Data scientists demand is increasing, and they have potential jobs in the markets, it is very beneficial to have a competitive advantage over your colleagues and these skills will help you to strengthen your selling point. These skills can be learn from online platforms and courses.
R Programming Language
R is a free software environment for statistical computing and graphics. It is a programming language commonly used in statistical computing, data analytics and scientific research. It includes machine learning algorithm, linear regression, time series analysis, statistical inference, clustering, linear and nonlinear modeling methods. Along with python R has an increase demand as it simplifies scrutiny of the data. The business side and academic side both uses R as programming language many companies like youtube, Uber, Google, Amazon and Facebook uses R.
R is a tool that simplifies the job of data scientist, he is not a programmer but a data scientist with a background of statistics so this tool will absolutely do a job and will help to simplify the analysis on huge amount of data.
Python
Python is commonly used general purpose programming language, it is the fastest growing programming language and is very versatile. It is also good to add in your checklist because it’s not only used for data science, but software and web development has also its uses. Python is very easy to understand and read, therefore reduces the cost as teams can work collaboratively and there are no communication barriers.
Python is used in data sciences because it is helpful in the quantitative and analytical overview of data. The data input is very easier and large data libraries help the scientist to manipulate data and makes it very easy for him to operate even if he is a beginner. The plus point of the language is that it can also integrate with any existing infrastructure which can help the operator to solve complex problems. For those wishing to learn more about it, there are many machine learning youtube channels that teach you about a lot of different things, like Python programming, web development, machine learning, and more. If we summarize the benefits of Python in data science, it comes down to these 5 elements.
- Scalability
- Visualization
- Easy to use
- Versatile
- Choice of libraries
Hadoop
Hadoop platform is the must skill that data scientist should possess, it is a data processing software framework which stores and process large amount of data on different locations at the same time. Not only this Hadoop platform is also used for data filtering, sampling and analyzing. It helps to analyze large cluster of data and predicts the future outcomes according to trends, mastering this tool will give you edge and strong selling point in the market.
Machine learning and Artificial Intelligence
Machine learning and Artificial intelligence are most important tools, they not only involve complex algorithms that have data input and the results predicts the outcomes, it also has a factor of adaptive learning. Teaching themselves and gets better with time so they could predict future outcomes themselves more accurately. It is the most promising tool as data input will be huge so adopting this technology simplifies your job.
SQL
SQL is also preliminary tool that also be mastered, it is a simple domain-specific programming language that performs add, delete and extract functions from large databases. It helps you to carry out analytical functions and helps to transform data structures.
