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    Quick Facts

    Total Fees
    5.16 L
    Seats
    60

    Fees Details

    General

    5.16 L

    Disclaimer: Data for total fees has been calculated based on all years/semesters as provided by the college. The actual fees may vary.

    Course Details

    Mode Full time | Duration 2 Years

    Data science is a “concept to unify statistics, data analysis, machine learning and their related methods” in order to “understand and analyze actual phenomena” with data. In other words, the detailed study of the flow of information from structured and unstructured data available with an organization is called data science. It primarily involves obtaining the meaningful insights from the data which is processed through analytical study. The current era is becoming a digital space where each organization deals with large amount of structured and unstructured data on a daily basis. Evolving technologies are leading to cost saving solutions for storage and analysis of such large data. In the current era, for the career progression, one needs to understand the language of data through analytical skill. Hence, it is absolutely necessary nowadays, to develop manpower with a skill to perform data analysis to get meaningful information from the data of different domains such as banking and finance, insurance, agriculture, healthcare, retail, education, social media, manufacturing, transportation, entertainment and so on. As reported recently, with nearly 100,000 vacancies, India is the second biggest data analytics jobs hub after the US and demand for data science skill sets is increasing at a very fast pace.

    The field of data science has witnessed an immense growth in recent years particularly due to the rise of internet and social media. The exploration of data science by the business world initially started with analysis of business data and hence emphasis was given for financial data analytics. With the increase of multimedia data such as image, video, audio and text, each domain as mentioned above, many a times needs to perform analysis of such multimedia big data. Hence the study of data science includes analysis of multimedia data along with other types of data such as business data and unstructured social media data. In our daily life, now we are capturing data from sources such as i) sensors used in various places like agricultural fields, shopping malls, ii) posts on social media, iii) digital images and videos captured in cell phones and iv) purchase transactions made through e-commerce.  Analysis of such big data which could be multimodal in nature is a huge challenge. Modern technologies in the areas of artificial intelligence (AI) and machine learning (ML) are now extensively used to get insights of such big data.

    With the availability of modern technologies of data storage, cleaning and computing, the study of data science expanded beyond the boundaries of mathematics and statistics. In modern days the study of data science is constituted with the knowledge of mathematics, statistics and computer science. Data science brings together a lot of skills of these disciplines with adequate domain knowledge to help any organization find ways to i) take major business decisions, ii) reduce costs, iii) get in to new markets, iv) launch a new product or service, v) find the sentiment of the customers, vi) recruiting the best talent and so on.


    Eligibility Criteria

    A Bachelor’s degree in Science from a recognized university with an aggregate of 60% or its equivalent as per the norms set by the degree granting institute/university in Statistics, Mathematics, Physics, Computer Science, Economics, Econometrics and Operational Research OR

    A Bachelor’s degree Engineering or Technology from a recognized University with an aggregate of 60% or its equivalent as per the norms set by the degree granting institute/university in Computer Science, Information Technology and Electronics/Electronics and Communication/Electrical Engineering.

    Candidates with BCA, B.Sc. (IT), B.Sc. (AI/ML) and B.Sc. (Data Science)

    Candidates appearing in their final Degree examination and expecting to complete it by July 2023 may also apply. However, their final admission will be subject to the condition that they obtain an aggregate of 60% marks, or its equivalent as per the norms set by the degree granting institute/university. All admitted candidates have to submit their degree certificates or proof of completion of Degree, before 30 October 2023 failing which their admission is liable to cancellation.


    The decision of the concerned authorities of DA-IICT regarding eligibility of any candidate shall be final.

    Age: There is no age limit applicable to this program.

    Admission Details

    The candidates are selected through an entrance test to be conducted at selected centers all over the country. The tentative list of centers is: DAIICT Gandhinagar, Ahmedabad, Bhopal, Benguluru, Chennai, Mumbai, Hyderabad, Patna, Jaipur, Kolkata, New Delhi, Pune, Rajkot, Surat and Udaipur. The final merit list for admission will be prepared on the basis of the aggregate score in the entrance test.

    Entrance Test

    The test will evaluate the candidates on their mathematical aptitude, logical reasoning, and basic programming.

    Pattern: Multiple choice questions (MCQ) from four sections – Mathematics, Statistics, basic Computer Science (programming) and Quantitative Aptitude.

    Exam Duration: 90 minutes

    Weightage: All questions will carry equal weightage.

    Negative Marking: The correct answers for each question will be awarded 4 marks, each incorrect answer will be assigned a negative mark of -1 and 0.25 marks will be awarded for not attempting a questionThere will be no section wise cutoffs. However, a candidate should have a positive score in each section to be eligible to be included in the final merit list.

    Student Reviews for M.Sc Data Science

    College Infrastructure: 4/5
    Academics: 3.5/5
    Placements: 4.5/5
    Value for Money: 5/5
    Campus Life: 5/5

    Best place for to study, enjoy and to live in

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