Today’s exclusive features Mr. Shehu Alaba, a data analyst and scientist, who recently concluded his studies at the University of Ilorin with a 4.96 CGPA.
We will be discussing among other things, his path and drive to success as well as his career path.
Linda Onuorah: Can you please introduce yourself to us, sir?
Shehu Alaba: My name is Shehu Alaba Rashid, and I’m a recent graduate
from the University of Ilorin, where I finished with a CGPA of 4.96 out of 5.0.
During my time at the University of Ilorin, I ventured into a lot of things, and one of the
things I did was to, mentor undergraduate students. I mentored a lot of students in mathematics and physical science.
I also created a foundation called the Imagine Minds Foundation, where we have been able to bring over 280 undergraduate students from the whole of the University of Ilorin into programming and technology.
Linda Onuorah: Wow! Impressive, thank you for sharing with us. Can you give us a look into
your educational background?
Shehu Alaba: My educational background, I am a recent graduate from the University of Ilorin. I graduated with a degree in Mathematics. I also took Data Science courses in online programs. So I’m a data scientist.
I learned data science from Data Camp, Udacity, and Coursera. All this was during my time at the University of Ilorin, so I can say that I’m a very active learner.
Linda Onuorah: It’s not every day you meet a mathematician. Can
you tell us? What’s that like?
Shehu Alaba: Oh, being a mathematician. I know many people think mathematics is boring.
Linda Onuorah: Yes,
Shehu Alaba: It’s not. Like I always say, whenever you go into anything, make sure you love it. You go into a particular field, make sure it’s something that you love. So mathematics is very fun.
The problem with mathematics is the way we view it, especially in Nigeria. If you go back into history, you see that the people who created computers, Charles Babbage was a mathematician, the first computer programmer and Ada Lovelace was a mathematician. One of the most prominent and popular scientists, Isaac Newton, was a mathematician. Steven Hawkins was also a mathematician.
But many feel mathematics is just all about solving and, all, but mathematics is much more than that. Mathematics is a thing of beauty. And, even in English, you find mathematics in there. For instance, when you are trying to explain something to a person and you are looking for a way to simplify it, you can say E plus something is equal to so and so.
Mathematics is everything, it is in every facet of our daily lives. it is a thing of beauty. it is not boring at all, quite the opposite, it is fun.
Linda Onuorah: Interesting! I will take your word for it. I’m sure you know this, most students going to the university when asked what they want to study, give answers like an accountant, an engineer, a doctor, but you chose to be a mathematician, I’m curious to know, what inspired that, what motivated you into wanting to do mathematics?
Shehu Alaba: I’ll be very honest, I have always loved mathematics, right from when I was very young and I was also very good at it. I can do other subjects and not do them well, but when it comes to mathematics, I always Excel. But you know, the thing is this, when you are coming up, as someone good in mathematics, you start hearing things like, Ah, you must go for engineering.
Once it is discovered that you are good in secondary school, they will tell you that you will do well in engineering, the same thing if you are good in things like biology, they say that you should go for medicine. So initially, when I was in secondary school, I was very, very good in mathematics, physics, and all. So all my teachers were like, go for engineering. Go for engineering. Go for engineering. I believe that was one of the things that made me lean towards engineering initially at the beginning. So you could say I was not doing engineering because I loved it. I was doing it because of the fancy name and because I was practically programmed to pursue engineering initially.
I applied to the University of Ibadan, but I wasn’t given engineering. You see the thing is this, secondary school will fool you into believing that you are the most intelligent and you’re the best and that may be true for your bubble, but when you step out of your bubble into the real world, you realise that there are scores of equally intelligent and even more intelligent people around.
I was the best student in my secondary school (my bubble), and I was the local champion, especially when it came to the sciences, but when I got out and started writing Jamb and then Jamb started jamming me, it was a shock. I was used to getting all A’s but now it looked like I was finding things difficult.
At this moment I started thinking of the things I loved more. I started reading more books. I remember in school, I used to read right before exams, I didn’t read ahead. Now I had seen a glimpse of the real world, I started learning the ability to read before exams and continued building myself.
It was during this process of building myself, I realised that instead of going for something for the sake of fancy, I should go for something that I actually love and have a passion for. And it has been a big thing of beauty since then.
Linda Onuorah: Interesting! And you, you came out with a first class in mathematics?
Shehu Alaba: Yes
Linda Onuorah: Not a lot of people can boast about such an achievement. Most people can’t even solve a small equation. So you coming out first class in mathematics is a big deal. How did you do it? What were the steps, and your strategies? How did you get ahead of it?
Shehu Alaba: The thing is this, I think the problem with many people is that they are afraid of failing, but you have to realise the best results often come after many failures.
Similar to when you want to make a sword, you have to first put it through fire, melt it, then pour the metal into a particular
shape, and you start heating it, heating it, then, from that, heating it becomes a thing of beauty. So I think that was typically my story. If when I left Obi College where I thought I was the best, if I had entered the university directly, without first building myself and being sure of what I wanted, I may have still finished with a good result but maybe not one as good as this.
