The CSE vs. Data Science debate is one of the most common debates nowadays among students. While CSE is considered the best career option in the field of engineering. On the other hand, Data Science is known as the future of computing. But is data science really as good as CSE? To find out, let's compare both fields side by side in this data science tutorial.
What is Data Science?
In simplest terms, Data Science is the branch of science that deals with the study of data. However, it is not where it ends. Data Science is becoming a very demanding field nowadays. The reason is the outcome that can be produced with Data Science.
In Data Science, the historically available data is studied with the help of algorithms and meaningful data is extracted from this raw data. This extracted data is then used for various purposes like prediction, AI training, machine learning, etc.
Nowadays, Data Science is being used in various fields. It can help in the prediction of choices that a customer may make based on the customer’s historical data. You may know it as a personalized approach to marketing. Data Science is also getting used to train Artificial Intelligence software to act and work like humans. Moreover, there are a lot of other uses for Data Science, making it a popular career option for tech enthusiasts.
What is CSE?
On the other hand, CSE is not a very new term. It has been there for many decades. CSE stands for Computer Science Engineering. It basically refers to studying computers and other related branches like networking. CSE has helped us to build various technologies.
Moreover, most part of the CSE deals with developing software for a computer. Similarly, the networking section deals with the improvement in networking between computers. All these three branches include CSE.
What are the differences between Data Science and CSE?
Area of Study
In Data Science, one should first know about CSE and the concepts of Data Science like machine learning and Artificial Intelligence. However, it doesn't require a very deep understanding of CSE, as only the area of software engineering is important.
Moreover, Data Science is a lot more based on practice and training. The reason is that Data Science ultimately trains the software, which requires human attention. It is also the reason for the lack of automation in Data Science.
On the other hand, CSE studies designing and developing software. It deals with creating new software, which includes system software, application software, SaaS and many more. In addition, it also includes the areas of studying the computer’s architecture and means of networking. Over the years, CSE has seen a lot of automation, to which Data Science has also contributed.
Career Options
There are comparatively fewer career options in Data Science than in CSE. Some careers you can pursue in Data Science are Data Analyst, Business Intelligence Analyst, Data Mining, Engineer, Data Architect, Applications Architect, Data Engineer, and Statistician.
In CSE, there are a lot of career options. The reason is that CSE deals with a wide range of specialities, whereas Data Science revolves around data extraction. By choosing the specialization according to your preference, you can become a Software Engineer, Hardware Engineer, Software Tester, Systems Analyst, Business analyst, Product manager, Network architect, Cloud computing engineer, Web Developer, Database Administrator and Network Architect.
There are a few more fields to explore in CSE, like Research and development (R&D) science, CSE or CSE research, Artificial intelligence and machine learning engineering, etc. These options lie more on the research side and require deeper knowledge.
Mandatory Skill Set
For Data Science, the skill set can be considered a subset of skills required for CSE and some unique skills.
In Data Science, the skills required are not a lot in number but need you to practice them perfectly. The skills you should acquire for Data Science are Machine Learning and Artificial Intelligence, Mathematics and Statistics, Data Visualization using Tableau and Excel, SQL Databases, Apache Spark and Hadoop, Python Programming and R Programming. Learning these skills will help you to become a successful data scientist.
On the other hand, CSE is about acquiring software-related skills. A large chunk of the skill set for CSE is made up of programming languages. You should learn programming, Software Development, Requirement Analysis, Software Testing, knowledge of IDE, Software Integration, Data Analysis, Creativity and Communication skills to become a successful computer programmer.
What are the similarities between Data Science and CSE?
Now since both fields are ultimately from a technical background, there are some similarities that both share. Firstly, the salaries in both fields are very high. Still, at the same time, it depends on your proficiency and knowledge of the respective fields.
Moreover, both of these fields share a common background in programming languages. However, the usage of programming languages differs in both fields. At last, the soft skills requirements of both profiles are the same such as excellent communication and teamwork.
What is EDA in Data Science?
EDA in Data Science stands for Exploratory Data Analysis. It is an important step in the data analysis process. Moreover, EDA in Data Science is typically performed at the beginning of a project. It helps to gain insights and make informed decisions about further analysis.
The primary goal of EDA in Data Science is to understand the structure of dataset, variables, and their meanings. It also helps in discovering trends, variations, and relationships between variables. It is important to uncover potential insights.
Moreover, Identifying outliers or unusual data points is also one of the goals of EDA in Data Science. Lastly, it also helps to Understand the distribution of data across variables. It is through visualizations like histograms, box plots, and density plots.
Final Words
In Conclusion, Data Science is powering some of the most important technologies for the future, like ML and AI. But CSE still provides a wide range of career options than Data Science.
So, choosing one of these should be based on which subject is easier to understand for you. However, Also, pursuing Data Science after CSE can be the best career option, as you will get the best of both worlds.
Hope this data science tutorial helped you gain valuable knowledge.
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