MSc in Data Science course is affiliated to Mangalore University. This course creates postgraduates who can become data science experts capable of using different techniques to obtain answers to various queries, incorporating computer science, predictiveanalytics, statistics, and machine learning to parse through massive datasets. The course contains many statistical and computing papers along with their practicals.
Concerning career opportunities, Data Science offers jobs for freshers as business analyst, data scientist, statistician, or data architect.
M.Sc Data Science has been developed to create Postgraduates who can become data scientists capable of working with the massive amounts of data now common to many businesses. The main job role of a Data Scientist is to solve business problems and challenges. They should have the domain knowledge to understand business issues as well as industry-standard terminology and workflows.
Program Educational Objectives
The intent of the M.Sc. (Data Science) programme is to produce Data Scientists who are able to achieve the following objectives:
- Highly innovative and distinct in their approach to applying several techniques intelligently to extract data and derive the most meaningful outcomes
- Must be efficient to locate and explore several data resources
- Must have hands-on expertise with tools like R, and Python to perform data conditioning which is converting the data into useful information by applying statistical analysis, predictive analysis, and more
- Must be highly efficient in managing large amounts of data
- Must be able to work effectively with a team and also possess effective communication skills to deliver knowledge to the members of the team precisely
- Deal with complex data problems and ideally should have some expertise in multiple disciplines
Students graduating from our Data Science Programme will be able to choose many different roles:
- Data Scientist
- Data Administrator
- Data Analyst
- Business Analyst
- Analytics Manager
- Data Architect
- Business Intelligence Manager
- Data Manager
The learning outcomes of the degree are to foster:
- To Analyse and interpret data using an ethically responsible approach
- Use appropriate models of analysis, assess the quality of input, derive insight from results, and investigate potential issues
- Design, implement, populate and query relational databases for operational data
- Design, implement, populate and query data warehouses for informational data
- Harness very large data sets to make business decisions
- Apply computing theory, languages and algorithms, as well as mathematical and statistical models, and the principles of optimisation to appropriately formulate and use data analyses
- Evaluate the use of data from acquisition through cleansing, warehousing, analytics, and visualisation to the ultimate business decision
- Discern when to implement relational versus document oriented database structures
- Execute real-time analytical methods on streaming datasets to react quickly to customer needs
- Interpret data findings effectively to any audience, orally, visually and in written formats
M.Sc Data Science.. (Course for Data Scientist …)
The M.Sc. (Data Science) programme is designed to provide students with a comprehensive foundation for applying statistical methods to solve real-world problems. One goal of this programme is to prepare students for careers in Data Science with a broad knowledge of the application of statistical tools, techniques, and methods, as well as the ability to conduct in-depth analysis, synthesis, and evaluation of data. Another goal is to prepare students for careers with analytical database knowledge, the ability to apply analytical database tools, techniques, and methods, and the ability to design, develop, implement, programme, and maintain data marts and data warehouses.
Data science is the study of the computational principles, methods, and systems for extracting and structuring knowledge from data; and the application and use of those principles. Large data sets are now generated by almost every activity in science, society, and commerce – ranging from molecular biology to social media, from sustainable energy to health care. As a MSc Data Science student, you will explore how to efficiently find patterns in these vast streams of data. Many research areas have tackled parts of this problem. Machine learning focuses on finding patterns and making predictions from data; ideas from algorithms and databases are required to build systems that scale to big data streams; and separate research areas have grown around different types of unstructured data such as text, images, sensor data, video, and speech.
M.Sc Data Science at St Aloysius College (Autonomous), Mangalore – Highlights
- School of Information Technology is going to offer 2-Year M.Sc Data Science course from 2022 under the Autonomous Scheme
- M.Sc Data Science has an integrated curriculum that consists of a highly diverse set of Data Science, Statistics, IT courses, Big Data Technology Courses and interdisciplinary Big Data research projects, continuous interaction with industry and personality development courses.
- The programme equips students with the skill and relevant competence to handle all practical problems faced by the industry.
- The aim of the M.Sc (Data Science) programme is to produce leaders for the IT and Big Data industry and profession.
- Continuous advances in technology have resulted in an explosion in the range and nature of computer applications, Data Science, Big Data Technology and applications of Big Data in various domains which today include societal, scientific, industrial and financial applications.
- The core subjects like Data Science, Big Data Analytics, Data Warehousing and Data Mining, Multivariate Data Analytics, Cloud and Big Data etc through which the students will have a sound footing in the technical fundamentals.
- It also prepares them for advanced study in areas of their interest. Courses like Business Intelligence and Data Mining, Big Data Analytics with Map Reduce and Hadoop, and Soft Skills module tap the full potential of the students by improving time and self-management, communication skills, team spirit, confidence even, and career-building attitude.
