Whenever we hear words like Data Science , Artificial Intelligence or Machine Learning. We find these words very fascinating and the first thought that come in our mind after hearing these words are robots, automatic machines, different assistants (google assistant), self driving cars etc... and then we think Woow !!! It's incredible that human can make a driverless car.
Note: You people might be thinking that recently Indian Government Launches a driverless metro train that must be based on Artificial Intelligence technology. But it is not AI driven.
If you carefully observe these examples you can find that, in these examples we are trying to teach a machine to behave like human being.
So how can a machine learn like a human being? The answer is data. In a way human, being is also a machine which is very well connected, we can observe things around us using 5 sense (sight, smell, hear, touch and test) and then we store these observed data (the things that we observed around us) in our brain and use it whenever we need it (our memory).
Like human, we try to feed data to machine and try to make it smart like human with more and relevant data considered smart. But the question is; What is Data ? Meaning of data for a human being is different from a machine. A machine understand the data in numerical form or in numbers and for a human being data is the objects around him.
What is Data Science ?
To understand data science let's first understand the words individually.
Data: Every time when we open a mobile phone and click on an application (apps) we create data. Data is everywhere; your computer to calculator (process raw data to give you information as output) everything is based on data.
But now just think if we have not used this data then what is it for us. Answer is; Nothing, it is just a garbage that we are creating everyday.
Science: Science means Knowledge
So, basically in simple terms data science refers knowledge of data.
For example when we use google map we basically create data by providing our location, destination, time taken to by us to cover distance using various transportation and also pictures of locations. But if google map do not use these information to improve itself then these information is just a garbage. This is how, data generated by us used by different organizations and companies to make a perfect business strategy to target audience to make profit.
Data Science: Data science is basically a process of using data by extracting, cleaning and manipulating data to make a decision or to predict a outcome using cleaned data.
Data Analysis: Data Analysis is a process of collecting, inspecting and cleaning data and performing statistics and mathematics to discover data can be used to making decision and solving a problem.
Machine Learning: In simple terms machine learning is a sub field of artificial intelligence in which we study algorithms to make prediction based on training data that improve automatically through experiences.
Deep Learning: Deep learning is a function of AI (Artificial Intelligence) and sub field of machine learning which usage artificial neural network to mimic human brain.
Artificial Intelligence: Artificial Intelligence a technique which enables a machine to behave like human. Basically making a machine enables to do a work which is done by human.
Note: Note that all fields (AI, ML and DL) are based on data meaning that they are part of data science. Or we can say that all these fields and data science are interconnected.
Now let's talk about future of data science basically what make data science to study in 21th century?
Future of Data Science:
Before talking about future of data science; take a look to the Future of Data Science Research paper published by Thomas H. Davenport and D J Patil.
The future of data science is all depends on data. Nowadays large amount of data excavated and still in process. Companies are using this data to make better decision and business strategy and therefore hiring skilled data scientist all around the world to make decision on cleaned data and to clean data raw data.
Note: A person who employed to analyse and interpret complex digital data, such as the usage statistics of a website, especially in order to assist a business in its decision-making.
Salary of a Data Scientist:
Salary of a Data scientist is vary depends on various factors such as work, experience, skills and region. If salary is a function then ; salary (Experience, work, region, skills).
Salary of a data scientist in the US:
The median base salary for a data scientist in the US vary $95,000 -165,000$.
Salary of a data scientist in India:
The starting salary for less than one year experienced is vary around 7 LPA (Lakhs Per Annum). Some startups also offers 4.5 to 5 LPA to freshers. The salary for mid level experienced vary around 10-14 LPA and more based on experiences, skills etc...
Qualification to become a data scientist:
To become a data scientist you don't required any degree but you have higher chances if you have degree in data related field, in computer science , statistics and mathematics.
If you don't have any degree then earn a certificate, diploma in data science. There are various platform provide certification in data science.
Process of Data Science:
- Business Objective: For example finding target audience.
- Data Collection: APIs, Web servers , Database etc...
- Data Preparation: Cleaning and transforming data.
- Exploratory Data Analysis: Refining data. (Python, R etc...)
- Data modeling: Predictive models based on data (Machine Learning)
- Visualization: To represent all statistical or mathematical work in graphs and charts to understand better. (Tableau, Power BI etc...)
- Monitoring and deploying: Testing models and monitoring their performance in real time. basically managing a project.
Roles assigned to a data scientist:
As we already discussed earlier data science is a process of making data useful which has various steps based on steps a data scientist can be;
Data Analyst , Machine Learning Engineer, Data Scientist etc...