We all learn differently.
Not just at different paces, but in different ways. This could be a reason as to why people are inclined towards different things — some of us are more creative, while others are more logical.
Some of us enjoy public speaking and debates, while others enjoy painting and drawing.
This inclination towards different paths stems from the way we think, and influences the way we learn.
We are all very different, with unique thoughts, ideas, and learning patterns. We have different ways in which we experience the world around us.
These different patterns can be classified into four learning styles.
This means that there are four categories of learners, and we all fall somewhere within each category.
Some people fall into more than one of these categories.
As I read more about learning styles, something clicked. I understood the importance of aligning my study material with my learning style.
I also realized why I struggled at a few topics while I excelled at others.
I always scored an A in my science exams, and the calculations were a breeze. However, I could say the opposite for the lab classes.
Put me in a chemistry lab, and you’ll see how I struggle to follow the seemingly simple instructions given by the lecturer.
To get through this difficulty, I’d ask my friends to tell me all the steps involved in completing the lab task. I would then write this down, repeat it to myself, and get a clear picture of what to do.
This was because of my learning style. I was not a visual learner, which made it difficult for me to watch and mimic what other people did. I also was not a kinaesthetic learner, which made it even harder to follow my lecturer’s instructions.
Knowing your learning style is important, because it can help you figure out the best way to study a subject. If you’re struggling with a seemingly simple concept that everyone around you seems to understand, maybe you’re just learning it wrong.
I will now break down the different learning styles.
Based on your learning style, I will also explain the different approaches you can take to study data science.
A visual learner is someone who learns best from visual means. This is a person who understands a concept best by looking at it.
This learner understands a concept best when it is in the form of a picture, mind map, or flow chart. If you are a visual learner, you’ll learn better by watching someone perform a task, rather than hearing them explain the process.
As a visual learner, watching online courses would greatly benefit your data science learning process. There are a lot of MOOCs that cater towards visual learners, as the tutor shows you how to perform tasks.
You will learn best when the tutor runs a block of code in front of you and demonstrates how the program works.
When taking notes, you should do so with different coloured pens, make mind-maps, or create a flowchart. This will help speed up your learning process.
As a visual learner, you are able to picture a concept in your mind by looking at it. I suggest using this to your advantage in your data science learning.
Make a mind-map of short-term and long-term study goals you want to achieve, and work towards them. You should also create a vision board, and illustrate where you want to see yourself in the next couple of years.
Waking up to your vision board every morning and looking at exactly where you want to be in the future will inspire you, and push you closer to your goal everyday.
Auditory learners prefer taking in information by hearing it, rather than through visuals.
If you are an auditory learner, you understand a concept best when you hear it out loud. You tend to repeat your notes to yourself, and prefer listening to lectures.
As an auditory learner, I like to explain concepts to other people, because saying it out loud helps reinforce my memory.
I always listen intently when my friends revise notes out loud before an exam, because hearing concepts helped me internalize them.
As an auditory learner, I often listen to data science and deep learning lectures from MITx or Harvard. While most people find the traditional style of listening to lectures boring, it is the way I learn best.
After finishing the lectures, I like to internalize everything I learnt by explaining the concepts again, in my own words. This method of listening to a concept, followed by repeating it out loud has greatly helped my understanding of new topics.
If you are an auditory learner, I suggest doing this to get a better understanding of new concepts. (Speaking from experience, I suggest avoiding libraries or silent study spaces when doing this).
Kinaesthetic learners learn best by doing. They understand a concept best when they actually get involved, and do some hands-on practice.
These learners struggle most when placed in a school setting, because they find it difficult to sit still and take in large amounts of information.
However, these learners have a lot of potential outside a school setting. Their interest in interacting with the environment around them makes it easy for this learner to thrive in the workplace, and in any setting that requires hands on practice.
If you are a kinaesthetic learner, I suggest taking the top-down approach to learn data science.
This means that you can follow Kaggle tutorials first, and work towards solving an end-to-end problem by writing out code.
Once you start to build and get familiar with the tools used, then you can start doing your research about the underlying algorithms.
As the name suggests, reading and writing learners learn best from reading and writing. They grasp concepts from reading textbooks, and writing down notes.
The traditional school system caters to reading and writing learners, since most of the work done involves writing essays and learning from textbooks.
If you are a reading/writing learner, I suggest taking the bottom-up approach to learn data science.
You can buy a machine learning book and familiarize yourself with the concepts. After developing an intuition on the use cases of each algorithm, you can go on to delve into the implementation, and actually start coding it out.
In addition to being an auditory learner, I also am a reading/writing learner. Due to this, I like to read concepts out loud, write them down, and read them out again.