Teachers need refresher courses to update latest trends: Survey

Anantapur: During the boom in the IT industry, engineering colleges mushroomed across the country. But these institutes lacked an updated curriculum and focused on non-existent linkages with industry and had poor student-faculty ratio. Except the IITs, a few NITs and some private engineering colleges, these new institutes failed to make their students job-ready. Indian engineers may figure among the most powerful CEOs in the world, but the country's BTech/BE degree has lost its sheen over the years. According to a survey conducted by Intellectuals Forum(IF), 86 per cent of engineers are unemployable for any job in the knowledge economy. IF Chairman Dr Suresh Babu maintained that majority of private engineering colleges surrendered core engineering branches and got additional sections in AI/ML/DS and IoT. 90 percent of the teachers do not know the fundamental concepts in Artificial Intelligence, Machine Learning, Data Science and IoT. Most of the teachers are not acquainted with the latest trends, technologies and tools. Teachers in Computer Science have to update their knowledge/skills by attending refresher course and orientation programmes are key programs to help continuous professional development of in-service teacher education and maintain quality of teaching profession. No wonder tens of engineering colleges which could not maintain academic standards nor ensure employability of their students, downed their shutters.

Teaching is a one type of profession. It also helps to disseminate the knowledge from young aspirant mind and create better, balanced society for facing new challenge. So, continuous up-gradation is necessary which also help a teacher to disseminate the qualitative knowledge from better way. Data Science is the complex study of the large amounts of data in a company or organisation's repository. This study includes where the data has originated from, the actual study of its content matter and how this data can be useful for the growth of the company in the future. Machine Learning is a field of study that gives computers the capability to learn without being explicitly programmed. Machine Learning is applied using Algorithms to process the data and get trained for delivering future predictions without human intervention.

Companies will always need experimental design, statistical testing, and good insight from data. Whether it is done with statistics or machine learning or whatever comes after machine learning, the need will still be there. The two fields are highly related. You cannot have machine learning without data. But simple data analysis and visualization/reporting is an area which is on the decline. Also, a lot of data driven models use rule-based solutions. These are not scalable. Machine learning on the other hand, although being nascent, has showed a lot of promising results. So, in future, one can say pure data science will not be as glamorous as machine learning.