A blend of statistics, mathematics, business acumen, tools, algorithms, and machine learning techniques constitutes data science! The knowledge of all these concepts helps in finding the hidden patterns in big volumes of data that can fetch actionable insights. You must have heard industry-leaders say “Data is the new oil!” which makes it clear that if it’s unrefined it’s barely of any use. It is here that Data Science actually comes into the picture! A data scientist knows how to put the unrefined data to use.
The market is abuzz with the data science jobs and hence, many schools are bringing out courses on this discipline. But while opting for any of the courses, it is pertinent to know Data Science Course Syllabus that the institute is offering.
Here’s a list of key-areas recommended by our expert educators that you should check in the data science course syllabus to decide on whether or not you should take up the course:
There are three components of Data Science namely Machine Learning, Big Data, and Business Intelligence. Hence, any course that offers full coverage on these three key components is best suited for learning. Let us look at what these are:
Being an industry leader in the education sector, Career Launcher brings to you a comprehensive Post Graduate Program in Data Science & Big Data Analytics covering all the three key components in great detail. The course has been designed in collaboration with faculty from KREA University. Check out the data science course syllabus of this program below.
The foundation module helps in ensuring a firm grounding in the basic tools required to appreciate both the application & delivery aspects of Data Science. Candidates need no prior experience in programming. The topics that are covered in this module include:
The science of using past data to generate useful future scenarios is called predictive analytics. Candidates need to have a clear and concise understanding of predictive modeling to appreciate the application modules that follow. The topics covered in this module include:
Big Data is the colossal volume of data that is unstructured. This module gives an insight into the understanding of big data and also introduces real-world applications in Data Science, through a mixture of theory, real-world problem-solving and guest lectures. The topics covered in this module include:
Prescriptive Analytics focuses on making the participants learn analytics techniques that are useful when no clear past intelligence is available with respect to input-output correlation. The topics covered in this course include:
During this module, the participants will get the opportunity to work on real-world problems across several industries. It will allow the participants to put all the theoretical knowledge that they have gained through the course into practice.
When you’ve decided that you want to make a career in this up-and-coming industry, it is better you choose a course that fits the demand of the industry with its course contents. Get in touch with our expert counselors to get complete guidance on a data science course.