What is their main purpose of our study (Data Science
programming)?
Answer:
The main purpose of our study in Data Science
programming is to learn how to work with data in a
practical way. We study how to collect data,
clean it, analyze it, and turn it into useful
information. By learning programming, we can
solve real problems, make better
decisions, and understand patterns or trends from
data.
In short, this study helps us use data to find
answers and create solutions in the real world.
2 Question 2
Why do we learn about it?
Answer:
We learn Data Science programming because data is
part of almost everything today. From social media,
online shopping, transportation apps, to business decisions — all of
them use data. By learning this, we can
understand what the data actually means, find patterns,
and use it to solve real problems. It also helps us
think more logically and make decisions based on facts,
not just opinions. Plus, data skills
are very useful for future jobs in many different fields.
3 Question 3
What tools do we have to be expert about?
Answer:
To become good at Data Science programming, we need
to be familiar with some important tools. First, we should be
comfortable with programming languages like Python or
R. We also need to understand tools for data analysis and
visualization, such as libraries in Python (like pandas, NumPy,
and Matplotlib).
Besides that, knowing how to use databases (like
SQL) is important because data is often stored there. It’s also
helpful to understand tools for machine learning and platforms
like Jupyter Notebook. These tools help us work with data more
efficiently and professionally.
4 Question 4
Give me your interest domain knowledge in Data
Science!
Answer:
My interest in Data Science is mainly in
analyzing real-world data and finding useful insights
from it. I’m interested in how data can show patterns,
trends, and behaviors that we don’t notice at first. For example, I like
learning how data can help businesses understand customers better,
improve services, or make smarter decisions. I’m also
interested in machine learning, especially how computers can learn from
data and make predictions. For me, Data Science is
exciting because it turns numbers into meaningful information
that can actually help solve problems.
