Comparing and Contrasting AI and Data Science: What You Need to Know

Artificial Intelligence (AI) has been making significant progress and has contributed to various industries. However, there is a lot of hype around AI, and the terms AI, Data Science, Machine Learning, and Deep Learning are adding to the confusion. In this post, we will focus on AI and Data Science and explore how they differ.

Understanding AI:

AI is a computer program designed to perform tasks that come naturally to the human brain. These tasks involve skills such as understanding written language, detecting speech, recognizing objects from images, and optimizing time, among others. Although these tasks are innate to humans, they are challenging for computers. Therefore, computer algorithms that can learn and perform these tasks are classified as AI.

Understanding Data Science:

Data Science is an umbrella term that encompasses various methods and practices for extracting insights from data. The data can be anything from stock prices, voice recordings, sensor data, satellite images, etc. Data Science includes processing the data, performing statistical analysis, presenting the data in ways that others can understand, and more. The complexity of the analysis depends on the type of data and the problem that needs to be solved.

The Relationship Between AI and Data Science:

In some cases, AI needs Data Science to learn from data. Before a computer program tries to learn from data, it is often helpful for a human or a data analysis program to study the data. Data Scientists can clean the data, extract important elements, and feed these to an AI to learn better. On the other hand, some advanced AIs can sift through large volumes of data that have undergone minimal to no data pre-processing. In these cases, AI does not necessarily require classic data science.

Similarly, Data Science can be used independently to understand, explain, and communicate insights about data. However, AI can learn insights from data that are not visible with simple data science techniques, especially when the data is rich or when the data volume is significant.

In conclusion, AI and Data Science have a complementary relationship, and both are critical for businesses. In the future, we can expect a seamless relationship between the two, and there will be no need to pick one over the other.