How YouTube Decided My Career
Are you a person who spends most of the time on social media like me?
I am a B.Tech student with an electronics background, and I often face this situation, where people ask me why data science. And, my reply is why not?
My friends used to tell me that data science is a vast course, we have to study a lot for it, and also we are not that strong in coding. Their advice often boils down to settling for any job, even if it’s just a standard 9-to-5 position.
Considering that, I thought It would be a great idea to share my insights on this. I hope this blog will help you!
Why Electronics?
Like a lot of other students, I had no other option.
After 12th grade the only option I had was engineering. I was interested in computer science, but due to delayed admission, I couldn’t get a seat as it was already occupied by some other student.
The only option I had was electronics. I had no interest, but when I entered this field it was interesting.
I don’t know whether it was my friends or the course, which one was interesting!
Jokes apart, I learned a lot in this field and generally got some interest. Anyways at the end, you would need coding.
So, I decided to start coding and since I was a beginner I decided to start with Python.
How interested in Data Science/Machine Learning?
After completing the Python course, I felt as If I knew everything about coding. But I was wrong!
While exploring I saw a great course on data science and machine learning. This was the first time I was introduced to this topic.
So, I decided to start this course. This course started with basics like statistics and probability, which was fun but the actual adventure started when data science libraries like NumPy, Pandas, and Matplotlib came onto the scene.
This is the part where it caught my interest to know more about this field. But one thing that I couldn’t move my eyes from was YouTube.
While randomly watching shorts, I saw that there was a unique section, which said “Recommendations For You”. I was shocked to see how YouTube knew what I wanted to watch next.
And the answer is data science and machine learning! Yes, you heard it right. Let’s begin!
Stay Tuned! for the Best Tip.
How to learn Data Science?
Get To Know Your Interests
First, know what are your interests. Don’t follow the chain of trends. Ask yourself a few critical questions:
- Do you want to opt for any particular specialization in data science?
- Do you want to stick to only data science or explore its related fields like data analysis, data engineering, or machine learning engineering?
Don’t worry! You’ll get to understand this once you enter this field.
Start Practicing
Besides taking online courses, do you know what’s best for you? It’s self-teaching.
After finishing a particular topic let’s say Pandas, start practicing it, set some difficult questions for your own, and try to answer them.
Honest Tip!
I know there are a lot of people advising you to start like this, like that. But I would personally suggest you to start like this:
- Start with data science libraries like NumPy, Pandas, Matplotlib, and SQL.
- Then, go for statistics, probability, and linear algebra.
- After that, start with the Machine Learning algorithms. Try to understand the train-test split, how to train and test the model, whether to use regression or classification, how to get the accuracy of the result, and so on. (If you want a complete step-by-step process comment me).
- Then showcase your understanding in the form of a project. Try to do a real-world project (unique project).
- If you want to know from where can you collect datasets for free other than Kaggle then share your thoughts in the comment section & follow me.
- Start learning about dashboards like PowerBI, or Tableau.
- Show the results in the dashboard, and add that to your portfolio to stand out.
If you find this blog helpful, please like, share, and follow me Data Science Delight for more.
Thank You!
