CHRIST (Deemed to be University) was born out of the educational vision of St Kuriakose Elias Chavara, an educationalist and social reformer of the nineteenth century in South India. He founded the first Catholic indigenous congregation, Carmelites of Mary Immaculate (CMI), in 1831 which administers CHRIST (Deemed to be University).

Established in 1969 as Christ College, it undertook path-breaking initiatives in Indian higher education with the introduction of innovative and modern curricula, insistence on academic discipline, imparting of Holistic Education and adoption of global higher education practices with the support of creative and dedicated staff. The University Grants Commission (UGC) of India conferred Autonomy to Christ College in 2004 and identified it as an Institution with Potential for Excellence in 2006. In 2008 under Section 3 of the UGC Act, 1956, the Ministry of Human Resource Development of the Government of India, declared the institution a Deemed to be University, in the name and style of Christ University. One of the first institutions in India to be accredited in 1998 by the NAAC, and subsequently in 2004 and 2016, CHRIST (Deemed to be University) has the top grade A in the 4-point scale.

The multi-disciplinary University which focuses on teaching research and service offers Bachelors to Doctoral programmes in humanities, social sciences, science, commerce, management, engineering, education, and law to over 21000 students. The campus is a living example for the harmonious multiculturalism with students from all the states of India and around 60 different countries. CHRIST (Deemed to be University) publishes six peer-reviewed research journals and has published more than 300 books in Kannada and English. A promoter of sports, music and literary activities, it is a nurturing ground for creative excellence.

Department Overview

Department of Data Science of Christ (Deemed to be University), Lavasa is started to shape outstanding Data Scientist and Analytics professionals with ethical and human values. The department offers degrees Bachelors of Science, Master of Science in Data Science and Doctor of Philosophy in the areas of Computer Science and Engineering. The department has rich expertise in the term of faculty resource who are well trained in various fields like Data Science, Data Security, Data Analytics, Artificial Intelligence, Machine learning, Computer Vision, Algorithms Design, Computer Networking, Data mining, BIG DATA, text mining, knowledge representation, soft computing, Cloud computing, etc.. The department has wide variety of labs setup namely Machine learning lab, Data Analytics Lab, Open Source lab, etc... Dedicated for the hands-on training of the students for their lab curriculum and research.
The department intermittently organize hands-on workshop on recent technology like Machine learning, Cloud Computing, Hadoop etc. for the students to keep them industry ready. The department equip students with holistic education to be better citizens.

Vission

Enrich Ethical Scientific Excellence

Mission

• To develop Data Science professionals with ethical and social values.
• Divulge state-of-art knowledge in the area of Data Science and Analytics.
• Encourages the research and innovation.
• Accustoms the students with current industry practices, team work and entrepreneurship



Introduction to Programmes

When it comes to choosing a graduation course after Class XII, Bachelor of Science (BSc) is one of the most common options selected by students. BSc is an undergraduate course offered at almost all universities in India. Students with an academic qualification of Class XII can pursue BSc course in different branches.

Data science is an interdisciplinary response to this demand, and in our BSc degree program-me students follow a carefully selected curriculum from Computer Science, Mathematics and Statistics.

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There are three general steps to becoming a data scientist: Earn a bachelor's degree in IT, computer science, math, physics, or another related field; Earn a master's degree in data or related field; Gain experience in the field you intend to work in (ex: healthcare, physics, business).

The best path to becoming a data scientist depends on an individual's background.

Many people currently working in data science come from backgrounds in math, statistics, or computer science.

BSc Data Science

Bachelor of Science (BSc) offers theoretical as well as practical knowledge about different subject areas. These subject areas usually include any one of the main Science fields (Physics, Chemistry, and Biology) and other fields depending on the specialization a student opts.

BSc Data Science is a unique Program designed to impart the essential skills to cater to the fastest growing trends in the industry. The curriculum is a blend of core and advanced specialized courses in Statistics and predictive analytics using R, Python, Machine Learning, Data Visualization with a strong foundation of Mathematics, Communication skills and entrepreneurship. Choice based electives from other Programs diversify the domain of knowledge in an interdisciplinary manner.

MSc Data Science

The MSc Data Science will provide students with the technical and practical skills to analyse the big data that is the key to success in future business, digital media and science. The MSc Data Science provides training in data science methods, emphasising statistical perspectives. After the program students will receive a thorough grounding in theory, as well as the technical and practical skills of data science.

Student's theoretical learning will be at a high mathematical level, while the technical and practical skills students will gain will enable them to apply advanced methods of data science and statistics to investigate real world questions.

The compulsory courses on the MSc Data Science programme will provide students with comprehensive coverage of some fundamental aspects of data, computational techniques and statistical analysis. They will then choose courses from a range of options ranging from Deep Learning for Natural Language Processing for Big Data and Statistical Computing, to Financial Statistics and Probabilistic Methods in Risk Management and Insurance. The programme will combine traditional lectures with computer lab sessions, in which students will work with data to complete hands-on exercises using programming tools.

IDSCS'20 is a technical gathering of the Internet and Data security professionals to exchange the latest developments that are gaining momentum in the ever-growing global infrastructure of Computer Science. The conference is a single-track program with a pre-conference tutorial scheduled on day 1. Day 2 will feature invited talks and selected paper presentations. IDSCS 20 aims to serve as a technical forum to share and learn about the various works that may lead to the Next generation of Internet Security Infrastructure. We invite original research submissions and findings based on large scale practical implementation on the following topics, but not limited to:

Keynote

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Neural Networks for Human Intention Prediction Dr Dong Seog Han Director, Center for ICT & Automotive Convergence Kyungpook National University

Abstract
In this talk, we consider the deep learning technology to predict a user’s intentions from a series of activities undertaken by the user within a known environment using data from wearable devices with sensors. This has three components; human activity recognition (HAR), indoor localization, and a time component. Human activity recognition aims to recognize the actions and goals of one or more users from a series of observations on the users' actions and the environmental conditions. Indoor localization aims at providing a precise and accurate position of the user in an indoor environment when performing a specific action. The time component is very crucial in that a user performs certain activities during a specific period. For example, a user “cooks dinner” – action; at “home in the kitchen” – location; at “5:00 pm for 30 minutes” – time. To achieve this, each of the above components has to be achieved individually before combining them for a system to continuously learn and understand a user’s behaviour and then have the ability to predict when certain activities need to be performed and reminding the user when “important” activities or events have been missed, including appointments, meals, etc. The applications for this research include ambient assisted living (AAL), can also be applied in smart homes, security systems, fraud detection, virtual reality, digital companions, and so many other areas that rely on continuously knowing what a user is up to in a manner that protects their privacy and pervasive since the devices we use are widespread and can easily be worn or carried without burdening the user. Modern deep learning techniques will be discussed to accurately recognize human activities. The indoor localization issues will also be handled considering the environment using deep learning. Finally, we consider ways to continuously learn the user’s actions, and their environments in a specific period.

To ensure publication of a paper in the Proceedings, at least one author has to register by submitting a normal registration fee within deadline. The authors are requested to make the registration of their accepted paper using the following steps and guidelines. Please pay the registration fee by 15 February’20 to avoid the late-fee penalty. The registration charges for early bird and late registration are also stated below.

10% concession on submission of 5 or more paper from the same Institution

Payment of registration Fee (Online Payment using the Payment Portal ):Click here for Registartion

Accommodation in CHRIST Residence hall can be availed on first come first serve basis by paying 700.00 Rs for Shared accommodation 1400.00 Rs for Single