Although artificial intelligence and data science stem from the same source, they are not alike. Unfortunately, in the modern world, we often use these terms and mistake one for the other.
Branching from the world of computer science, artificial intelligence and data science are two different terms and apply to two separate streams of education. Moreover, data scientists and artificial intelligence engineers have entirely different jobs.
If you are still confused about which is which, then here is some information to enlighten you. I have gone through rigorous research to offer you the ideal differences between artificial intelligence and data science.
I have not only offered a difference based on their definitions, but I have also offered a comparison based on what professionals from both of these platforms do daily. So, let me start by defining what each of the fields is and how they work.
What Is Artificial Intelligence?
Artificial intelligence is a stream of computer science where engineers make intelligent machines capable of handling tasks that require human intelligence.
AI is a combination of intricate computer algorithms that can learn and adapt to solve specific types of problems. These intelligent machines are also great at mimicking human behaviors.
Some of the other attributes of artificial intelligence include translation, understanding human speech, decision making, and image recognition. Artificial intelligence is meant to learn from data and understand. Based on the functionality of artificial intelligence, there are two types of artificial intelligence: general AI and applied AI.
Tasks like speaking, translation, and speech and image recognition are tasks that general AI can handle.
On the other hand, applied artificial intelligence can handle technologies; for instance, autonomous vehicles run using applied artificial intelligence.
Applied artificial intelligence works by understanding patterns and designs. With innovative memory and sensory technologies applied artificial intelligence can drive cars.
What Is Data Science?
Data science is the process where the extraction of valuable, intuitive, and unstructured data occurs. The interdisciplinary approach of data science merges several fields of computer science, statistics, and the scientific process for extracting valuable data from raw data points.
Data science is currently at the heart of the business world. It helps with business decision-making. Thousands of companies now understand the value of data analysis and processing.
Some of the crucial steps of data science are:
- And Data Maintenance.
As a data scientist, you need to know diverse aspects of technology; from artificial intelligence to machine learning algorithms, a data scientist needs to do a lot.
Difference Between Artificial Intelligence And Data Science
Data science vs artificial intelligence; what are the differences between two of these different technology streams? Here is a detailed comparison between artificial intelligence and data science; it will help you distinguish between two of them.
- Artificial intelligence implements predictive models for foreseeing events. On the other hand, data analysis takes place through pre-processing unstructured data, prediction, and visualization.
- Algorithm Design, development, conversation, efficiency, and the deployment of these products come under artificial intelligence. Design techniques, statistical techniques, and development methods come under the umbrella of data science.
- A data scientist needs to have skills such as Python or R, Jupyter Notebook, TensorFlow, Statistics. On the other hand, in AI, one needs to use TensorFlow, sci-kit-learn, and Kaffee. In data analysis, a data scientist needs to work with data analysis. They work with past and present data to determine future data. Artificial intelligence concerns itself with machine learning.
- A data scientist looks for hidden patterns and trends in data science. The process incorporates the extraction, processing, understanding, and utility of the extracted data. The ultimate use of the extracted data helps in making decisions. On the other hand, artificial intelligence avoids human involvement entirely. The AI can handle the data and use it autonomously.
- Data scientists can build complex models using data science. These models can extract statistical techniques and various facts and insights. On the other hand, Artificial intelligence can make models for emulating cognition and a certain level of human understanding. Artificial intelligence aims to create a self-sufficient entity that will require no input from a human.
Frequently Asked Questions (FAQs):
After going through the previous sections, I hope you have gained some insight into artificial intelligence and data science. However, if you still have some queries, some of these questions that people frequently ask about on the internet may help.
1. What Is Data Science Used For?
The difference between artificial intelligence and data science can be better understood by understanding what they are used for. Here are some of the uses of data science-
- Data science helps to identify patterns and trends.
- Data science helps with statistical insight.
- If there is a need for exploratory data analysis, data science is helpful.
- Data science can help with rapid mathematical processing.
- If there is a need for predictive analysis, data science can help.
2. What Is Artificial Intelligence Used For?
AI is used on different platforms and for various reasons. Here are some of the ways that an AI can help-
- AI helps with precision.
- If there is a need for fast analysis and decision-making, AI can help.
- Logical decision-making without the interference of emotions is possible using an AI.
- If a task requires repetitive action of a certain work, then artificial intelligence can help.
3. Is Data Science A Good Career?
Data science is indeed a promising career if you proceed with passion. In the United States, it is the most desired career. The median salary for a data scientist is around $108000. In 2019 it was ranked as the top promising job LinkedIn. Surprisingly the data science organizations suffered no loss during the covid pandemic.
As stated in this article, artificial intelligence and data science are not the same things. They indeed branch from the same platform, computer science, but they have different use cases and characteristics.
AI is becoming increasingly popular in businesses and technological farms. As for data science, it offers excellent data solutions and decision-making in industry and other platforms. I hope this article will help you understand the difference between data science and artificial intelligence.