Data science is a “concept to unify statistics, data analysis, machine learning, and their related methods” 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 in an organization is called data science. It primarily involves obtaining 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 amounts of structured and unstructured data daily. Evolving technologies are leading to cost-saving solutions for the storage and analysis of such large data. In the current era, for career progression, one needs to understand the language of data through analytical skills. Hence, it is necessary nowadays, to develop manpower with the 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. 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) make major business decisions, ii) reduce costs, iii) get into new markets, iv) launch a new product or service, v) find the sentiment of the customers, vi) recruiting the best talent and so on.
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
Programe Objective
The primary objective of the M.Sc. in Data Science program is to develop a skilled professional workforce that is prepared to address the increasing needs in the rapidly expanding area of big data analytics. The program aims to provide skills in quantitative data analysis, data mining, data modeling and prediction, data storage and management, machine learning, big data processing, data visualization, multimedia big data, programming and communication skills. Value Added Course/ training and a large number of practical case studies have been integrated into the program to boost the learner's confidence and market acceptability.
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
Salient Features
Curriculum based on Research and Development and industry needs
Career prospects in major sectors such as Agriculture. Healthcare, education and Infrastructure, Banking etc,
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
VISION
To excel in Computer Science and Engineering education, research and project management by empowering the students with strong conceptual knowledge.
MISSION
M1: To educate the students with basic foundation blocks of core and allied disciplines of Computer Science.
M2: To provide practical skills in the advancements of the Computer Science field required for the growing dynamic IT and ITES industries.
M3: To sculpt strong personal, technical, research, entrepreneurial, and leadership skills.
M4: To inculcate knowledge in lifelong learning, professional ethics and contribution to the society.
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
Eligibility Criteria
For M.Sc. (Data Science): Bachelor’s degree in Mathematics / Computer Science / Information Technology/ Data Science/Artificial Intelligence/ Computer Application from any recognized University/institute with a minimum of 50% aggregate marks or equivalent grade Final year students can also apply
Participants
Science (Statistics, Mathematics, Physics)/ IT/ Computer Science/ Data Science/ Economics/ Engineering Graduates or its equivalent with good mathematical aptitude, basic programming skills, and inclination to pursue a career in data science. Professionals who are interested in upskilling in the field of data science.
Data Science jobs for freshers may include the job of a business analyst, data scientist, statistician or data architect.
Big Data Engineer: Big data engineers develop, maintain, test, and evaluate big data solutions within organizations.
Machine Learning Engineer: Machine learning engineers have to design and implement machine learning applications/algorithms to address business challenges.
Data Engineer/Data Architect: Data engineers/architects develop, construct, test, and maintain highly scalable data management systems.
Data Scientist: Data scientists have to understand the challenges of business and offer the best solutions using data analysis and data processing.
Statistician: The statistician interprets the results, along with strategic recommendations or incisive predictions, using data visualization tools or reports.
Data Analysts: Data analysts are involved in data manipulations and data visualization. Business Analysts: Business analysts use predictive, prescriptive, and descriptive analyses to transform complex data into easily understood actionable insights for the users.
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
FAQ
What can I do with an MSc in data science?
With an MSc in data science, you can pursue a variety of careers related to data analysis, data modeling, and data visualization. Some common job titles for individuals with an MSc in data science include data scientist, data analyst, data engineer, machine learning engineer, and business intelligence analyst.
Is an MSc in data science useful?
Yes, an MSc in data science can be very useful in today’s job market. With the increasing amount of data being generated in various industries, the demand for individuals with data science skills has also increased. Obtaining an MSc in data science can help you stand out in the job market and provide you with the necessary skills to succeed in a data-driven world.
What are the future prospects of MSc data science?
The future prospects of an MSc in data science are very promising. As the amount of data being generated continues to rapidly expand, even exponentially, the demand for skilled data scientists and analysts will only continue to grow. Additionally, emerging technologies such as artificial intelligence and machine learning are also creating new opportunities for those with data science skills.
Does data science have coding?