- The newly proposed syllabi is as per the guidelines of Mangalore University- Hard Core, Soft Core, and Open Electives. In the newly proposed scheme, the Choice Based Credit System has been introduced to give better choices to the students in technology domains with a deep dive such as – Data Science, Business Analytics and Data Technologies.
- A candidate who has passed any recognised under graduate examination or equivalent examination with Mathematics, Statistics, Computer Science, Computer Applications, Computer Programming, Business Mathematics or Business Statistics as one of the optional subjects and obtained an aggregate minimum of 45% marks taken together in all the subjects in all the years of the Degree Examination is eligible for admission to the course. 40% of marks in Q. E. in case of SC, ST and Category-I of candidates.
- Provided that in respect of candidate who has studied and passed one of the subjects specified above in Pre-University Course with 50% percent of marks in that subject shall also be considered for admission. 45% of marks in case of SC, ST and Category-I of candidate
Recognition & Core Values
Learning at AIMIT extends beyond the classroom. Throughout the program, classroom learning is complemented by hands-on experiences. You have a project work, industrial visits, technical rounds, seminars, competitions and a host of other activities that are designed to enhance your understanding of computer applications.,
- M.Sc Data Science programme at AIMIT, St Aloysius College (Autonomous) is Recognised by the Mangalore University, UGC New Delhi
- The School of Information Technology has introduced the Data Science and Big Data related courses from 2010 at MCA and M.Sc Software Technology programmes
- Well qualified and experienced faculty in Data Science and Big Data Technology, trained through the industry-academia collaboration of the department.
- The programme starts with one month Refresher Course “Foundations of Information Technology” designed by Infosys under the Campus Connect Initiative.
- Several Industry Elective papers are being included in the syllabus from Infosys, IBM, EMC.
- The School of Information Technology has been awarded with a project to set up a Big Data Analytics Lab in Health Informatics by the Vision Group in Science & Technology (VGST) , Government of Karnataka .
- The students have to undergo Business Consultancy projects at various industries, which will help them to study the data patterns and arrive at business decisions.
- The School of IT is keen on working very closely with several Research & Development Institutions for advanced research work in Big Data.
- Encouraging the students to organise and deliver workshops, present and publish papers, and work closely with the faculty at the Special Interest Group in Technology.
- The School of IT is aiming at producing the effective Data Scientist and Big Data Analyst through this course, thus bridging the requirements gap at the industries in Big Data.
School of Information Technology of AIMIT provides
- International Standards in Course Structure in collaboration with Universities, Institutions and Companies from India and Abroad.
- World class ambience for Information Technology Studies.
- Wi-Fi enabled campus – available 24×7 in the classrooms, campus and especially in the hostels.
- Well equippedlabs with servers and nodes with software on bioinformatics installed.
- Access to latest e-journals and e-books through IEEE, ACM, Safari Books, 24×7 Books etc.
- Spacious library &reading rooms with latest editions of books
- Advanced syllabi under the autonomous stream; updated as per the industry-academia and research needs.
- Excellent placement records with leading companies –Data Analytics Companies.
- Internships in companies and research institutions – for product development, data analysis, and research.
- To participate in international / national level seminars /conferences and present papers as well as publish papers in national and international journals withhigh impact factor with the guidance of afaculty mentor.
- Organise workshops on latest trends in Data Analytics, Machine Learning & Big Data.
- Certification through MOOCS in various technologies as part of self study
- Special interest groups of faculty and students to enhance research &consultancy.
- Placement training – model interviews, analytics labs, analytics schools.
- Soft skill training in association with Infosys Leadership Development Institute.
- Leadership opportunity &training in organising various activities and events in the campus as well as participation in intercollegiate fests.
- Centre for Creativity & Innovation & Incubation – to promote entrepreneurship.
- National level IT Fests (epITome), IT Exhibition (Infovision), International Conference (SACAIM), Symposium (Anveeksha), Talent Hunt (Lakshya), Sports Day (Utkarasha), Defining Dialogues (Alumni Interaction).
- Rural Immersion Programme to reach out to the backward areas of Karnataka and get experience under Student Social Responsibility Programme.
- Industry visits to different locations and interact with industry professionals.
- Admission to M.Sc Data Scienceprogramme for Karnataka / Non Karnataka candidates is made based on Data Analytics Competency Test (DACT) conducted by St Aloysius College (Autonomous), Mangalore as per the norms of the Autonomous institute regulations.
- The minimum percentage in eligibility examination for admission in M.Sc Big Data Analytics programme is 50% in case GM and 45% in case of SC / ST.
- Ranking of the admission will be given based on 50% of the scores of Undergraduate Examination and the remaining 50% of the Scores from Data Analytics Competency Test (DACT)
- In the event of a particular department receiving a lesser number of applications than the number of seats available, the entrance test, where applicable, may not be conducted (As per Mangalore University regulations).