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What is the difference between baseline computer science and data science/analytics?
Can a business degree include data science? Also does it still count as a STEM field?
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3 answers
Updated
Leo’s Answer
TL;DR
Data science and analytics are subfields within computer science.
There are many business degrees with a data science or analytics focus.
I would consider a such a degree to be STEM related, others may disagree.
Computer science is the study of algorithms, data structures and computational processes. This is a software-focused field. While computer engineers design physical hardware, computer scientists design the methods to utilize that hardware. While we often think of this as programming, it is not. Programming is a method we use to implement the algorithms, data structures, and computing patterns. For instance, defining the steps required to implement a Netflix recommendation falls under computer science. Defining an efficient way to search for a single number within a list of 10,000 numbers also falls under computer science. Implementing these things in code falls more under software engineering. The two fields are closely related, but not the same thing. CS degrees often include both of these disciplines.
Data science and analytics are concerned with answering questions with data. Data scientists will develop and utilize algorithms for determining patterns in data. This is a broad field with many specializations. When we hear terms like deep learning, artificial intelligence, machine learning, we are generally hearing about data science. It is one of the many sub-fields within computer science. On any given day, a data scientists might create charts and graphs to make complex data easy to interpret. They may implement a machine-learning algorithm to predict failures in a power grid before they happen. They may even work on clinical drug trials to determine if a drug is likely to create a better outcome for patients.
To better understand data science, take a free course on Coursera
Data science and analytics are subfields within computer science.
There are many business degrees with a data science or analytics focus.
I would consider a such a degree to be STEM related, others may disagree.
Computer science is the study of algorithms, data structures and computational processes. This is a software-focused field. While computer engineers design physical hardware, computer scientists design the methods to utilize that hardware. While we often think of this as programming, it is not. Programming is a method we use to implement the algorithms, data structures, and computing patterns. For instance, defining the steps required to implement a Netflix recommendation falls under computer science. Defining an efficient way to search for a single number within a list of 10,000 numbers also falls under computer science. Implementing these things in code falls more under software engineering. The two fields are closely related, but not the same thing. CS degrees often include both of these disciplines.
Data science and analytics are concerned with answering questions with data. Data scientists will develop and utilize algorithms for determining patterns in data. This is a broad field with many specializations. When we hear terms like deep learning, artificial intelligence, machine learning, we are generally hearing about data science. It is one of the many sub-fields within computer science. On any given day, a data scientists might create charts and graphs to make complex data easy to interpret. They may implement a machine-learning algorithm to predict failures in a power grid before they happen. They may even work on clinical drug trials to determine if a drug is likely to create a better outcome for patients.
Leo recommends the following next steps:
Updated
Vamsi’s Answer
Computer Science delves into the wonderful world of a computer's inner workings and related systems, offering an exciting opportunity for those fascinated by technology. Data science, on the other hand, focuses on harnessing the power of data to craft meaningful stories that can drive impactful insights for companies. Business executives can then capitalize on these findings to make well-informed decisions.
When exploring the business side, it's important to strengthen your skills in statistics, as this will greatly aid in data analysis. With a solid foundation in Computer Science, you'll be well-equipped to collect data and implement machine learning models that can transform raw data into valuable information.
So, go ahead and embrace the exciting new challenges that lie ahead in the intersection of Computer Science, Data Science, and Business! The synergy of these fields can lead to endless possibilities and fulfilling achievements. Together, let's build a brighter future by turning data into actionable insights and informed decisions!
When exploring the business side, it's important to strengthen your skills in statistics, as this will greatly aid in data analysis. With a solid foundation in Computer Science, you'll be well-equipped to collect data and implement machine learning models that can transform raw data into valuable information.
So, go ahead and embrace the exciting new challenges that lie ahead in the intersection of Computer Science, Data Science, and Business! The synergy of these fields can lead to endless possibilities and fulfilling achievements. Together, let's build a brighter future by turning data into actionable insights and informed decisions!
Updated
Nicole’s Answer
Hi Neela. Terrific question!
In addition to the awesome answers already provided, I will add that for sure having a computer science background is a very helpful tool if one is interested in data science /analytics.
In my experience, the practice of using data to solve problems can expose you to building a good and sustainable relationship with your clients/partners/customers. The added benefit of having a computer science and/or programming background is the flexibility it can bring to the problem you are trying to solve. Oftentimes, that flexibility means you can move faster by implementing changes faster. Change...and being comfortable with change, is a large part of working in data and data analytics. Data changes all the time and so do the problems that need to get solved. If you are lucky, you get to solve one problem and then have the know-how to move on to solving another.
For sure data science can be and is big and splashy..AI and machine learning are very significant parts of data analytics. For people who are interested in the data analytics field, but are just starting their journey, there are numerous ways to learn and engage in data and trends that can be of benefit. I encourage you to consider learning a few programming languages as they can be very helpful building blocks whether your focus in business (fintech is a business focus where there is lots of data science/analytics) or another career path.
Hope you find this advice helpful. Best of luck to you!
In addition to the awesome answers already provided, I will add that for sure having a computer science background is a very helpful tool if one is interested in data science /analytics.
In my experience, the practice of using data to solve problems can expose you to building a good and sustainable relationship with your clients/partners/customers. The added benefit of having a computer science and/or programming background is the flexibility it can bring to the problem you are trying to solve. Oftentimes, that flexibility means you can move faster by implementing changes faster. Change...and being comfortable with change, is a large part of working in data and data analytics. Data changes all the time and so do the problems that need to get solved. If you are lucky, you get to solve one problem and then have the know-how to move on to solving another.
For sure data science can be and is big and splashy..AI and machine learning are very significant parts of data analytics. For people who are interested in the data analytics field, but are just starting their journey, there are numerous ways to learn and engage in data and trends that can be of benefit. I encourage you to consider learning a few programming languages as they can be very helpful building blocks whether your focus in business (fintech is a business focus where there is lots of data science/analytics) or another career path.
Hope you find this advice helpful. Best of luck to you!