Steps of Data Science Training and its uses


The branch of science which deals with the study of data is known as data science. Well, if you dig a little deeper, it does not only mean the study of data, but also its manipulation and processing.


Data science typically involves-

  1. Identifying and determining the correct data.
  2. Collecting large amount of both structured as well as unstructured data.
  3. Cleaning, validating, devising and applying algorithms.
  4. Analyzing and interpreting the data.
  5. Finalizing the data.


Use of Data Science

Now, a question should be arising in your mind that what is the use of data science. Well, the answer lies in the fact that not all data is structured. Today, data is mostly either unstructured or semi structured, and for dealing with this type of data, we need data science, but this is not the only reason for having data science, if you dig deeper, you'll find many more reasons for the existence of data science.


Data Science Training

Data science training is nothing else but the process of becoming a data scientist. It requires both tools and machine learning. Data science training involves a lot of time in gathering data, cleaning data and munging data as data is never clean.

All this requires persistence, statistics and skills. Altogether, becoming a data scientist is not at all an easy job. A data scientist applies machine algorithms to text, numbers, images, audio, video and many more to manufacture artificial intelligence (AI) systems. In other words, a data scientist has to analyze data and provide enough meaningful data for organizations to make a well-informed decision.


More generally, a person having the knowledge of how to extract meaning from interpreted data is termed a data scientist.

Data Science VS Business Intelligence

Many of you may confuse data science with business intelligence which shouldn't happen as the two are very different concepts. Business intelligence analyses previous data and finds insight to explain the ongoing business trends whereas data science is a more advanced approach. It can explain what and how events occur by analyzing the past or current data.


All You Need to Become A Data Scientist

After reading the above article and digging deeper in the field of data science, many of you will be interested in becoming a data scientist, and you'll eagerly want to know the qualifications and skills required for becoming a data scientist. The first and foremost thing required is education as data scientists are highly educated intellectuals and secondly, you require programming skills. R programming is generally preferred for learning by a data scientist as it is specially designed for the same. Some technical and non-technical skills required are - python coding, SQL database/coding, apache spark, machine learning and AI, data visualization, intellectual curiosity, business acumen, communication skills and teamwork.


The Conclusion

Now that we know what data science means and how it functions, we can conclude that maybe it is a complex thing to understand but once implemented will surely benefit the organization. It is beneficial in the long run.


To become a data scientist, you would need data science training. ExcelR offers a variety of courses and training to clear your concepts

E-mail me when people leave their comments –

You need to be a member of The Brooklynne Networks to add comments!