In the 21st century, Data is the New Oil. Raw oil is useless. It is only after getting refined that it becomes useful. Similarly, data is just like oil waiting to transform into meaningful information. In layman’s terms, data science is the art of analyzing data to generate meaningful information.
The problem which a beginner is facing is that of choice. There are loads of content and options available. Hence for someone who is not seasoned and experienced, it becomes a difficult choice. Taking positive steps in the right direction is what that’s takes to learn data science. There are several methods to learn data science. The key methods are described below.
Start with basics
Practice your hands and mind on MS excel. Get an understanding of tools such as Data filters, Formulas (both scientific and others). Then move to advanced options such as Visual basics, macros, and Pivot table. Try to make sample projects by yourself. These projects can include determining the growth forecast of a company’s revenue. The growth will depend on economic growth and an increase in customer base. It can be as simple as analysing your spending pattern based on your bank statement data.
Be aware of basic statistics such as Mean, median, Normal Distribution, Standard Deviation, and Variance. Correlation and regression tools are important to understand how one data set is related to another. As you advance, pick on advanced mathematics such as calculus and simultaneous equations.
Learn Programming Language: Both paid and free versions are available to learn data science skills. You can check data science courses in India from Great Learning to grow your career in Data Science and related fields. Aim to learn programming languages via online classes. The Programming language used in data science is Python and R . Their commands and texts are similar to English, and they have a rich library. A python is a problem-solving tool in the true sense. Always try to visualize the problem and its probable solution at the same time.
Understand Data visualization: Data visualization and exploration tools such as Numpy and Pandas are in high demand. Data cleaning tools allow you to clean up your messy data so that both you and others can use it with ease. Learning of these visualization tools is a prerequisite in data science. It helps to compile your syntax and coding. Otherwise, it becomes difficult to navigate through the code.
Try Machine learning: Machine learning employs a lot of statistical and mathematical tools. You also need to be aware of basic algebra. The machine learning tool can be used to build a website. The website will take variable parameters from the user and display the appropriate result. You can use both text and image data to analyze via ML. The goal is to build a predictive model.
Adapt trial and error approach while using machine learning tool. If the current syntax doesn’t give the required outcome, try amending it till it is exact.
Final words
The data science domain does not require a specific educational background. Just an analytical mind and the ability to ask the right question is enough. Having a problem-solving approach and a curious mind is a key. Getting a data science online certificate also aids in showcasing your skills
Try to grow organically by showcasing your data science skills on different platforms. And take advice from mentors and peers.
