Career in DATA SCIENCE

 

Have you ever thought of how Artificial intelligence and machine learning will change the world and the internet of things will make our lives easier, yeah the one thing that underpins all these technologies is "data". And all these data is implemented by Data Science.

So,what exactly does Data Science mean?

Data Science uses scientific methods, techniques, algorithms, and systems to extract knowledge and useful insights from many structural and unstructured data.
From social media to IOT devices in generating large amount of data, For example you have searched for a watch on amazon and you didn't bought them and the next day you are watching some youtube video or any other application that contains ads and you see the sandals in that recommendations. Have you ever surprised of seeing how the product you have viewed is in recommendations. Well, this happens because google tracks your search history and recommends ads based on this. This is one of the coolest application of data science.There are even lot of applications of data science.

Big data and Data Science: So here are the two terms which often leads to confusion. Big data refers to large volume of data which cannot be handled using traditional database programming whereas, Data Science approaches the process to Big data which uses scientific methods to draw meaningful insights.

Path to Data Science: In this Data Science career path,By following these steps you can achieve your dream job.

• Firstly, find out what data science means and the skills required.

• Attend workshops so that you can know better about everything. Talk to the data science experts.

• For learning anything you need to start with fundamentals, Learn basics of maths, python.

• Concentrate more on ML tools.

• Create your github profile or other profiles, attend more competitions, participate in discussions.

• Apply for internships, engage in online communities, keep practicing and stay dedicated.

By taking this career path seriously one can be in a greater position in this field.

Skills needed: Each of the job roles require specific skills which are explained in the further posts. In order to excel in the field of Data Science one must have high knowledge on

• Programming skills

• Statistics

• Machine learning

• Data wrangling

• 5Data visualization and communication.

 Apart from these, also non technical skills like higher communication skills and also presentation skills are required.

Programming languages required :

• R-R is the adopted language for pure Data Science.

• Python-Python comes with lots of libraries for analysing data.

• Java-As compared to java, python is preferred by most of the Data Scientists as due to its libraries and ease of its implementation.

Data Science tools:

Tools helps us to learn, create, practice and also publish our views. With the help of these tools we can excel better in a particular field. So, here are some of the Data Science tools.

• Tableau

• Bokeh

• D3 js

• jupyter

• OpenRefine

So, here comes the question!

"Where can i learn these courses?"

Wide range of Data Science courses are offered online in which few of them are free of cost and many are paid.

• Udacity: Machine learning

• CIT: learning from data

• eDx course

• Coursera: offers a wide range of Data Science courses for free of cost.

Apart from these online courses there are lots of Data Science blogs and communities like kaggle-largest community with data science tools and resources which help in guiding to achieve data science goals.

 Jobs roles in Data Science:

• Data Analyst: Data Analyst collects data, processes, performs statistical analysis on large amounts of data.

• Data Engineer: Data Engineers are the professionals who prepare Big data to analyze by the data scientist.

• Data Scientist: Data scientists are the analytical experts who use their technical skills in order to uncover the unsolvable and business problems.

• Business Analyst: Business analyst analyses business domain and helps in improving processes, products through data analysis.

• Machine learning engineer: Their focus goes beyond specially programming machines to perform specific task.ML engineering creates programs that will enable machines to work without being directed.

• Machine Learning Scientist: Research new data algorithms and approaches to be used in adaptive systems including supervised, unsupervised, and deep learning techniques. Machine learning scientists often go by titles like Research Engineer or Research Scientist

• Applications Architect: Track the behavior of applications used within a project or a business and how they interact with each other and with users.

Factors that contribute to the future of data science:

• Inabality of organizations to manage data.

• Austounding phase in data development.

• Updating block chain with data science.

How much do data science professionals earn ? 

This can vary depending on your experience, projects you work and the company/country that you work in. As per the data available in various employment websites, even data science freshers can earn above Rs 5 lakh per annum. Experienced data science professionals can expect to earn more than Rs 20 Lakhs per annum in India.