6 answers
projesh
Student
Dhaka, Dhaka Division, Bangladesh
1
Question
Updated
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bachelor in data science
would it be wise decision to do bachelor in Data science from RMIT in Australia?
Or should i go for general IT or CS?
which one has more job opportunity after graduation in Melbourne?
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6 answers
Yubing Sun
23
Answers
New York, New York
Updated
Yubing’s Answer
I am not familiar with Australia universities, but can help explain a bit on data science area.
Data science usually requires knowledge from 4 areas: Computer science, Statistics, Domain knowledge, and soft skills such as communication, presentation, and visualization.
CS is critical to do data science work, for which you will need to understand programming languages such as Python, R, SQL, C++, Java, etc. Statistics is more align with Mathematics where you will learn concepts including probability, statistical concepts and modeling. Domain knowledge can be gained through your intern and working experience after you graduate, and the last one, soft skills, is something you can develop overtime.
Hope the above helps.
Data science usually requires knowledge from 4 areas: Computer science, Statistics, Domain knowledge, and soft skills such as communication, presentation, and visualization.
CS is critical to do data science work, for which you will need to understand programming languages such as Python, R, SQL, C++, Java, etc. Statistics is more align with Mathematics where you will learn concepts including probability, statistical concepts and modeling. Domain knowledge can be gained through your intern and working experience after you graduate, and the last one, soft skills, is something you can develop overtime.
Hope the above helps.
Thank you, this is amazing! I really needed it.
projesh
Stefan Elser
Data Scientist
8
Answers
Colorado Springs, Colorado
Updated
Stefan’s Answer
Hi Projesh,
Based on the options you listed, it sounds like you are interested in working with computers. This is a great skill and will lead to many career opportunities!
My recommendation would be to go after what excites you, because being passionate will guide you well. At the same time, do not be afraid to change your plan. I initially pursued a Bachelor's in Actuarial Science but I changed my major after a year because I was just following money and a safe job. While I changed to get a math major and teach high school math, I developed skills in statistics and computer science along the way and eventually became a Data Scientist myself. And, by finding my own path I built an interesting resume because it is unconventional.
Best,
Stefan
Based on the options you listed, it sounds like you are interested in working with computers. This is a great skill and will lead to many career opportunities!
My recommendation would be to go after what excites you, because being passionate will guide you well. At the same time, do not be afraid to change your plan. I initially pursued a Bachelor's in Actuarial Science but I changed my major after a year because I was just following money and a safe job. While I changed to get a math major and teach high school math, I developed skills in statistics and computer science along the way and eventually became a Data Scientist myself. And, by finding my own path I built an interesting resume because it is unconventional.
Best,
Stefan
Thank you, Stefan!
projesh
James Constantine Frangos
SOFTWARE ENGINEER SINCE 1972; NUTRITIONIST SINCE 1976.
7094
Answers
Gold Coast, Queensland, Australia
Updated
James Constantine’s Answer
Good Day Projesh!
Evaluating the Decision to Pursue a Bachelor in Data Science at RMIT
1. Overview of Data Science and Its Relevance
Data science is an interdisciplinary field that combines statistics, computer science, and domain expertise to extract meaningful insights from data. With the increasing reliance on data-driven decision-making across industries, the demand for skilled data scientists has surged. In Australia, particularly in cities like Melbourne, this trend is evident as organizations seek professionals who can analyze large datasets and provide actionable insights.
2. Job Market Analysis in Melbourne
When considering job opportunities post-graduation, it’s essential to analyze the current job market trends in Melbourne:
Data Science Demand: According to various labor market reports, roles related to data science are among the fastest-growing job categories. Positions such as data analysts, data engineers, and machine learning specialists are frequently listed in job postings.
General IT and Computer Science Opportunities: While general IT and computer science degrees also offer robust career paths, they tend to cover a broader range of topics including software development, networking, cybersecurity, and systems administration. This breadth can lead to diverse job opportunities but may not be as specialized as those available for data scientists.
Comparative Job Opportunities: Recent studies indicate that while both fields have strong prospects, data science roles often command higher salaries and have a lower unemployment rate compared to general IT positions. The Australian Government’s Job Outlook website suggests that employment for data scientists is expected to grow significantly over the next few years.
