It's been a crazy time for the world's economy - pandemic to the looming recession, the future of the world is hanging by a thin thread. Difficult times have led to difficult decisions, with companies across the world temporarily suspending hiring and laying-off manpower. Nevertheless, if there is one sector that has withstood these changing times would be the Information Technology sector. It goes without saying, doesn't it?

Technology's exponential growth creates both benefits and difficulties for businesses. "How so?" you might wonder. Massive amounts of data are being produced every second, thus increasing the need for professionals who can handle challenging issues. To improve the overall functioning and efficiency of technology-abled processes, companies need skilled individuals to comprehend difficulties and offer reliable solutions.

If you are someone who is looking to get into data science, we bring some interesting snippets from a recent conversation with Mr. Peter Webb Mulan, the director of the International Recruitment University of North Texas, PETA, and Mr Daryl Fong, COO of AECC. 

What is Data Science?

​Simply put, data science is the study of information, including where it comes from, what it conveys, and how to turn it into a resource with the potential to assist organizations in decision-making, problem-solving, and formulating plans to enhance performance. It is an interdisciplinary subject that combines technological expertise with business acumen to inspire impactful change.

Owing to its growing popularity in recent years, many prestigious universities around the world, including those in popular study-abroad destinations like Australia, Canada, the United States, the United Kingdom, New Zealand, and Ireland, are offering postgraduate programs on data science that covers the important aspects of artificial intelligence, machine learning, business analysis, and cloud computing. In fact, Mr. Peters also added that the University of North Texas is one of the first few universities which started offering Data Science master's courses even before it became popular.

Why is Data Science a high-in-demand course?

​Let's take a look at the skills a student must possess and develop after completing a Data Science degree.

• Data analysis and Modeling
• Problem-Solving
• Intellectual Curiosity
• Critical thinking
• Math and statistics
• Basic Coding Knowledge
• Market Understanding
• Business Acumen
• Communication and Collaboration
• Visualization and Presentation skills

No matter what the future holds, these skills that you acquire while studying Data Science are high-value and transferable skills that add great value to any field/sector that sustains or develops in the future. Mr. Peter also mentioned that one of his good friends who works as a human resource manager at the prestigious Toyota industries shared similar views.

What will you actually learn in Data Science?

The course curriculum for learning data science is comprehensive because the work of a data scientist encompasses a wide range of responsibilities and draws from a wide range of disciplines. Don't let the list scare you because data scientists, like other professions, learn just as much on the job as they do in school. It is estimated that you would need six to ten years to thoroughly study all the courses.

You will learn:

• 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

As you work toward earning a Masters in Data Science after completing your undergraduate studies, these subjects could be presented at various difficulty levels. Given the nature of the subject, even after gaining experience working as a Data Scientist for a while, you will continue to learn new things.

What does a qualified Data Scientist do?

​On any given day your job as a data scientist would look like this:

• Collecting enormous volumes of data and simplifying it in a format that is easy to analyze.
• Troubleshooting issues by utilizing tools and tactics powered by data.
• Using a range of programs and computer languages for data collection and analysis
• Using insightful data visualizations and thorough reports to convey results and provide guidance.
• Recognizing patterns and trends in data and offering a strategy to put improvements into practice.
• Predicting analytics; foreseeing upcoming needs, occasions, performances, trends, etc.
• Contributing to the techniques for data analysis, reporting, and modelling used in data mining.
• Creating innovative algorithms to address issues and providing analytical tools.
• Recommending affordable adjustments to current practices and tactics.

​Why you should consider Data Science as a career?

​In the interesting conversation that ensued on careers in Data Science, *Name* and *Name* summarised the top 3 reasons to consider applying to study data science in various prestigious worldwide.

Earning Potential

With the growing need for managing, analyzing, and utilizing data, data scientists are paid handsomely. With the ever-increasing need for talented data science professionals, companies would be willing to compensate you fairly.

​How does one apply to study Data Science?

• After you've narrowed down the colleges you want to apply to, you must visit their websites to learn more about the admissions requirements. A few requirements that are listed below, however, are common across all colleges:
• Transcripts
• Purpose Statement
• Character Reference Letters
• CV
• Evidence of language ability (TOEFL, IELTS, or PTE test scores)
• Test results (GRE or GMAT)
• Begin gathering these materials six months in advance of your application deadline.
• Proceed with submitting the application and await a response.
• If you are chosen for further consideration, you will receive a letter of acceptance which you may use to apply for a student visa and potentially a scholarship!

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

The amount will vary based on the country, college, and disciplines you decide to study. However, the cost of studying data science at the colleges mentioned above ranges from roughly $22,000 to about $75,000. The average cost of doing Data Science courses at any reputed university abroad is about $53,000.

Apart from the tuition fees, the cost of living, food, transportation, entertainment, and a few other everyday expenses will be part of your additional costs. Depending on the destination and the university you choose, this sum will change. Your living costs will increase if you decide to live in a city. In the same vein, it will cost you far more to study in the US, UK, or Singapore than it will in Canada, Germany, or the Netherlands.

If you are looking to enter the world of data science and want tips on selecting the right university and ensuring whether data science is really the right choice for your Master's, Pieter Vermuelen and Daryl Fong recently discussed all of it on a podcast. Do listen to it for free here - Listen Now