Here are 3 points that tell the difference between Data Science and Computer Science.
- Data Science typically deals with a vast amount of structured, semi-structured, and unstructured data. At the same time, Computer Science focuses on solving problems in terms of instructions and instructions implemented in programming languages.
- Data Science uses sophisticated mathematical methods and data exploration to make predictions and develop insights, while Computer Science studies computer architecture and the interaction of software and hardware.
- Data Science heavily uses data mining, data visualization, and text mining, while Computer Science focuses on understanding principles of computation and algorithms, program design, and language.
A career in Data Science.
If you’re looking forward to making a career in data science, there cannot be a better time than now to get started.
This guide will help you through the process and provide a clear roadmap to start your data science career.
Step 1: Learn the Fundamentals of Data Science
Data science includes machine learning, statistical analysis, data visualization, artificial intelligence, and more. To get started, you must know the basic concepts of these different disciplines. Take some time to learn the fundamentals of data science, including algorithms, programming languages, and data structures.
Step 2: Build Your Portfolio
Data science is very competitive, so you’ll need a portfolio that stands out. Gather projects that showcase your data science skills and focus on quality, not quantity. Also, document your processes, methods, and results, as this will give recruiters and hiring managers an insight into how you think and approach data science problems.
Step 3: Network and Get Hired
Data science job postings are constantly growing, and recruiters often look for candidates with a great network. Get in touch with the right people and expand your network. Attending conferences, hackathons, and meetups related to data science is a great way to find potential opportunities.
Step 4: Advance Your Career
Now that you have the basics down, you’ll need to stay updated with the latest trends and advancements in data science. Take advantage of opportunities to improve your skill set, such as enrolling in advanced courses, participating in data science challenges, or even pursuing a degree in the field.
A career in Computer Science
Starting a career in computer science can be daunting, especially if you’re unfamiliar with the field. Regardless of how you get there, these steps will help you take the first steps on your computer science career journey.
Step 1: Understand what computer science is.
Computer science is a vast and diverse field that involves designing, building, and maintaining computer systems and creating software for those systems. To start your career, you’ll need to have a solid understanding of the concepts, processes, and technology associated with computer science.
Step 2: Get formal education.
Depending on the role you’d like to have, a formal education may be necessary to enter the field. A graduate position in computer science is an excellent place to start, and many universities also offer masters and doctorate programs. You can also consider online programs and boot camps to gain relevant skills quickly.
Step 3: Seek certifications.
Industry certifications can show potential employers that you’re well-versed in computer science and its various applications. Popular certifications include those related to programming languages, databases, software development, system architecture, and cybersecurity.
Step 4: Build a portfolio.
You’ll need to demonstrate your knowledge and skills to get recognized in the competitive job market. It means creating a portfolio of projects, experiences, and credentials. Employers will want to see that you have a solid technical understanding and problem-solving skills, good communication, and a commitment to professional development.
Step 5: Look for opportunities.
You may find an entry-level position at a company with some research or networking, but there are also many opportunities to gain experience and make connections online. Look for volunteer or remote places, or explore online job boards, such as Glassdoor, to find opportunities in your area.
Data Science vs. Computer Science Salary
The average salary of a computer scientist and data scientist can vary significantly depending on the company, role, and industry they work.
According to a Robert Half Technology report, computer scientists typically earn higher salaries than data scientists. The median salary for computer scientists was $113,937 per year as of May 2020. Data scientists, meanwhile, had a median salary of $101,196 during the same period.
However, looking at salary ranges, it’s important to note that the lower range of salaries for computer scientists is lower than for data scientists.
Data scientists have an advantage when it comes to flexibility and location. Many data science jobs are remote, allowing employees to work from anywhere.
Is Data Science harder than Computer Science?
The significant difference between Data Science and Computer Science in terms of difficulty is minor. It depends on various factors, including the individual’s particular skill set and level of knowledge.
Computer Science involves a more structured approach, involving algorithms and programming languages to complete a specific task or solve a problem. It often requires understanding many core principles, like software engineering, database design, networking, and system security.
On the other hand, data science focuses on leveraging data to generate meaningful insights. It is often more flexible and relies on data and problem-solving techniques than computer science.
