Table of Contents
What is Data Science?
Data Science: In a world that is rapidly becoming a digital space where a huge volume of data is collected every day, it becomes highly necessary for every organization to collect the data and analyze it and visualize it and understand the inside of it to extract the patterns from it. So that the companies could make an idea about market trends, customer interest, where their business is heading, so all these useful pieces of information and insights can help them boost their Revenues. By using this data, they can build effective strategies, and they can build automated models using algorithms. So whenever they give new data to that model, it gives a quick analysis of that. In the 21st century, every company relies on data to optimize their business. To convert the raw data into a useful piece of information using various tools and algorithms is Data Science.
What is Raw Data and Processed Data?
Raw data the pieces of information that are not structured. Raw data contains information, but not ready to serve on the plate. These data are the data directly generated by the user’s behavior and transferred to the parent company.
Process data the filter data. Raw data is collected and filtered to make it presentable and easy to understand, called processed data or Ready to serve data.
What is the need to process the Data?
After the raw data is collected, it is cleaned to make processed data because raw data can have duplicate data, replicated data, missing data. The variety of data can be different. Formats can be different. If we try to take out information from raw data, then the data can be inaccurate. So the company can’t make the right strategies. To convert raw data into processed data, we have various tools like R, Python etc.
What is Data Visualization?
Now that data is processed and ready to serve. You need to show it to someone it can be stakeholders or your colleagues or anyone. But you have numbers and it will be very difficult to make it understood. So we use graphs such as pie graph, line graphs, bar graphs, histogram. So, presenting the number of data into a graphical representation is called data visualization. Some data visualization tools are – Tableau, JS, Chartist, Fusion Charts.
Who is a Data Scientist?
Data surround us. Every time we pick our phone, we encounter data and generate data. Let’s take an example – You Clicked a picture. All pictures in the smartphone comprise of 3 layers, RGB. And in all these 3 layer data is hidden.
Whenever you are scrolling through your social media, you are interacting with data. And you are also generating data for the company (your watch time, your clicks, your pattern of interaction) all this data generated by you is supplied to a parent company. Here, a data scientist’s role is to filter the data, simplify it, and present the information to the company so that the company can make marketing strategies and target the right audience.
If you’ve ever noticed, you visited an e-commerce website and searched for any product. You will get the same recommendations for your social media account. That’s how data is used to generate leads.
Data Science career growth and salary insights
The data science job profile has become one of the industry’s top profile; also, they are the highest paid professionals in the IT industry. According to Forbes, America’s best job is of a data scientist with an average annual salary of 1,10,000 Dollars. By this, we can understand the data science plays a major role in the growth of an organization. To know the salary insights of data science professionals in different countries visit: glassdoor.com
Best free online courses for Data Science
After searching over the Internet, I came across many certification courses for data science, after going Through the curriculum and course structure. I found out the best course on data science which is completely free. And the cherry on the top it’s taught by Harvard professionals.
Best Data Science online certification course :
edx Data Science course
This course is divided into 9 certificates. The last is a “Capstone Project” which will definitely help to give a comprehensive hands-on experience to the learner.
1st Certificate – Data Science: R Basics
2nd Certificate – Data Science: Visualization
3rd Certificate – Data Science: Probability
4th Certificate – Data Science: Inference and Modeling
5th Certificate – Data Science: Productivity Tools
6th Certificate – Data Science: Wrangling
7th Certificate – Data Science: Linear Regression
8th Certificate – Data Science: Machine Learning
9th Certificate – Data Science: Capstone
Should you learn Data Science?
If you like to research and work on your own. If your analytical skills are good and have a keen interest on playing with numbers.
Data Science undoubtedly is the hottest job in the market today. But just because there is a projected shortage of data scientists or data professionals in the future, does not mean that you should jump off to become one, as data science is not everyone’s cup of tea. Data Science is not an easy skill to master. Data science jobs are available in several sectors in information science, Computer Science, Health Care and Business. One can choose from different fields based on their interest or even geographical location.
If you are a beginner and are fascinated by the field of data science, you could choose to pursue any of the online courses for beginners and kick off your journey right away. Of course, there are some prerequisites to handle first, like math concepts, statistics and programming.
Computer Science Engineer
If you are a computer science engineer, you can surely shift to data science.
Junior Data Executive/Data Analyst/Business Executive
You might be working in the field already but somehow have not managed to climb up the ladder. If that’s the case, it is time to upgrade your skills so that you can finally get better projects and role to work on.