RV University Offers First Apprenticeship-Based UG Programme In Decision Sciences
Signs Memorandum of Understanding with Mu Sigma – the world’s largest pure-play data analytics company
Bengaluru-based RV University (RVU) and Mu Sigma have signed an MoU to offer a unique four-year B.Sc. (Hons.) programme in Decision Sciences. This is the first Apprenticeship-based UG programme in India along the lines of the Co-Op concept from US and Canadian universities.
This four-year programme offered by the School of Computer Science and Engineering at RVU allows students to learn from the University and train as apprentices at Mu Sigma simultaneously with a 50 per cent duration of the programme as an apprenticeship at Mu Sigma.
The job-oriented curriculum is jointly designed and delivered by RV University’s School of Computer Science and Engineering, and Mu Sigma Which is the world’s largest pure-play data analytics firm providing data science solutions.
During this programme, students will get an opportunity to work on existing problems of Fortune 500 companies. They will spend 50 per cent of their time working on real projects and the other half at the University, developing a strong foundation in fundamentals, skills in the rising technical field of decision sciences, and life skills that are critical for their future.
The demand for data professionals and decision sciences is soaring. Decision scientists are rare professionals who have insight into behavioural science, business acumen and design thinking. Moreover, these qualified professionals can artfully blend business, math, technology and behavioural science and use diverse skill sets to help enterprises make informed decisions. As a result, competent professionals are highly sought after by various industries like telecom, BFSI, IT and more. These trained professionals help sift through voluminous data to provide valuable insights to increase sales and detect frauds about anti-money laundering, pattern recognition, and risk mitigation in various domains using AI and Machine Learning.
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