www.linkedin.com/in/kuo-ting-cliff-chew-22001925/

Cliff Chew's Blog: https://cliffchew84.github.io/

Questions for our Guest: https://forms.gle/YhEtzQ3W7JVTNbHN9

We are discussing about Data Visualization! We discuss why is data visualization important in the Big Data era, talked about the different tools of visualization and more importantly what is a Good visualization and how to get to it. In the episode, we share how one can design good visualization for audiences. Join us in this learning journey to understand a key data science toolkit, data visualization.:)

Reference:

John Snow's visualization (The Guardian)

Visual Cues (Github)

Tableau Visual Vocabulary (Tableau)

Our next guest is Charin Polpanumas from Bangkok! He is the Lead Data Scientist at Central Retail, Thailand's largest owners of shopping malls, supermarkets, office depots, and so on. He works on search, ranking, recommendation, CRM,, and all the omnichannel retail shenanigans. In this episode, he will be sharing about his career journey, what are the tools he is currently using and also how does he hire for his team. :)

LinkedIn Profile: https://www.linkedin.com/in/cstorm125/

Questions for our Guest: https://forms.gle/YhEtzQ3W7JVTNbHN9

In this episode, we turned the table around. Koo interviewed Thu Ya Kyaw, his co-host, to find out how he becomes a machine learning engineer at NE Digital (a subsidiary of NTUC). He will be sharing his career journey, what got him interested in the field, and what steps he has taken to get into and stay on top of the field. Join us, to understand the work of a machine learning engineer. :) 

Questions for our Guest: https://forms.gle/YhEtzQ3W7JVTNbHN9

We have a special guest for this episode. He is Thia Kai Xin, co-founder of DataScience SG and currently a Senior Data Scientist in Refinitiv Labs working on Natural Language Processing project. He shares his career journey, what are the skills and knowledge that got him his jobs and provided some advice on how to get into Data Science. Travel with him through his career journey and see how you too can become a data scientist. :)

LinkedIn Profile: https://www.linkedin.com/in/thiakx/

Questions for our Guest: https://forms.gle/YhEtzQ3W7JVTNbHN9

In this episode, we discussed how someone, regardless of their background, can get into data science. The topics include the necessary skills and knowledge he/she need to be equipped with as well as recommendations on whether to choose boot camp, official degree program or self-learning to get started. We also briefly touched on what you need to do for your project portfolio, to improve your chances during job interviews.

Resources

What is shared is to the best of our knowledge at the time of recording.  We strongly encourage our listeners to continue seeking more knowledge from other resources. Have fun in your learning journey and thanks for choosing us as learning companions. :)

In this episode, we explore what is Data Science, Machine Learning, and Artificial Intelligence. We also discussed the relationship and differences between them. How did Data Science come about, what are the common branches of machine learning and what do they do, are some of the questions we answered in the episode. We also covered briefly the difference between Data Scientist and Software Engineers.

References:

What is shared is to the best of our knowledge at the time of recording. We strongly encourage our listeners to continue seeking more knowledge from other resources. Have fun in your learning journey and thanks for choosing us as learning companions. :)

In this episode, we did a brief introduction to who we are. We discussed briefly what is Artificial Intelligence and the history of it, namely Symbolic AI and Connectionist AI. The difference between them, and how did we move from Symbolic AI to Connectionist AI was discussed as well. Take your first step together with us in our learning journey of Data Science and Artificial Intelligence. Below are a few resources you can refer to after the podcast. Will be happy to discuss the topic with our audiences. :) 

Resources: 

What is shared is to the best of our knowledge at the time of recording. We strongly encourage our listeners to continue seeking more knowledge from other resources. Have fun in your learning journey and thanks for choosing us as learning companions.