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Data Science with Python Certification.

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Data science is the process of deriving knowledge and insights from a huge and diverse set of data through organizing, processing, and analyzing the data. It involves many different disciplines like mathematical and statistical modeling, extracting data from its source, and applying data visualization techniques. Often it also involves handling big data technologies to gather both structured and unstructured data. Below we will see some example scenarios where Data science is used. The Applied data science with python is designed for Computer Science graduates as well as Software Professionals who are willing to learn data science in simple and easy steps using Python as a programming language.

Recommendation systems

As online shopping becomes more prevalent, e-commerce platforms are able to capture users’ shopping preferences as well as the performance of various products in the market. This leads to the creation of recommendation systems which create models predicting the shopper’s needs and showing the products the shopper is most likely to buy.

Financial Risk management

The financial risk involving loans and credits is better analyzed by using the customer’s past spending habits, past defaults, other financial commitments, and many socio-economic indicators. This data is gathered from various sources in different formats. Organizing them together and getting insight into customers’ profiles needs the help of Data Science. The outcome is minimizing loss for the financial organization by avoiding bad debt.

Improvement in Health Care services

The health care industry deals with a variety of data which can be classified into technical data, financial data, patient information, drug information, and legal rules. All this data need to be analyzed in a coordinated manner to produce insights that will save cost both for the health care provider and care receiver while remaining legally compliant.

Computer Vision

The advancement in recognizing an image by a computer involves processing large sets of image data from multiple objects of the same category. For example, Face recognition. These data sets are modeled, and algorithms are created to apply the model to newer images to get a satisfactory result. Processing of these huge data sets and the creation of models need various tools used in Data Science.

Efficient Management of Energy

As the demand for energy consumption soars, the energy-producing companies need to manage the various phases of energy production and distribution more efficiently. This involves optimizing the production methods, the storage, and distribution mechanisms as well as studying the customer’s consumption patterns.

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