Difference between Data scientists & business analysts

Welcome to the Foundations of Data Science course . Learners from a wide variety of backgrounds study Data Science and while there are no prerequisites, it would be helpful to learners if they had some knowledge about topics like analytics and statistics so that they would be able to pick up concepts faster.  This course is aimed at providing this background knowledge and helping students get started on their data science journey. In this video, we will get started with a basic introduction to analytics, what has changed in the data and analytics ecosystem as well as highlighting a few cases which show the application of and the power of analytics. Great Learning has collaborated with the University of Texas at Austin for the PG Program in Artificial Intelligence and Machine Learning and with UT Austin McCombs School of Business for the PG Program in Analytics and Business Intelligence.   

We may not know what our future holds, but we educators must prepare our students to flourish in it. The world we live in will not be the same in the future, many new occupations will come up and many existing ones won’t exist. Since we can’t accurately predict the type of jobs that would guarantee greater success, we can perhaps prepare our students the best for the challenges of the future.  Educators need to empower learners and mold them according to market needs. They shouldn’t just prepare learners on specific skills, rather, the focus should be on their all-round development. Developing adaptability to change and creativity will enable learners to deal with challenges. It will also remove a learner’s limitation of being good in one specific field. We can use innovative and flexible methods like  Design thinking  to overcome this challenge. Design thinking is a human-centric approach to solving real-world problems providing educators with the necessary steps toward...

Data Science  is a comparatively new concept in the tech world, and it could be overwhelming for professionals to seek career and interview advice while applying for jobs in this domain. Also, there is a need to  acquire a vast range of skills  before setting out to prepare for  data science  interview. Interviewers seek practical knowledge on the  data science  basics and its industry-applications along with a good knowledge of tools and processes.  Here we will provide you with a list of important  data science  interview questions for freshers as well as experienced candidates that one could face during job interviews. If you are aspiring to  be a  data  scientist  then you can start from here.

This Roadmap To Artificial Intelligence Video by Great Learning will introduce you to what Artificial Intelligence is, and discuss pointers like Salary, Career Path and Skills an Artificial Intelligence Engineer can and must have, Visit Great Learning Academy, to get access to 80+ free courses with 1000+ hours of content on Data Science , Data Analytics, Artificial Intelligence, Big Data, Cloud, Management, Cybersecurity and many more. These are supplemented with free projects, assignments, datasets, quizzes.  You can earn a certificate of completion at the end of the course for free. https://glacad.me/3duVMLE   Get the free Great Learning App for a seamless experience, enrol for free courses and watch them offline by downloading them. https://glacad.me/3cSKlNl     #roadmaptoai #great learning #artificial intelligence #data science #free online courses #free certificate courses

Business analysts are professionals who look into the ever changing needs of any business and assist them in implementing those changes. They form a bridge of communication between various departments in a business organisation to execute any business plan. Data scientists are responsible for developing algorithms and drawing data inferences. Since data science aims at unveiling complex data patterns by studying and understanding data sets, it is important that data scientists are well versed in multidisciplinary skill sets. Both these roles are in fact, similar in a lot of ways since both involve data gathering, inference accumulation, and data modelling. The scope of data science and business analytics often overlap and the skill sets are not mutually exclusive. In any business environment, data scientists and business analysts work closely to understand and implement strategies. However, there are certain differences between these two branches that aspiring professionals must consid...