Two days ago, I had my 27th and final session at the Summer Institute in Computational Social Sciences (SICSS ) Calabar location, and the experience was truly life-changing and left an indelible impact on my professional and personal growth that I can’t wait to share with you.
My experience at the Summer Institute of Computational Social Sciences was an equal blend of learning more about computational social science, the people, the historical city of Calabar, and its myriad of lucrative economic activities.
Besides having to explore the intricacies of R programming packages for statistical analysis and machine learning, I am super proud that I left the city with no regret — having leveraged every opportunity I had to learn, socialize, and collaborate to expand my horizons in all aspects.
This post is an overview of the overall values I have gotten from the SICSS Calabar 2023. In my subsequent posts, I will extensively write on statistics for data science, features, and packages in R programming language for machine learning modeling, data wrangling, and visualization.
On the professional front, I have had a bunch of takeaways from the summer institute. But the one that stood out is the experience I had working with the R programming language and a clearer insight into some interesting statistical theories and hypotheses that are crucial to my data science career.
If I had a strong grasp of R and these statistical hypotheses earlier on, it would have saved me a lot of time and fast-tracked my data science skills. But it is never too late as having an idea about what I should work on going forward has already elevated me to a step ahead.
Let me also save the time of other aspiring data scientists, especially those not from STEM backgrounds, in their learning journey by clarifying a notion they may have already fallen for — that coding is the most vital skill you need to build a career in data science.
Coding is undoubtedly an essential skill. But I can equally tell you for free that jumping into coding without being well-grounded in mathematics and statistics is akin to building a castle in thin air than a data science career.
How could you possibly choose an appropriate data structure, machine learning algorithm, and model evaluation metrics for the task at hand without understanding the mathematical concept? Hell no way! In fact, as fundamental as it is to every machine learning task, you can not suitably preprocess your data and apply feature selection, to begin with. All I am saying here is, that statistics is the backbone of data science and as an aspiring data scientist, the earlier you pay attention to it the better!
Ever since I started my Data science journey, Python has been my all-time favorite — for obvious reasons. But having seen R programming language performing wonders in data modeling, text classification, and predictive machine learning modeling at the SICSS, I can’t help but cheat on Python.
I am particularly fascinated by the diverse packages and functionalities R possesses which I think are as user-friendly and efficient as Python when it comes to performing data science and machine learning tasks. Apart from its unique and friendly user interface, R also adopts some spreadsheet and SQL syntaxes, making it more relatable to people with prior experience in spreadsheets and SQL.
Note that besides having a strong understanding of statistics, you should also consider learning both Python and R programming languages to enjoy the flexibility in choosing tools to work with.
I also strongly recommend participating in the Summer Institute in Computational Social Sciences to aspiring data scientists — particularly those who are interested in solving social problems or looking to specialize in Natural Language Processing or Natural Language Programming.
About SICSS:
The Summer Institute in Computational Social Science was founded in 2017 by Prof. Christopher Bail — a Professor of Sociology, Political Science, and Public Policy at Duke University. Every year, the institutes bring together — via its partner locations spread across the globe — graduate students, postdoctoral researchers, and beginning faculty interested in computational social sciences. For 2023, only two SICSS locations are in Africa — Calabar (Nigeria) and Accra (Ghana). You can keep track of active SICSS locations around the world via the SICSS global website.
SICSS Calabar 2023 was organized and hosted by the founder of the Academic Hive, Juliet Inyang, in collaboration with the University of Calabar. It was fully — funded by the Mathematica, Social Science Research Council, Duke University, Institute for the Study of Societal Issues, and SICSS Howard. You can access the SICSS online learning material for free via the SICSS Boot Camp platform.
SICSS has exposed me to a promising dimension in my data science career and I am looking forward to collaborating with other professionals from the social sciences to solve social issues using data science and machine learning techniques. I am specifically interested in using machine learning to predict the crop yield of staple food in Nigeria.
On a personal level, being my first time traveling to the south-south region of Nigeria, I landed at Calabar with two things in my mind — learn, network, and explore. And I am glad that I was not in any way disappointed as my 2-weeks stay at “The Nation’s Paradise” was truly eye-opening, life-changing, and memorable.
I had the most amazing co-participants, facilitators, and organizers that I could ever ask for — so open-minded, resourceful, and accommodating. Among the participants, I met Uduakobong Otu — a Calabar indigene and Ph.D. student at the University of Calabar.
Uduak — as we fondly call him, besides making time out of his tight schedule to upskill my understanding of some statistical hypotheses, he generously took me around on personal sightseeing around the City of Calabar.
I believe you can understand why Uduak deserved to be my social and academic mentor:) Courtesy of my mentor, I witnessed the live show of the third episode of the De9jaspirit Talent Hunt — credit to my mentor:)
I want to believe that the generosity depicted by Uduak represents the hospitable nature of the Efik and Ibibio clans. Having said that, I am hereby adopting Calabar as my home — second to Bauchi.
About the delicacies. If you have ever been to Calabar but haven’t tried their Afang soup, you should go back again and correct your mistake — it’s like visiting my hometown, Bauchi, without having a taste of masa, our favorite delicacy. Afang (wild spinach) soup is a signatory dish of the Efik and Ibibio people. As a professional Food explorer with top-notch food-tasting skills, I ran a couple of experiments with the Afang soup, and trust me, I can still feel the delight in my taste buds.
Besides the FOOD, I was also amazed when I visited the historical sites in Calabar that date back to the mid-19th century. Notable among these sites is the Old Residency, also known as the Government House. This ancient building was said to have been prefabricated in Britain in 1884 — about 139 years ago — before it was later moved to, and erected, in Nigeria to become the British Colonial Administration.
I am still trying to picture how a 1-story building, as big as this was brought all the way from Britain to Nigeria:)
I learned that the Old Residency, which is currently a museum run by the Federal Government of Nigerian, was the first operational base of the British colonial masters, and the residence of the British administration of the southern protectorates before the amalgamation of the northern and the southern protectorates to become Nigeria.
In the Old Residency Museum, I came across this bell called Nkanika, the Ship Bell. According to the historical narrative behind it, the bell was seized from a High chief of the ancient city of Calabar in 1870 by the then British Consul, as a punishment for maltreating his slaves. After it was confiscated, it was said to have been used to announce the beginning and end of the working hours and, the arrival of trade ships among other things.
I was told not to ring the bell as it is tantamount to waking up the ancestral spirits. But trust me I had to ring it to quench my curiosity:)
Wrapping up:
Summer Institute in Computational Social Science has remarkably exposed me to a promising dimension in my career development. It has given me an in-depth understanding of the applications of data science and machine learning in addressing social science problems. I am eager to explore professional collaboration in computational social sciences to address pressing social issues such as food security.
Once again, to every aspiring Data scientist out there willing to explore Natural Language Processing or Natural Language Programming, I strongly recommend attending the Summer Institute in Computational Social Sciences or any social sciences professional networking event.
In my subsequent post, I will elaborate on statistics for data science and R packages for machine learning. Don’t forget to follow my page to keep in touch!
Sọsọñọ SICSS Calabar🫶
