Based on the title itself dah tahu nak cerita apa kali ni kan? :)
Sama mcam previous post, nak describe pengalaman and bagi a lil bit review.
Basically, ni first time SQS organize symposium hence the program ada letak 'The 1st'. Then, ini antara committee yang kecik, cooperative, and well-functioned i've ever join. Kitorang semua student postgrad. Maybe faktor umur. They reached maturity level already (I am excluded). Despite assignments and hectic week, they all managed to handle it. Seronok! Dapat pulak coordinator yang masuk kepala, n particular so kredit untuk well balance kat situ.
Secondly, participants. I am totally amazed for participants sebab majority of them ialah undergrad students. Early exposure is crucial. Lagi-lagi untuk quantitative sciences, courses yang ada high graduate employability tapi low promotion, causing few people yang determine nak further studies in these courses. Contoh terdekat, last year, Decision Science course sendiri duduk dalam hot cup sampaikan KPT sarankan tutup course. Sedangkan majoriti lepasan Decision Science dapat proper position in working sector. Back to symposium, it is a good platform for them to educate others like prospect employers and public tentang apa yang you belajar during degree and also, mana tahu ada yang berminat nak sambung belajar lagi. :)
Next, ada jugak postgrad participants (which is to me, sama macam SLCP Conference event) yang nak peer-reviewed, tambah publication, etc. Ada tu, lecturer school sendiri. Cuak ok. These educated and superior people really scares me sebab kita level marhaen sahaja. But it is totally good way of sharing ideas and PR kan after all? 😊
Thirdly, I love the issues brought by the invited speakers. First speaker talked about integrity of data analyst. Dia cerita current issue yang banyak berlaku dalam real world data science lately. It made me realize the importance of being precise and particular. Second speaker presented research that has been done by her team. since i already in optimization field, i feel that sebenarnya banyak je cabang untuk diaplikasikan/ yang student boleh pergi dalam data science/quantitative sciences. and, deep in my heart,ada la sikit rasa ralat atas kemalasan dan kejahilanku zaman dahulu kala.
Thirdly, I love the issues brought by the invited speakers. First speaker talked about integrity of data analyst. Dia cerita current issue yang banyak berlaku dalam real world data science lately. It made me realize the importance of being precise and particular. Second speaker presented research that has been done by her team. since i already in optimization field, i feel that sebenarnya banyak je cabang untuk diaplikasikan/ yang student boleh pergi dalam data science/quantitative sciences. and, deep in my heart,ada la sikit rasa ralat atas kemalasan dan kejahilanku zaman dahulu kala.
If you are interested in any symposium/conference, what do you need?
- Be ready. Be it mentally or physically. Kena ada dalam optimum health state.
- Be an early bird. Register awal (harga early bird usually lil bit cheaper), datang awal, prepare material awal. Sebab we cannot expect everything gonna be as we please.
- Back up. Ada orang yang simpan slide kat emel and OL. bila ada masalah internet, laju je ada back up kat pendrive.
- Laptop as first life. This baby device is super sensitive and dia boleh 'sakit' bila-bila masa especially bila dia penat. So, careful.
- Lastly, be proactive. Ha yang ni even me myself trying to practice. Because, our culture, Malay, we are well trained of spoon-feed. Bila dah lepas teenage years, you will be treated differently. Ilmu tu takkan datang bergolek, takkan terbang melayang directly to you. Mingle around with new people.
- Never underestimate others. Sometimes, kita rasa kita ni ada background yang hebat tau. Good pr, ada kabel saiz trojan, rasa paper/tajuk kita paling bagus, apa-apa la. Well, orang lain pun hebat tau. They are just being humble.
Cheers!
| whole audience |
| our committee |
| standing: invited speaker 1, sit from right: invited speaker 1, Dean |
| poster evaluation |
| paper presentation |
| me |
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