I can proudly say that I was one of the top three in the University of Ilorin not just in my department. I can’t tell who is number one or number two, because convocation hasn’t been done yet, but I am confident of a top-three finish.
All this didn’t come easy for me. It came from me failing Jamb continuously. Because in my first Jamb, I got 220. I passed only the mathematics, but I failed other subjects. In my second Jamb, I got 270. This slight difference was a result of the fact that I wrote my first jamb based on pure talent, not study.
With my second attempt, I started learning the ability to read ahead. But even though I was reading, I was focused only on the things I was good at. So when I got 270, I was not surprised but I knew if I wanted to get into the University of Ilorin, I must get something that is above the scale.
One of the problems I had was chemistry. I always failed chemistry in Jamb, no matter how high I score I always fail chemistry. So I was like, Okay, this particular time
around, I must do something very different. So I started learning chemistry, and glory be to God in my Jamb, I was able to get 82 out of 100 in my chemistry.
From all this, what I learned is that from failing the first time I learned something new, and failing the second time I learned something new so when I got to the University of Ilorin, I already had the ability that okay, even if I don’t like a particular subject, I won’t want to fail it. And more importantly, I wasn’t scared of failure again, because I’d already failed countless times, the only thing I was scared of was not doing the best I could. So, I think it was my constant failures. I know that sounds weird, but I think my constant failures made me into the person I am today.
Linda Onuorah: That doesn’t sound weird. Like you said, a lot of us are very afraid of failure, and that’s why we don’t even try. Just like you said, before you make a sword, it has to go through fire and a host of other processes before it becomes a beautiful thing. So it’s okay, that was your own story, and that’s great because you came out on top. Do you mind sharing some of the strategies you applied to come out with a first class?
Shehu Alaba: The thing is, my lifestyle in my early years at the University of
Ilorin isn’t one I would advise anyone to emulate. From early on, I was determined to be the best.
First class wasn’t the original plan, the only plan was to come out as the Best Graduating student. My mindset was, that no matter how good the next person was I had to be better, no matter how hardworking, I had to work harder. If you can read for 10 hours, then I can do 11 hours, if you do 13 hours I can do 14 hours. That was my mindset in 100 level. So at 100 level, I will not say that I had a life outside mathematics.
The only thing I was doing in 100 level was, I would just go to class. After we finish classes, I won’t go home I will sleep in school till the next day. I won’t even sleep, I would stay up reading all night. I could be in school for three days straight without bathing in my 100-level days because I wanted something. I just wanted to have that score and glory be to God, in my 100-level first semester I had a 5.0GPA.
I didn’t have any B’s it was all A’s in my 100-level first semester. I think my 100-level second semester, was when covid happened, or something that we were forced to stay back from school. So I can say that COVID was one of the things that changed my life because COVID-19 made me see things from a different angle, okay, even though I’m very good at mathematics, I should be able to apply it to other aspects of life.
After COVID, my lifestyle changed a little bit. I still studied a lot but I structured my studying, I would read maybe eight to ten hours. That sounds weird, I know but remember, I used to read all day and all night before. So take for example, on school days I can read for like five hours after school, but on weekends I could read longer, and depending on whether it was close or during examination periods, I could extend or shorten the number of hours. I learned to create a balance. Then I think by 300 level, I reduced it a bit.
The thing is, make sure you start strong and get great results in your early levels. That’s my advice for anybody. Have very strong results initially, then once you already have that result, it’s easy for you to relax a little bit. And because you already have that result, all you need to do is maintain it and avoid a drop. That was my approach, starting very strong and maintaining it as I progressed.
Linda Onuorah: That sounds like a great plan. It worked out for you. So would you say mathematics is the same with data analyst? Are they the same thing?
Shehu Alaba: No, they are not the same. Mathematics and Data Analysis are different, but the thing is, you can apply the knowledge that you get from mathematics as a data analyst.
I started as a mathematician, but COVID changed everything for me. One of the things that inspired me to become a Data Scientist was, I saw the way people were dying, and I felt like mathematics could do something about this. So I said to myself, let me look for a field whereby the knowledge of mathematics is applied to real-world problems.
That was how I got into Data analysis. So I will say that in mathematics, you analyse. You can have numerical analysis, and algebraic analysis in mathematics. Data analysis is now a combination of mathematics, statistics, and computer science. So data analysis is more.
Linda Onuorah: Okay. So would you say, the death rate during the COVID-19 pandemic, was what motivated you to become a data analyst?
Shehu Alaba: Yes actually, because I felt like relative analysis would have saved a lot of lives. I believe if there was data available it could have lessened the loss of life that was caused during this pandemic. Date could have helped prevent the many deaths that happened but we did not have any data and over 6.9 million lives were lost globally.
