Don’t learn Machine Learning if you want to start Data Science(ChatGPT Agrees)

I’ll say it again: if you want to get started in data science, avoid learning machine learning. Of course, I do not disagree that mathematics and machine learning are the core components of data science, but if you are a newbie, the biggest error you can do is to jump right into machine learning.

I can suggest that SQL would be a lot better place to start. 90% of your time will be spent processing data, and if you have a reasonable command of SQL, you will have a strong understanding of the many sources and logic that were utilized to obtain the data that you have.

Reasons for my position:

1. I began my path into data science by diving head first into advanced algorithms and mathematics, statistics, probability, and all the crazy stuff. There is nothing wrong with learning these initially, but without SQL and fundamental data analytics skills, you will need a lot of help(Assistance) from data analysts to leverage your knowledge and contribute.

2. This may not apply to everyone, but ML algorithms, math, and statistics are all HARD. They require a lot of work and a lot of hours to even have a rudimentary understanding of what’s going on beneath the hood. On the other hand, SQL is so simple that you can have a strong grasp of the necessary foundations in a matter of weeks.

The job market:

Here is a statistic for you if what I have said so far hasn’t convinced you. 98% of employees want the candidates for data scientists to have prior industry experience, but this is not the case for data analyst roles, even if you lack prior experience, your likelihood of being hired as a data analyst is far better than that of being hired as a data scientist.

However, there is still hope. The best chance for a newcomer to become a data scientist is to gain some valuable experience working as a data analyst for a few years.

Now what are the essential skills to become a data analyst ?? then answer is python, SQL, Tableau/PowerBI this is the reason why I suggested that those who want to start data science start with SQL

Where to begin then?

Now that I’ve hopefully persuaded you to start with SQL, let’s look at some great places where you can learn these skills.

1. For those who prefer to read:

I’m attaching two medium posts that I used when I first started learning SQL.

Post 1: Uğur Savcı, This is the most straightforward and concise post on SQL fundamentals.

Post 2: Taylor Brownlow, Now that you’ve covered the fundamentals in the previous posts, it’s time to delve into some of the nuances in greater depth. This is a four-part series that will teach you the fundamentals.

2. For those who prefer video lectures:

I’ve attached a video from freecodecamp that covers all of the basic operations that we perform daily.

3. Time to practice:

Now that you’ve learned, it’s time to put your knowledge into practice, and there are some fantastic websites where you can do so.

Website 1: SQLbolt, This is the most beginner-friendly website to write SQL there is IMO.

After you’ve completed all of these steps, there’s one more optional step that can help you solidify your knowledge: solving some problems. Leetcode is the website that everyone uses and that I prefer, and a list of all the free questions is linked below.

Link: LeetCode You will become super efficient in SQL after this step

For those who were waiting:

CONCLUSION:

Instead of starting with ML, start with SQL. Your adherence to the data science journey will be increased, and you will be able to enjoy the fruits of your labor much sooner if you start with SQL and continue to learn some data visualization tools.

So, what are you still waiting for?