Everything you need to know about studying Data Science

In 2023, from the episodes you binge on Netflix to your Instagram scrolling habits and shopping preferences, data plays a pivotal role. Leading companies like Google, Amazon, Apple, and YouTube are harnessing vast amounts of information. With the surge in data comes the rising demand for Data Scientists—experts adept in data management, possessing stellar computational abilities, deep mathematical knowledge, and a sharp business acumen. Interested in joining this cutting-edge field? You’re in the right spot. Dive into this guide to discover all about studying Data Science in today’s digital age.

What is Data Science?

Let’s start with the word “data.” Have you ever thought about how much data gets generated every day? YouTube users watch 1.4 million videos a minute, Google delivers results to 3.6 searches in 60 seconds. And Wikipedia gets edited 10 times per second. So, what do we do with all this data?

We study it. To be more specific, those who know Data Science do. Data Science helps us understand and make sense of huge amounts of data (like millions of minutes of video) to draw helpful conclusions (like the ideal length of a video) about it. Using these conclusions, governments and organizations can improve themselves exponentially, making the world a much better place to live in. 

What does a Data Scientist do?

As simple as I have made it sound, the job of a Data Scientist is not easy. You have to collect data from different sources, remove the bits and pieces you don’t need, and decide which parts of the data are important.

Then, you have to find the best way to process this data and transform your results into charts and bar graphs that are easy to understand.

The next step is to process this data live and generate results in real-time. This is so that others can easily understand the conclusions that you have drawn.

Each stage requires a Data Scientist to have a different set of skills. And each one of them is super cool. Let’s look at them in the next section.

What skills should a Data Scientist have?

As I’ve already mentioned, Data Science is a complex, interdisciplinary field. Learning it will involve picking up a hoard of different skills from each of these four domains – including Business Mathematics, Computer Science, and Communication. These skills are – 

• Mathematics
• Statistics
• Advanced Computing
• Visualization
• Data Engineering
• Advanced Computing
• Scientific Method
• Business Acumen
• Hacker Mindset

What subjects will I learn?

In 2023, the multifaceted role of a Data Scientist draws from a plethora of fields, making the study curriculum for Data Science rich and comprehensive. However, don’t be daunted by the expansive list. Much like other professions, Data Scientists often learn as much on the job as they do in academic settings. Anticipate dedicating 6 to 10 years to delve deep into these subjects, enriching your expertise along the way.

• Statistics
• Information Visualization
• Natural Language Processing
• Data Mining, Data Structures, and Data Manipulation & Modeling
• Machine Learning Algorithms
• Data Acquisition & Data Science Life Cycle
• Working with Real-World Data Sets
• Experimentation, Evaluation, and Project Deployment tools
• Predictive Analytics and Segmentation using Clustering
• Applied Mathematics
• Informatics
• Big Data
• Computer Programming
• Business & Accounting
• Econometrics
• Macroeconomics & Finance
• Communication Skills

These topics may be covered at different levels of difficulty as you go from pursuing your undergraduate degree to graduating with a Masters in Data Science. And it’s pretty likely that you will find yourself learning new things even after having worked as a Data Scientist for years.

Top universities for Data Science

A data science course and online lectures will take you only so far. If you are really serious about studying data science, you should consider pursuing a degree in it. While most students choose to study it as they pursue a Masters in Data Science, you can also specialize in the subject when you’re doing your undergrad.

Here are the world’s 10 top universities that offer a Data Science course-

1. Stanford University
2. Harvard University
3. Yale University
4. University of Pennsylvania
5. John Hopkins University
6. University of California, Berkeley
7. Columbia University
8. University of Michigan, Ann Arbor
9. New York University
10. University of California, San Diego

If you choose to apply, you should know that there are 2 intakes every year. The Fall intake happens in August, and the Spring intake takes place in January. I suggest you visit the course websites of the universities you are interested in, take a look at their individual deadlines (December for Fall courses and May for Spring programs), and start your application process accordingly.

What are the application requirements?

After you’ve shortlisted the universities you want to apply to, you will have to go through their websites and find out the admission requirements. However, a few requirements are common across all universities.

You will need to provide –

• Transcripts
• Statement of Purpose
• Letters of Recommendation
• CV
• Proof of language proficiency (TOEFL, IELTS, or PTE test scores)
• Standard test scores (GRE or GMAT)

I suggest you start preparing these documents 6 months before you have to apply. After you submit your application, it is time to wait. If shortlisted, you will receive a letter of acceptance, which you can then use to apply for a student visa (and even a scholarship)!

How much does it cost to get a degree in Data Science?

The amount will change depending on which country, university, and subjects you choose to study. But for the universities listed above, the cost of studying Data Science ranges from around 22,000 USD to about 75,000 USD. And the median cost to study Data Science in top universities is around 53,000 US dollars.

And that’s just the tuition fees. Your additional expenses will include the cost of living, food, transport, entertainment, and a few other daily spendings. This amount will vary depending on the country and the university you pick. If you choose to live in the city, your living expenses will go up. Similarly, studying in countries like the US, UK, and Singapore will cost you a lot more than studying in Canada, Germany, or the Netherlands.

To offset your fee and living costs, you can always work part-time, get a teaching assistantship, or apply for a scholarship. They will help you a long way when it comes to funding your education in Data Science.

What about Data Science jobs?

Even though there has been a need to understand and manage data ever since the late 1990’s, the field of Data Science is relatively new. Most skilled Data Scientists haven’t really studied the subject as a part of their syllabus but learned it themselves using online study materials and courses. And the universities are still perfecting their curriculum on the subject.

Even so, depending on their knowledge and area of expertise, Data Scientists are assigned various roles. These Data Science jobs include Data Analyst, Machine Learning Engineer, Deep Learning Engineer, Data Engineer, Data Scientist, and of course, Data Scientist.

Now, because the job is so demanding and requires a person to have a diverse set of skills, it is also one of the highest-paid jobs of all time. Data Scientists earn between 100,000 US dollars and 128,000 USD for entry-level positions.

With time, this salary can progress to 250,000 USD, when you reach a good level of expertise and become the Data Scientist you had always wanted to be. 

Now that I have shared the basics of studying Data Science with you, I have a question.

Do you want to learn it?

Let me know in the comments section!

Until then, ciao!