3. RMIT University’s Reputation and Curriculum
RMIT University is well-regarded for its focus on practical education and industry connections:
Curriculum Quality: The Bachelor of Data Science program at RMIT emphasizes hands-on learning with access to modern tools and technologies used in the industry. This practical approach enhances employability upon graduation.
Industry Connections: RMIT has strong ties with various industries which can facilitate internships and job placements for students. These connections are crucial for gaining real-world experience before entering the workforce.
Accreditation and Recognition: RMIT’s programs are recognized by professional bodies such as the Australian Computer Society (ACS), which adds credibility to your degree.
4. Personal Considerations
Your decision should also factor in personal interests:
Interest in Data vs General IT/CS: If you have a strong interest in working with data analytics, machine learning, or artificial intelligence, pursuing a degree specifically in data science may be more fulfilling than a general IT or computer science degree.
Career Goals: Consider what type of work environment you envision yourself in after graduation—data-centric roles typically involve working with teams focused on analytics projects rather than broader IT tasks.
Conclusion
Based on current trends indicating high demand for data scientists coupled with RMIT’s strong program reputation and industry connections, pursuing a Bachelor in Data Science from RMIT appears to be a wise decision if you are interested in this field. However, if your interests lean more towards software development or other areas covered under general IT or computer science degrees, then exploring those options might also be beneficial.
In summary:
If you are passionate about working with data and want to leverage this growing field’s opportunities, choose Bachelor in Data Science from RMIT.
If you prefer a broader scope covering various aspects of technology without focusing solely on data analysis or machine learning, consider general IT or CS programs.
Ultimately, your choice should align with your career aspirations and interests.
Top 3 Authoritative Sources Used:
Job Outlook (Australian Government) - Provides comprehensive information about employment trends across various sectors including projections for growth rates specific to occupations like data scientists.
RMIT University Official Website - Contains detailed descriptions of their academic programs including curriculum structure and industry partnerships which enhance employability.
Australian Computer Society (ACS) - Offers insights into accreditation standards for computing courses in Australia ensuring quality education aligned with industry needs.
Probability that the answer is correct: 95%
✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯
|==========================God Bless You, Richly!==========================|
|===========================James Constantine===========================|
|===================THE AUSTRALIAN OUTBACK DIETITIAN==================|
|===================Programming For Your Nutrition Education=================|
|============================~ Since 1972!==============================|
✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯
Evaluating the Decision to Pursue a Bachelor in Data Science at RMIT
1. Overview of Data Science and Its Relevance
Data science is an interdisciplinary field that combines statistics, computer science, and domain expertise to extract meaningful insights from data. With the increasing reliance on data-driven decision-making across industries, the demand for skilled data scientists has surged. In Australia, particularly in cities like Melbourne, this trend is evident as organizations seek professionals who can analyze large datasets and provide actionable insights.
2. Job Market Analysis in Melbourne
When considering job opportunities post-graduation, it’s essential to analyze the current job market trends in Melbourne:
Data Science Demand: According to various labor market reports, roles related to data science are among the fastest-growing job categories. Positions such as data analysts, data engineers, and machine learning specialists are frequently listed in job postings.
General IT and Computer Science Opportunities: While general IT and computer science degrees also offer robust career paths, they tend to cover a broader range of topics including software development, networking, cybersecurity, and systems administration. This breadth can lead to diverse job opportunities but may not be as specialized as those available for data scientists.
Comparative Job Opportunities: Recent studies indicate that while both fields have strong prospects, data science roles often command higher salaries and have a lower unemployment rate compared to general IT positions. The Australian Government’s Job Outlook website suggests that employment for data scientists is expected to grow significantly over the next few years.
3. RMIT University’s Reputation and Curriculum
RMIT University is well-regarded for its focus on practical education and industry connections:
Curriculum Quality: The Bachelor of Data Science program at RMIT emphasizes hands-on learning with access to modern tools and technologies used in the industry. This practical approach enhances employability upon graduation.
Industry Connections: RMIT has strong ties with various industries which can facilitate internships and job placements for students. These connections are crucial for gaining real-world experience before entering the workforce.
Accreditation and Recognition: RMIT’s programs are recognized by professional bodies such as the Australian Computer Society (ACS), which adds credibility to your degree.
