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Applications and Role of Data Science
Company payroll, employee information, customer information, customer reviews, etc. The company always wants this information to be simple and comprehensive so that they can make better, accurate decisions and future policies. This is when data science comes in handy.
Data science helps customers make the right decisions from the right information from large amounts of mixed data. Data scientists use their extensive skills in mathematics, business, programming, and statistics to clean and organize data into useful information and discover hidden patterns, trends, and correlations.
Applications of data science
It has now become an inevitable and integral part of industries such as risk management, market analytics, market optimization, fraud detection and public policy among others. Using statics, machine learning and predictive modeling, data science helps industries solve various problems and achieve measurable benefits. There are many reasons to choose a data course as a career option. The following programs help you understand it better:
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This helps companies to understand customer behavior and trends in a very powerful way. This helps to engage customers in a more personalized way and provide better customer services.
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It helps brands leverage data comprehensively to deliver their message to their target audience in a compelling and persuasive way.
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The results and findings of data science can be applied in almost all sectors such as healthcare, education and travel among others, helping them to solve problems in their fields more effectively.
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Big Data is a recently emerging field that helps organizations to strategically solve HR, resource management and IT challenges by leveraging tangible and intangible resources.
A data scientist is one of the key positions in an organization. They open new fields of experience and research to the organization. Some of the direct roles of a data scientist are:
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Linking new information with previous information to offer new products that satisfy the desires of the target audience.
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Interpreting weather conditions and reorienting the supply chain accordingly.
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Increasing the speed of data set evaluation and integration.
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To detect anomalies and frauds in the market.
An idea about Data Science Course
The data science course is 160+ hours of training with experienced faculty working in top organizations to keep you abreast of the latest technologies. An overview of the course is as follows:
- Mathematics and Statistics: It is an integral topic of data science course and includes integration, differentiation, differential equations etc. includes. Statistics include inferential statistics, descriptive statistics, chi-square tests, regression analysis, etc. includes.
- Programming language: Python, C++, Matlab, Hadoop, etc. one can choose from a number of programming languages such as
- Data Dispute and Data Management: This section covers MySQL, NoSQL, Cassandra, etc. engages in data extraction, cleaning and management using
- Machine learning: This includes supervised and unsupervised learning, testing, reinforcement learning, model evaluation and validation.
- Data Analysis and Visualization: This part uses seaborn in python, plotly, ggplot2 in R, matplotlib, etc. teaches how to use plotting libraries for programming languages such as It also involves using Excel, Tableau and D3.js for data visualization.
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