Semester 1 as a Data Science Student

🎓 Semester 1 as a Data Science Student: What’s Actually Going On?

Hey there, future Data Scientist! 🚀

Just started college and wondering, “Why am I taking Calculus and National language? Isn’t this supposed to be Data Science?” Relax—you’re definitely not alone. The first semester is like an introduction—not just to university life, but to the core knowledge you’ll need as a data wizard in the making.

Semester 1 as a Data Science Student

Let’s break down what’s in store for your very first semester. You might even end up more excited to dive in! 😉

1. 🧮 Calculus 1

Yep, the one that makes a lot of foreheads wrinkle. But don’t underestimate it—calculus is super important for understanding change, trends, and patterns. Want to build predictive models? Play around with machine learning? You’ll need a solid calculus foundation (even if it gets a bit toxic sometimes 😅).

📘 Reference: James Stewart - Calculus: Early Transcendentals

2. 📝 National Language

Wait… is this Data Science or Literature class? 😆
Don’t worry. As a data scientist, you won’t just be coding all day—you need to know how to communicate your findings clearly and effectively. This course helps sharpen your writing skills for reports, presentations, and even data storytelling.

📘 Reference: Gorys Keraf - Komposisi (The Basics of Effective Writing)

3. 💻 Introduction to Information Systems

This course introduces you to the world of Information Technology: how systems work, the role of data, and why every company is racing toward digital transformation.
Here, you'll start understanding why data is often called "the new oil."

📘 Reference: Kenneth C. Laudon & Jane P. Laudon - Management Information Systems

4. 🖧 Fundamentals of IT Infrastructure

Sounds a bit technical? That’s because it is—but it’s also crucial. Knowing the basics of servers, networks, data storage, and cloud systems helps you work better with IT teams or even handle systems yourself in the future.

📘 Reference: Jean Andrews - A+ Guide to IT Technical Support

5. 📊 Statistical Methods 1

Now we’re talking real data science! Statistics is basically the brain of the field. Every analysis, prediction, and insight is built on statistical thinking.
From means and medians to standard deviations and hypothesis testing—you’ll meet them all here.

📘 Reference: Walpole, Myers, Myers, & Ye - Probability and Statistics for Engineers and Scientists

6. 🤖 Introduction to Data Science

This is your official welcome to the world of data science. You’ll learn:

  • What data science is all about

  • Who works in this field

  • What tools and skills are needed

  • And how the data science process flows from raw data to insight

📘 Reference: Joel Grus - Data Science from Scratch
📘 Additional: Cathy O'Neil & Rachel Schutt - Doing Data Science

🎯 Final Thoughts: Semester 1 Is Just the Warm-Up!

If your first semester feels like a mixed bag, that’s totally normal. You’re being set up with the core foundations that will support your future journey as a real data pro. So enjoy the ride, explore each subject, and never hesitate to dig deeper.

Remember: being a data scientist isn’t just about numbers—it’s about understanding the world through data. And this semester is your very first step.

Keep going, data warrior! 💪📈

📚 References:

  1. Stewart, J. (2015). Calculus: Early Transcendentals. Cengage Learning.

  2. Keraf, G. (2006). Komposisi: Sebuah Pengantar Kemahiran Bahasa. Nusa Indah.

  3. Laudon, K.C., & Laudon, J.P. (2020). Management Information Systems. Pearson.

  4. Andrews, J. (2019). A+ Guide to IT Technical Support. Cengage Learning.

  5. Walpole, R.E., et al. (2012). Probability and Statistics for Engineers and Scientists. Pearson.

  6. Grus, J. (2019). Data Science from Scratch. O’Reilly Media.

  7. O'Neil, C., & Schutt, R. (2013). Doing Data Science. O’Reilly Media.


Comments

Post a Comment