Even though we could not prevent that kind of outbreak, you can’t prevent it totally, but you can mitigate it. You can reduce the amount of people that will die. So that was one of the things that motivated me into data science and data analysis.
Linda Onuorah: Wonderful! This brings me to the base question of you know, as a layman, I don’t know mathematics, I don’t know statistics, I don’t know anything. What would you tell me data analysis is? If I say, what is data analysis, Mr. Shehu, what would you say to me?
Shehu Alaba: Data analysis, before I go into details is a field I love very much. So before I say anything, I will say data analysis is a beauty, but if I want to define it, data analysis is the act of collecting data.
Linda Onuorah: What do you enjoy the most when working with data? What is your favourite part of being a data analyst?
Shehu Alaba: I am actually, a data scientist. A data scientist is a step above a data analyst. The thing about data science is that you can make predictions. You can predict things, It’s one of the reasons I love data science.
Sometime last year, I created a project, and the work of the project is that you can predict heart disease without even going to a hospital. So you just interact with the web app, give it your details and it will predict if you are at risk of having a heart disease or not. Being able to create groundbreaking, things like that, things that can lead to Global change is one of the things I love about being a data scientist. I feel like we can do more, and we can, you can make a change. I can make a change on a global scale. So that is what I love about being a data scientist.
Linda Onuorah: Okay, so if I get you right, a Data Analyst collects the data and others process it?
Shehu Alaba: Yes
Linda Onuorah: While a Data Scientist does the prediction?
Shehu Alaba: Let me, let me, let me just explain further.
Linda Onuorah: Please do
Shehu Alaba: A data scientist now can do almost everything a data analyst can do. That’s the difference. Data science is, a little bit more advanced than data analysis.
So for a data scientist now, when they give you the problem, you get data out of it. After getting the data, you analyse that data bring out those results, and present the results to the stakeholders. But when it comes to data science, you can take it a little bit further.
Let me break it down, say you own a real estate company and you employ a data analyst. That analyst will give a breakdown of the data you already have, like, this and this is what you are selling, and this and this is what you are making. This will just give you insights into your data. But for a data scientist now, they can make predictions for the future of your business. That’s just the difference. A data scientist will take it a little bit further.
Linda Onuorah: I understand, better now. For every other person watching, and our readers who will be reading this article later what are those areas where you need a Data Scientist?
Shehu Alaba: The beauty of data science is that it can be applied and useful in any field. This is why I advise anyone wanting to go into tech to give data science a chance.
A data scientist can work anywhere. They can work in healthcare, finance, etc. The prediction data I did was for healthcare. You can work even in the banking sector. For example, I know, you know in the banking sector there are many fraudulent activities. So as a data scientist, one of the analyses that is very popular is credit card analysis, whereby you can predict if a credit card application is, a fraud.
You can also work in marketing. You can work practically anywhere as a data scientist. You can even work for farmers. I have a friend who created an analysis that will show you the diseases affecting your tomato plants from the leaf.
They installed the program into a drone, the drone will scan over the plant, and it will tell you the kind of disease that is affecting those plants, without, having to pull out the plant. A data scientist can work anywhere, which is why it is an interdisciplinary goal.
Linda Onuorah: Okay! How does one become a Data Scientist? Does it or do I have to go through being a Mathematician, or have to go through being a Data Analyst first?
Shehu Alaba: To become a data scientist, having a mathematical background is a great bonus, because some of the things that you’ll be doing, will involve calculations, and hypothesis testing. In school, you will have already learned that and so it will make navigation easier.
You can become a Data Scientist, even without a mathematics background. The only thing you need to do is you need to look for very sound online programs. There are many online programs to choose from. You need to look for a sound online program that will take you through Python programming.
They will teach you how to use NumPy, which is Numerical Python. They will teach you how to use pandas, which is like Excel in Python programming. They will teach you how to do data cleaning, data manipulation using Pandas, data pre-processing, and how to preprocess data. After that, you will be taught to build machine-learning models. Then if you want, and if you can, you will be taught Machine Learning Module for a machine learning.
From a machine learning model, you can make predictions. You can stop there, or you can take it a little bit further by learning machine learning production (MLPs). Using machine learning, you can create apps that people can interact with. When you have learned all these, then you’re a data scientist.
What is left is for you to think of a field where you want to apply all that you have learned. You can apply it in finance, agriculture, health care, anywhere you wish to basically.
Linda Onuorah: Coming back to you as a Data Scientist. What are you currently working on?
Shehu Alaba: Being that I just finished school, I’m still exploring, that’s just it. I’m still exploring.
Linda Onuorah: Is there a particular field that you’d like to work in as a Data Scientist?
Shehu Alaba: I’ve worked in the health sector. Most of my projects that you can see online are actually in the field of health, but I’m open to any challenge. I don’t want to confine myself to one space.
Any opportunity that comes, I will accept the challenge. I have the general science knowledge there, all that is left is to apply it to a particular field. So I’m not confined to a specific industry, I can pop up anywhere.
