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When it comes to the question of filling key gaps in employability and helping freshers get ready for new age job roles, it is the opinion of experts that Academia must take the initiative by partnering with the corporate world via experienced technology evangelists who offer services of campus to corporate transformation of students. Here is a list of things that will help students get ready for job roles that are available in the market today: Revamping of curriculum in order to make it more relevant to the current industry needs Collaboration with the industry through Tech Evangelists with events, labs, internships, contests, assessments, skill training and mentor based projects. Based on experiences in various organizations, experts believe training in building all these three areas by industry experts will certainly help both freshers looking for jobs and corporate companies looking for the right workforce. The ability to focus and understand one’s strengths without being too concerned about the rat race Understanding the importance of soft skills, enhancing the focus on problem solving skills, client orientation, communication etc.

The young adults of today require a different set of support services rather than the typical traditional students, but these services that are required includes skill development, care, long-term credit counseling, placement support and interview-ready training that are often unavailable as a wholesome course. A recent research titled as ‘The Voice of the Employer on the Effects and Opportunities of Professional Development’ pointed out that universities and colleges must now work towards giving students the very skills that are required for jobs and long term success in an industry rather than focusing only on certain support services. How does such training benefit colleges A University or a college that responds to industry needs appropriately will not only attract, success driven students to apply but will also attract corporate companies who are looking for professionally trained freshers to join their workforce. Corporate companies get trained workforce that have hands-on experience in the technologies that they work with, hire them right off the campus, fresh out of the training, and such a work-force displays productivity from Day 1 at job that saves these companies huge resources.

Corporate companies can function via training evangelists to make new advances and technologies available to tertiary education creating workforce that is up to date. Here is the way forward- 3 powerful ways in which industry oriented training can be looped in with formal academics: An efficient Learning Management System: The connection between corporate learning and colleges can be done with a well designed and relevant Learning Management System. Companies can provide access to white papers, crucial project papers in order to train students, and assess them via the institute’s Learning Management System in order to evaluate prospective employees. IIHT’s Academia Learning Solutions forms a strong bridge between the corporate and the academia creating a holistic environment for industry readiness.

Here are a few things that you can begin with in order to work towards a career in Machine Learning: Machine Language is growing at a real fast pace with smart algorithms being used right from mobile applications and email to marking campaigns. Here are a few things that you can begin with in order to work towards a career in Machine Learning: Understanding what really Machine Learning is: This may sound like a really obvious point but just knowing what machine learning is on the surface and really learning it well, hands-on with in-depth understanding of basic analytics behind can be very different. Machine Learning has been evolving at a rapid pace in the last few years with new languages, new techniques, new frameworks, new technology and new things to learn that makes it important for people to eagerly learn what’s new. Learn Python and the use of Machine Learning libraries: Python is the most recommended programming language for machine learning by industry experts.