What is Data Science | DATA SCIENCE in 3 minutes | Application of data science | Quantra
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Data science, in simple terms, is using data to draw an inference or predict an outcome. Such information can help us make better decisions. For instance, say you want to choose your next destination for vacations. You would like to find a perfect place that fits your budget, your activity or interest, recommended trip duration, language, food and cultural preferences, security and political scenario and other factors. Let us say there is a tool which can predict your next dream vacation location, considering all these above-mentioned points.
Can you guess how that tool might work?
A simplistic one would have all these data points for say a thousand locations across the globe. Based on your inputs, it will come with a cumulative score, which we will call “Vacation preference score” or VPS for short. It will recommend you locations that are close to your VPS.
Sounds simple enough. The complexity lies in collecting relevant data for all these locations, cleaning it, quantifying it, and calculating VPS.
A location can be cheap or expensive based on average one-night hotel rate. This data can be downloaded from a hotel booking website. The political scenario can be found from news websites using Natural Language Processing tools. The recommended trip duration can be found on popular vacation websites.
You might find that you haven’t got any data on some locations for a political scenario or recommended trip duration. These fields might need to be updated with a “default” value.
Once you have all the data at hand, you need to come up with a method to calculate VPS. An average of all scores might not work. You might need to standardize your numbers. You might need a weighted average. You might need a regression analysis and so on. There are plenty of data analysis techniques which you can work with.
What matters is, how relevant your list of choices was. Did your model predict Timbuktu when actually your choice was Bora Bora? Or did you recommend your friend to go to the Zermatt when actually she wanted to go to Miami? It is quite important to test the accuracy of your analysis by working with different data points.
With the advent of Data Science, almost everyone relies on data to make better decisions. To choose an insurance plan, to find a restaurant, to select an internet plan, to create a marketing campaign, every decision maker now relies on data. Hence, every domain requires data scientists and analysts.
In this course, you will learn to play with data from the field of sports. We all love to predict the winning team. Now let us use data to help us make informed predictions.
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