Artificial intelligence vs. data science is known to be closely related; however, they are not the same. So, what is the difference between them?
While Data Science has gained global popularity, the concept of AI is still quite vague to many people. Let’s compare them to find the answer to the question “Artificial intelligence vs. data science: Which is for you?”
Artificial Intelligence (AI) and Data Science (DS): Which Is For You?
Each field comes with its own advantages. Therefore, you should choose a career that best suits your skills, interests, and capabilities.
The critical differences in skills and knowledge required for specific roles will ultimately shape the journey to proficiency and your career projection.
Whatever industry you choose, you will have a bright future if you work hard.
If you want to choose an appropriate field, it is essential to understand these fields and what it entails. So let’s discuss them more to find out the differences.
What Is Data Science?
Data science deals with the analysis of unstructured data to gather valuable insights. DS is a combination of different fields such as statistics, computer science, scientific methods, and processes for extracting data.
This field brought us the fourth industrial revolution. Nowadays, it is one of the main factors in making business decisions.
Most companies and businesses realize the great value of this sector. So, businesses of all sizes are taking advantage of this sector daily.
The more data an organization has, the better and more detailed information it can gather about the business.
Companies like Airbnb use it to analyze and process customer-generated data to predict customer behaviors. As a result, the company solves service problems and improves services and products to provide the best value for customers.
Even banks and insurance companies extract contact information using industry methods. This field of science includes basic procedures and steps such as data extraction, manipulation visualization, and data maintenance.
Scientists in this industry are expected to know various concepts and technologies, including AI and machine learning algorithms. If you are interested in working with AI, you can also pursue a career in this area.
What Is Artificial Intelligence?
Artificial intelligence, also known as AI, refers to a complex set of computer algorithms that simulate and mimic human intelligence.
Computers programmed with AI can learn to acquire knowledge as they work. They will get better as more data is received.
Besides, it also deals with image recognition, translations to understand the human voice, speech recognition, and the decision-making process.
AI is a product created by humans, developed to allow computers to read, learn and understand data, which is very useful for the decision-making process of businesses. These decisions are made from deductions that are difficult for humans to make.
Al can also handle tasks such as translation, sound and object recognition, and, say, and significantly engage in business and social transactions.
Applications of this field also refer to sensory technologies, or self-driving cars, also known as autonomous vehicles. This vehicle operates on creative memory and ai. It uses algorithms to understand designs and patterns.
Algorithm implementations are so advanced and modern that humans can operate them from different devices, including laptops or smartphones.
What’s The Difference?
After learning about these technologies, it’s time to compare them in some striking aspects to find out the differences.
For data science, you need to possess the following skills
- Proficient in using languages such as C++, C, R, and Python.
- Reporting and visualization of data
- Knowledge about mathematics and statistics
- Understanding of Machine Learning techniques
- Experience in risk analysis
- Knowledge of data warehousing and data structures
The following are the skills required for the field of AI:
- Proficient in using languages such as C++, Java, and Python.
- Knowledge of data evaluation and data modeling
- Expert knowledge of Machine Learning algorithms
- Distributed computing
A data scientist can get an average salary of around $116,654 per year. Companies accept to pay high salaries to these scientists to drive business decisions.
Even the starting salaries in this growing field are attractive. For example, an entry-level scientist can earn $93,167 per year, while experienced scientists can get $142,131 per year.
The average annual salary that an AI engineer can receive is around $100,000.
Besides, as career opportunities for AI engineers rapidly develop and expand, the salaries of engineers in this field will continue to increase.
If you pursue the AI field, you have the opportunity to get many high-paying jobs available in top organizations. Here are a few positions you can expect to get.
- Robotics Scientists
- Data Scientists
- Machine Learning Engineers
- Software Developers
- Big Data Engineers
- Business Intelligence Developers
- AI Research Scientists
Here are some high-paying jobs you can get while pursuing data science:
- Database Administrator
- Machine Learning Engineer
- Business Analyst
AI is a vast land containing many things to explore. Meanwhile, DS uses AI to generate predictions and focuses on transforming data for analysis.
Knowing where you want to be with your career and the knowledge you need to utilize will allows you to decide your career.
Hopefully, this article has provided you with useful knowledge on the topic of ‘artificial intelligence vs. data science‘. Don’t forget to share with me your experiences and thoughts!