Last updated on May 17th, 2022 at 09:13 am
Data Science is one of the most sought after career tracks at the moment. There is a reason that the hype on data science exists. The fundamental focus of data science is that it assists human being on taking better decisions, quicker decisions. And it’s not that this is a requirement of only a handful of industries from a particular segment. This is true across industries, even where decisions are automated for e.g. in online shopping, retail etc.,
There is a rapid growth in the data science field. Its prominence is directly proportionate to the record level of increase in the raw material i.e. structured and unstructured data.
There are a number of other factors that are adding significance to this field. The number of sensors that accumulate information like internet, phones etc.., along with advanced and sophisticated machine learning techniques that help give better insights with the help of better extraction algorithms.
All these forces are working in one direction, the direction to ensure that the skills of using available data to extract actionable insights for business to impact better decision making which in turn will impact the revenue of the company is here to stay. Recognising this most MBA’s have also introduced Data Science into their MBA curriculum.
What skills does one learn in order to become an effective Data Scientist?
Large bits of unstructured data are not easy to interpret, one needs a unique skill set, one needs to develop useful auxiliary skills, some technical attributes required to apply is the top line. One needs to create a perfect balance of various skills. Predictive modelling, analytics, organisation skills and above all communication skills.
Besides the above to be able to secure a lucrative job in the organisation of your choice one needs to develop excellent and valuable coding skills. Efficiency in SAS Statistical Analysis System, R programming language, Python programming language etc.., further aids your skills as a data scientist or analyst. It helps you to think logically in terms of algorithms, which in turn allows you to better manage irrelevant data.
Another additional set of skills that are essential to have academically and through experience are contextual understanding of possibly any given situation, skills in probability and statistics. And finally the most important of all the skills is the ability to communicate, explain, in the method and language of the audience, your findings. So storytelling and presentation skills become imperative.
Why Data Science Prodegree at Imarticus Learning?
To begin with the Data Science Prodegree at Imarticus is designed in association with Genpact as the knowledge partner. It essentially covers all foundational concepts and offers hands-on learning of leading analytical tools such as SAS, R, Python, Tableau etc., and the learning is integrated with relevant industry case studies and projects, which is essential in gaining in-depth problem-solving capabilities.
The course is divided into four semesters and is focused on ensuring that the candidate not only gain the theoretical knowledge of the tools but also learns best industry practices and business perspectives through live interaction with the gurus of the corporate world through guest lectures and regular project submission.
To ensure maximum learning efficacy the course ranges over 200 hours and is delivered in two modes, online and classroom. The course offers career readiness assistance too, at Imarticus the Career Assistance Services provides you customized industry specific mentorship, with assistance in resume building workshops and one on one mock interviews.
The Data Science Prodegree is a power packed course endorsed by Genpact, which has a comprehensive coverage aided by project based learning, with effective and efficient program delivery along with career assistance. Thus preparing you to confidently apply your newly learned skills and excel in your given role right from day one, making you a sought after data driven decision maker.
