Assignment Week 1

Ahmad Rizki Mubarak

March 01, 2026

Assignment Week 1 - Ahmad Rizki Mubarak
ASSIGNMENT // WEEK 1

ASSIGNMENT
WEEK
1

4 essential questions explored interactively. Click each tab to navigate through the assignment.

Ahmad Rizki Mubarak
// STUDENT
Ahmad Rizki Mubarak
NIM: 52250036 Data Science
QUESTION 1 / 4
01
QUESTION_01.md
What is the main purpose
of our study?
🎯 Core Purpose

The main purpose of this Data Science study is to systematically explore, analyze, and extract meaningful insights from data using scientific and computational methods. We study Data Science to develop the ability to transform raw data into actionable knowledge that drives smarter decisions in business, science, technology, and society.

🔬
Explore & Analyze

Uncover hidden patterns and trends within complex, large-scale datasets using EDA techniques.

🤖
Model & Predict

Build machine learning and statistical models that forecast outcomes and classify data accurately.

💡
Solve Real Problems

Apply data-driven approaches to address challenges in industry, healthcare, and public policy.

📊
Communicate Findings

Present insights clearly through data visualization, dashboards, and structured reports.

📝 Conclusion

In summary, the purpose of our Data Science study is to master the full data lifecycle — from collection and cleaning, to analysis, modeling, and storytelling — enabling us to make evidence-based decisions in any domain we choose to work in.

02
QUESTION_02.md
Why do we learn
about it?
💬 Core Reason

We learn Data Science because we live in an era defined by data explosion. Every industry — healthcare, finance, e-commerce, government — generates massive amounts of data daily. Without the skills to interpret and use this data, we lose the ability to compete, innovate, and solve modern problems effectively.

🚀
Career Demand

Data Scientists are among the most sought-after professionals globally, with salaries far above average.

🌐
Data-Driven World

Organizations make better decisions when powered by data — learning DS gives you that superpower.

⚡
Automation & AI

AI and automation are reshaping industries. DS knowledge is essential to navigate and leverage these changes.

🎓
Interdisciplinary Power

DS skills are transferable across every field — biology, economics, engineering, social science, and more.

📝 Conclusion

We learn Data Science because it is the language of the 21st century. Mastering it empowers us to understand the world better, build smarter systems, and lead with confidence in any field we enter. It is not just a skill — it is a competitive advantage.

03
QUESTION_03.md
What tools do we have
to be expert about?
🛠 Overview

A Data Scientist must be proficient in a diverse toolkit spanning programming, visualization, statistics, machine learning frameworks, and cloud platforms. Mastery of these tools is what separates a practitioner from a true expert.

🐍
Python
Programming
📊
R
Statistics
🗄️
SQL
Database
🤖
Scikit-learn
ML Library
🔥
TensorFlow
Deep Learning
⚡
PyTorch
Deep Learning
📈
Tableau
Visualization
🎨
ggplot2
R Viz
🐼
Pandas
Data Wrangling
🔢
NumPy
Computation
☁️
AWS / GCP
Cloud
📓
Jupyter
IDE / Notebook
📝 Conclusion

The modern Data Scientist needs fluency in Python and R for core work, SQL for data access, ML frameworks for modeling, and visualization tools for communication. Cloud and big data tools become essential as data scale grows. The best approach: master the fundamentals first, then expand.

04
QUESTION_04.md
Your interest domain
knowledge in Data Science
🌍 Domain Overview

Data Science can be applied across countless domains. My personal interest lies in areas where data creates measurable human impact. Below are the domains I find most compelling, each representing a unique intersection of data and real-world significance.

01
🏥 Healthcare & Medical Data Science
Using ML to predict disease outcomes, analyze patient records, and accelerate drug discovery. Data in healthcare directly saves lives — making it profoundly meaningful.
HIGH INTEREST
02
💹 Finance & Risk Analytics
Applying predictive models to detect fraud, forecast market trends, and optimize investment portfolios. Finance is data-rich and rewards analytical precision.
STRONG FIT
03
🌍 Social Impact & Policy
Using data to study inequality, urban development, education gaps, and government policy effectiveness. DS as a force for social good.
PASSION AREA
04
🛒 Business Intelligence & E-commerce
Customer segmentation, churn prediction, recommendation engines, and supply chain optimization — data powers every major business decision.
PRACTICAL
05
🌱 Environmental & Climate Science
Analyzing climate data, modeling ecosystems, and predicting natural disasters. One of the most urgent domains for data-driven intervention today.
EMERGING
📝 Personal Note

My core interest is in Healthcare Data Science — specifically building predictive models that support clinical decisions and improve patient outcomes. I am also drawn to Social Impact Analytics because I believe the most powerful use of data is making the world more equitable and informed.