Today, I dived deeper into the space of Data Science, learning what it is, the definition of the buzz words, the different disciplines and specialisations, the tools and software needed to practice as a Data Scientist.

Data Science is indeed a broad subject and it has several other disciplines embedded in it. Data Science requires the knowledge of Statistics, Mathematics, Programming and Data Management tools. A Data Scientist must also be a great problem solver.

This reminds of my days as a University Undergraduate studying Computer Science, we were made to take courses in Statistics and Mathematics. In fact, at that time, the Computer Science, Statistics and Mathematics departments were categorised as one department and was managed by one Head of Department.

It didn’t make any sense to many of us then, and as far as I was concerned, as a Computer Science student, I shouldn’t have anything to do with Statistics and Mathematics. Looking back now, it makes so much sense and I can connect the dots.

I feel that my background in Computer Science, experience with programming and business generally will make my learning Data Science a bit easier but I have also seen that anyone without such background but with a genuine interest and dedication will be able to learn and grasps the skill as well.

So today, I have learnt that at the heart of the work of a Data Professional is “Data”. Data, which can be structured or unstructured is simply the information that we generate daily in different forms and from different sources.

There are a lot of buzzwords in the field of Data Science, some of them are Data, Data Cleansing, Data Team, Big Data, Big Data Team, Data Analytics, Business Intelligence, Business Analytics, Predictive Analytics, Machine Learning etc. To get a better knowledge of these terms, ask ChatGPT or Google Bard to give you their definitions.

I came across a very short video that explains how to become a Data Scientist in 2023, watch it below.

Also, the video below details the different types of Data Science jobs that is available in the market, it’s a short video that you can watch right now.

Probability is next on my course content for tomorrow, I am eager to see what new thing I would learn and I look forward to sharing that knowledge with you.

May I ask that you stay tuned and follow along with me on this journey? I am sure that you would learn a lot too.

See you tomorrow for Day 3.

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