Objective: To produce world class data scientists, at least 500 in the next 10 years.
Intake: As the Programme shall be offered in blended MOOC model, there shall not be any limit on the intake; To begin with we plan to offer admissions to top 1000 scorers in the admission entrance test (We shall close the on-line application link if receive 5000 applications before the deadline). Based on the response and demand from the applicants, the online registration will be made available after this count.
Duration: 2 years, i.e., 4 semesters, specialized Programme including a rigorous training, a capstone project and one semester internships with Wadhwani Institute Of Artificial Intelligence (WIAI) or any such industry.
Eligibility: Anybody having passed XII or higher standard examination with minimum 50% score can appear for the national level entrance examination and take admission if gets through. The admissions to Master's degree (MSc in Computer Science, specialization data science) shall be open to the graduates of this University or its equivalents. The candidates who qualify the entrance test and not having completed their graduation could take admission to micro degrees (Certificates) and allowed to accumulate credits by qualifying discrete Courses of this Programme by following the pre-requisite structure. The credits earned by such candidates shall be recognized and transferred by this University and be utilized by the candidates wherever applicable. The candidates who qualify the entrance test and have taken admission in any of the Programmes of this University that includes a Master's Programme, can accumulate up to half of the credits of this Programme while completing the other Programme and secure Master's in Computer Science with specialization in Data Science by earning the remaining credits in one year any time after his / her graduation. The admission procedure to this Programme shall be opened twice a year, i.e., in the months July and December. Since the Programme will be offered in the blended MOOC model the students taking admission to this Programme would be eligible to take admission simultaneously in some other Programme of This or any other University subject to the Dual degree facilities of the respective Institutions.
Mode of dissemination of knowledge: A blended MOOC model tested by IITB for its performance has been proposed; Each Course shall be equivalent of 6 credits, the teaching-learning spread over 16 weeks, ideally each week a student is expected to study 6 videos, each of 15-20 minutes, each ending with an activity that calls for the similar amount of time, attend 2 hours of tutoring and 2 hours of practical offered in a flipped classroom and, contribute to forum discussions on 2 threads by spending half an hour on each thread. (This counts to 8 hours per week teaching learning per Course; engaging 32 hours a week a student in a Semester that is at par with our F2F Programmes) WIAI shall help generating MOOCs and sponsor honorarium of 2 SRF (Assistant Professor cadre) and a Programme Coordinator (Professor cadre) in UDCS and employ a Programme manager at their end for the initial three years. The personnel will be responsible for the class and lab tutoring with the help of the MOOCs that would be finalized by UoM in consultation with WIAI. The theory and practice sessions of the Programme would be conducted through and in UDCS. WIAI shall get a MOOC studio built in the Department, till that, the facilities available at IITB shall be shared under an academic agreement that is in process.
For each Course a student has to secure minimum 16% of the total marks through a Semester-end examination that would carry 40% weight in the total evaluation; the 60% weight would be for the student's attendance and submissions in response to the video-based learning and flipped classroom activities, call it continuous internal evaluation (CIE). In order to qualify a Course a student has to earn minimum 40% of the total marks in the same; There shall not be minimum passing requirement for the students score in CIE. However,
a failed student can choose to improve CIE score once by paying only examination fees and by submitting all the assignments and term-work as prescribed by the on-going term. The students failed in the second attempt have to pay 30% of the tuition fees in addition to the examination fees, i.e., to avail the new Course-ware whenever they will wish to appear for the CIE.
Subject to the availability of the Programme / Course in the University, there shall be no limit on the number of attempts a student takes to qualify the same. A syllabus will be valid only for a year and shall be kept up-to-date by generating a refinement a year. The repeaters have to follow the syllabus and assignments that are available at the time they wish to appear for the examination. (This constraint is must for keeping the standards of the Programme and guaranteeing the employability of the students in the world of the fast-changing industrial requirement and the sophistication in data science).
The Semester examinations shall be conducted in the months December and May.
WIAI shall share academic and technical expertise to guide the evaluation process. CMO has volunteered to provide support to conduct the examinations at distributed centers and in generating results in time. It has been decided that the student's competence in descriptive type writing shall be tested through their responses to the assignments given for CIE; The Semester-end examination shall be to evaluate their comprehension about the Course content and problem solving, these should be tested through the objective responses expected for the questions in the paper.
University department of Computer Science (UDCS), University of Mumbai(UoM), shall be responsible for execution the Programme and evaluation of the students admitted to it. UDCS shall interface with the Examination Section of UoM for further proceedings towards the award of degrees to the qualifying candidates. UDCS will see to that the Structure and Evaluation model of the Programme shall be compatible with the UGC guidelines that have been adopted by UoM from-time-to-time.
Fees: Fees for the Entrance Examination shall be Rs 500/- per student per attempt; If admitted to the Courses from the first three semesters then a student has to pay Tuition fee Rs 4000 / - and Examination fee Rs 1000 / - per Course plus, Convocation and other fees like Gymkhana, insurance etc., as prescribed by UoM. Fees for the Fourth semester will be 10K that includes the Departmental support in mentoring and processing fees that may require to publish student's work and file patents etc. (Tentatively the fees per semester would come up to 25K per semester that is at par with the present fees of CS and IT Programmes. The per Course fee structure has been recommended because the nature of the Programme is that there would be people interested in attending a few Courses of the whole Programme in order to seek micro-degrees that would uplift their career profiles. We need not evolve a separate fee structure for them.
A novel incentive is recommended: A candidate scoring 50% or more shall be awarded up to 50% discount in the fees in his / her further studies towards the completion of This Programme. The proposed discount pattern based upon a student's score is given in the Table below.
|% score||Discount: % of fee paid|
|50 - 59||10|
|60 - 74||20|
|75 - 84||30|
|85 - 94||40|
|94 and above||50|
Highlights of the Syllabus: Tentatively 75% content is focused to the core data science and 25% is from the interdisciplinary fields of its applications. Theory and practice have been given equal weights. The scope of the Research Methodology Course involves mentoring students for a research and an industrial project start from problem formulation phase to publishing the research and securing its IPR. A student alone or in a group is expected to publish his / her work carried out during this Programme, in a good impact factor journal or file a patent or make its outcome available under Open Source licenses etc. The syllabus emphasizes the project based learning. Besides the senior academics, the Syllabus committee has members from the Industry and experienced people from the professional bodies like ACM and IEEE. Along with the UGC guidelines, the content and its distribution possibilities recommended by the ACM, IEEE and alike are considered while designing the curriculum. National and international level content dissemination and evaluation models that are successful in offering a similar Programme have been studied while designing the proposed scheme.