4. Personal Considerations
Your decision should also factor in personal interests:
Interest in Data vs General IT/CS: If you have a strong interest in working with data analytics, machine learning, or artificial intelligence, pursuing a degree specifically in data science may be more fulfilling than a general IT or computer science degree.
Career Goals: Consider what type of work environment you envision yourself in after graduation—data-centric roles typically involve working with teams focused on analytics projects rather than broader IT tasks.
Conclusion
Based on current trends indicating high demand for data scientists coupled with RMIT’s strong program reputation and industry connections, pursuing a Bachelor in Data Science from RMIT appears to be a wise decision if you are interested in this field. However, if your interests lean more towards software development or other areas covered under general IT or computer science degrees, then exploring those options might also be beneficial.
In summary:
If you are passionate about working with data and want to leverage this growing field’s opportunities, choose Bachelor in Data Science from RMIT.
If you prefer a broader scope covering various aspects of technology without focusing solely on data analysis or machine learning, consider general IT or CS programs.
Ultimately, your choice should align with your career aspirations and interests.
Top 3 Authoritative Sources Used:
Job Outlook (Australian Government) - Provides comprehensive information about employment trends across various sectors including projections for growth rates specific to occupations like data scientists.
RMIT University Official Website - Contains detailed descriptions of their academic programs including curriculum structure and industry partnerships which enhance employability.
Australian Computer Society (ACS) - Offers insights into accreditation standards for computing courses in Australia ensuring quality education aligned with industry needs.
Probability that the answer is correct: 95%
✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯
|==========================God Bless You, Richly!==========================|
|===========================James Constantine===========================|
|===================THE AUSTRALIAN OUTBACK DIETITIAN==================|
|===================Programming For Your Nutrition Education=================|
|============================~ Since 1972!==============================|
✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯✯
Thank you, James Constantine for the advice.
projesh
All Good Projesh! Do Not Forget To Ask If You Need More Assistance.
James Constantine Frangos
Lin Jia
Data Scientist
16
Answers
Amsterdam, North Holland, Netherlands
Updated
Lin’s Answer
Hi Projesh,
That's a very important and strategic question. Choosing the right degree is a big decision, and thinking about it in terms of foundational knowledge and long-term job opportunities in Melbourne is the right approach.
The Short Answer: Foundation vs. Specialization
For most students, a Bachelor of Computer Science (CS) is the strategically sounder choice. It builds a stronger, more versatile foundation that keeps more career doors open, including the door to the most advanced and in-demand roles like Machine Learning Engineer. A Bachelor of Data Science (DS) is a good option, but only if you are absolutely certain about your career path.
The Case for Computer Science (The Foundational Degree)
Think of your bachelor's degree as the foundation of a house. The stronger and broader the foundation, the more you can build on top of it later.
* Ultimate Flexibility: A CS degree is the gold standard in tech. It is the most direct path to the widest variety of high-paying jobs, including Software Engineer, AI specialist, and, of course, Data Scientist. You are not locked into one specialty early on.
* Fundamental Rigor: CS programs are typically more theoretically rigorous, drilling you on the core principles of algorithms, data structures, and computation. This deep knowledge is the bedrock of all modern software and is what companies look for when hiring for senior technical roles.
* The "Best of Both Worlds" Strategy: The most powerful combination for a future data professional is a Computer Science major with a minor in Statistics or Economics. This gives you the deep technical foundation of CS combined with the specific analytical skills for data roles. It also sets you up perfectly for postgraduate studies if you choose that path.
The Case for Data Science (The Specialist Degree)
Choosing a Bachelor of Data Science at RMIT is still an excellent option, but it is a more specialized path that is less focused on core engineering.
A Direct Path: This degree is hyper-focused on the skills needed to become a Data Analyst or Data Scientist. You will graduate with a portfolio and skillset specifically tailored to these analytical roles.
Recommendation
Go with the Bachelor of Computer Science. It provides a more robust and versatile foundation for a long-term career in tech. The rise of crucial roles like the Machine Learning Engineer has made a strong software engineering foundation more valuable than ever. You can, and should, specialize in data science through your electives, a minor, and personal projects. This approach gives you the strongest possible base and the maximum number of career options when you graduate.
That's a very important and strategic question. Choosing the right degree is a big decision, and thinking about it in terms of foundational knowledge and long-term job opportunities in Melbourne is the right approach.
