Introduction to Data Science
As the world advanced and entered the era which is driven by data, the amount of data to be stored and structured also increased. The storage of the data called out for several frameworks and the IT professionals have solved this problem. However, processing the stored data is the second most important thing and this is where Data Science plays its part.
Data Science is the utilization of various quintessential tools, methods, algorithms, techniques, strategies, and the fundamental principles of Machine Learning to extract information from raw data. It uses the data's insights to figure out the patterns buried deep into it and then apply all the tools and algorithms to turn valuable information in the company. A question may arise here that how Data Science can be any different from what Statistics have been providing us?
The answer to this question is that the Data Analytics only process the data and explains the situation as to what is going on. On the other hand, a Data Scientist not only processes the data but it also implements certain algorithms of the Machine Learning to predict whether a particular event will take place in the future or not. For these purposes Data Science utilizes:
- Prescriptive Analytics
- Predictive Casual Analytics
- Pattern Discovery by using Machine Learning
- Predicting the Future by using Machine Learning
Top Skills That Will Get You Hired in Data Science
Every organization requires a special skill set for hiring Data Science experts and for that reason, we have compiled the top 8 skills that will get you hired in Data Science.
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- Skills of Programming
To give structure to the data, you need to have firm robustness on a variety of programming languages to consummately interpret the entire set of raw data. Having the skills of programming is the basic requirement for you to secure a job as a Data Science expert. These programming languages include Python, Java, JavaScript, R, SQL, etc.
- Enhanced Statistical Approach
To become a professional Data Scientist, you must get familiar with the basic knowledge about the statistics and the related distributions, test, and all the other estimators that can help in processing the data. Understanding Statistics can help you in implementing various techniques when one fails to deliver the required results.
- Machine Learning
If you want to work at larger companies such as Google, Netflix, Facebook, etc., then you need to build strong Machine Learning skills. This is because the bigger the organizations, the more complex data they contain. Therefore, to tackle bigger problems, you need to have bigger solutions.
- Linear Algebra & Multivariable Calculus
Linear Algebra and Multivariable Calculus can help you to achieve greater wins for the organization that you are working for. This is because these techniques can help you to optimize the algorithms along with the predictive analysis to draw out prolific outcomes. In an interview, you can be asked several questions about these two techniques, so must excel them.
- Data Wrangling
Apart from being unstructured, the data can also be messy and difficult to interpret with bare eyes. For example, the format of the data can be written as 2020-02-01 instead of 01-02-2020. The transformation of imperfect data to perfectly arranged data is called Data Wrangling and a lot of companies consider it important.
- Data Communication & Visualization
Data Communication and Visualization are the two most important techniques to explain the entire situation of processing and predicting the data. These two techniques are important to build an atmosphere of transparency between the company and the shareholders.
- Software Engineering
If you are a beginner at understanding Data Science and getting a job in a small business then you must know about Software Engineering and all the related techniques about the logging of the data and the products made by exploring a particular set of data.
- Intuition of Data
You must have a lot of knowledge regarding all the above-mentioned areas so that when you get asked in an interview, you must respond intuitively and correctly. They can ask anything about Data Science, from Machine Learning to basic Algebra, thus; you must ace every field efficiently. This is will result in high morale and the company will be drawn to hire you as an employee.
Conclusion
Data Science has been in demand for a long time and it is about time that you start turning your dreams into reality. Acquiring the right and authentic skill set can be overwhelming but with the Data Science Certification, you can master the skills and the required training by just one click. A lot of people are getting benefits from these certifications, so what are you waiting for? Start right away and enter into the world of Data Science to make a promising career.