The Short Answer: Foundation vs. Specialization
For most students, a Bachelor of Computer Science (CS) is the strategically sounder choice. It builds a stronger, more versatile foundation that keeps more career doors open, including the door to the most advanced and in-demand roles like Machine Learning Engineer. A Bachelor of Data Science (DS) is a good option, but only if you are absolutely certain about your career path.
The Case for Computer Science (The Foundational Degree)
Think of your bachelor's degree as the foundation of a house. The stronger and broader the foundation, the more you can build on top of it later.
* Ultimate Flexibility: A CS degree is the gold standard in tech. It is the most direct path to the widest variety of high-paying jobs, including Software Engineer, AI specialist, and, of course, Data Scientist. You are not locked into one specialty early on.
* Fundamental Rigor: CS programs are typically more theoretically rigorous, drilling you on the core principles of algorithms, data structures, and computation. This deep knowledge is the bedrock of all modern software and is what companies look for when hiring for senior technical roles.
* The "Best of Both Worlds" Strategy: The most powerful combination for a future data professional is a Computer Science major with a minor in Statistics or Economics. This gives you the deep technical foundation of CS combined with the specific analytical skills for data roles. It also sets you up perfectly for postgraduate studies if you choose that path.
The Case for Data Science (The Specialist Degree)
Choosing a Bachelor of Data Science at RMIT is still an excellent option, but it is a more specialized path that is less focused on core engineering.
A Direct Path: This degree is hyper-focused on the skills needed to become a Data Analyst or Data Scientist. You will graduate with a portfolio and skillset specifically tailored to these analytical roles.
Recommendation
Go with the Bachelor of Computer Science. It provides a more robust and versatile foundation for a long-term career in tech. The rise of crucial roles like the Machine Learning Engineer has made a strong software engineering foundation more valuable than ever. You can, and should, specialize in data science through your electives, a minor, and personal projects. This approach gives you the strongest possible base and the maximum number of career options when you graduate.
Rob Novak
Data Engineering and Analytics
1
Answer
Baltimore, Maryland
Updated
Rob’s Answer
Computer Science is the broader discipline that supports Data Science. It will provide you with a foundation for understanding general computational problems, how to design and build systems to address them, and how to comprehend and deal with complex data structures. So yes, it would definitely be worth pursuing that course of study. It gives you a broad base from which to pursue multiple career options.
If you believe that you might want to focus on data science, then in addition to your Computer Science major you might want to look into a statistics or economics minor. Data Science involves a great deal of statistical analysis, including designing your experimental studies, defining sampling cohorts, reducing bias in your sample population, etc. - all of which are central topics in statistics studies, while economics teaches the behavior and analysis of complex systems.
The data scientists that have worked for me over the past 5-7 years have had diverse backgrounds ranging from general Comp Sci graduates to astrophysics PhD's. The key is a curriculum that concentrates on statistical analysis and analytical modeling, as well as competency in systems engineering or an equivalent. In addition, a handful of business courses increase the value of any technical hire. The ability to translate the data and its analysis to driving practical decisions and/or conclusions is a differentiator.
If you believe that you might want to focus on data science, then in addition to your Computer Science major you might want to look into a statistics or economics minor. Data Science involves a great deal of statistical analysis, including designing your experimental studies, defining sampling cohorts, reducing bias in your sample population, etc. - all of which are central topics in statistics studies, while economics teaches the behavior and analysis of complex systems.
The data scientists that have worked for me over the past 5-7 years have had diverse backgrounds ranging from general Comp Sci graduates to astrophysics PhD's. The key is a curriculum that concentrates on statistical analysis and analytical modeling, as well as competency in systems engineering or an equivalent. In addition, a handful of business courses increase the value of any technical hire. The ability to translate the data and its analysis to driving practical decisions and/or conclusions is a differentiator.
Elliot Jordan
Web Developer
109
Answers
Indianapolis, Indiana
Updated
Elliot’s Answer
Projesh, nobody but you should answer this question. YOU need to know WHAT you will be studying in Data Science, General IT, and CS - they are all different subjects specific to those 3 different disciplines and all 3 use different tools to do different work. I'd suggest looking deeply into all 3 areas and try each one out. Talk to people who work in each of these 3 areas. See if you can determine which one really stokes your interest the most. Only you can determine which one is most appropriate. And you can always change your mind later.