Yes, data science does involve coding. Individuals with data science skills should have a strong understanding of programming languages such as Python, and SQL in order to effectively work with and analyze data.
Is there any scope in data science?
Yes, there is a lot of scope in data science. As mentioned earlier, the increasing amount of data being generated in various industries has created a high demand for skilled data scientists and analysts.
Which branch is good for data science?
There are several branches that are good for data science, including computer science, statistics, mathematics, and engineering. However, it’s important to note that data science skills can be developed through a variety of educational backgrounds.
Is data science easy to get a job?
Obtaining a job in data science can be challenging, especially for individuals who are just starting out in the field. However, with the right skills and experience, it is possible to obtain a job in data science.
Is a data science job an IT job?
While data science involves working with technology and data, it is not necessarily an IT job. Data scientists and analysts work with data to provide insights and make informed decisions, whereas IT professionals focus on the management and maintenance of technology systems.
Is a career in data science safe?
It’s difficult to predict the future, but currently, a career in data science appears to be relatively safe. As mentioned earlier, the demand for skilled data scientists and analysts is high, and this trend is likely to continue as the amount of data being generated increases.
Which is better, data science or IT?
It’s not necessarily a matter of which is better, as data science and IT serve different purposes. Data science involves working with data to provide insights and make informed decisions, whereas IT focuses on the management and maintenance of technology systems.
Is data science a stable career?
Data science appears to be a stable career at the moment, as the demand for skilled data scientists and analysts is high and is likely to continue to grow as the amount of data being generated continues to increase. However, it’s important to stay up to date with emerging technologies and trends in data science.
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
PROGRAM’S EDUCATIONAL OBJECTIVES (PEO’S)
PE O1: To prepare graduates to be successful professionals in industry, government, academia, research, entrepreneurial pursuit, and consulting firms.
PE O2: To prepare graduates to achieve peer recognition, as individuals and as a team player, through demonstration of good analytical, design, implementation and interpersonal skills.
PE O3: To prepare graduates to contribute to society as broadly educated, expressive, ethical, and responsible citizens with proven expertise.
PE O4: To prepare graduates to pursue life-long learning to fulfil their goals.
PROGRAM OUTCOMES (PO'S)
PO 1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
PO 2: Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
PO 3: Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
PO 4: Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
PO 5: Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
PO 6: The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
PO 7: Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
PO 8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
PO 9: Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO 10: Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
PO 11: Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
PO 12: Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
PROGRAM OUTCOMES (PO'S)
PSO 1: To model computational problems by applying mathematical concepts and solving real-world problems using algorithmic techniques.
PSO 2: To apply the mathematical and statistical approaches for analyzing, designing and development of computing systems in interdisciplinary applications.
PSO 3: To work as a socially responsible professional by drawing statistical inference using software tools in real-world problems.
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
Our Faculty
S.NO
NAME OF THE FACULTY
DESIGNATION
EXPERIENCE
SPECIALIZATION
1
Dr.I.Lakshmi
Associate Professor
1 and 6 months in Hindustan 17 Years other
IOT,Data Science, Security,Image Compression
2
Ms. Praisy
Assistant Professor
4 Years and 10 months in others
Computer Networks, Machine Learning, Deep Learning
3
Ms.T.Vani
Assistant Professor
7 Years in others
Computer Network 1. Deep Learning 2.Machine Learning
Data science is a “concept to unify statistics, data analysis, machine learning, and their related methods” 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 in an organization is called data science. It primarily involves obtaining 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 amounts of structured and unstructured data daily. Evolving technologies are leading to cost-saving solutions for the storage and analysis of such large data. In the current era, for career progression, one needs to understand the language of data through analytical skills. Hence, it is necessary nowadays, to develop manpower with the 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. 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) make major business decisions, ii) reduce costs, iii) get into new markets, iv) launch a new product or service, v) find the sentiment of the customers, vi) recruiting the best talent and so on.
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
Programe Objective
The primary objective of the M.Sc. in Data Science program is to develop a skilled professional workforce that is prepared to address the increasing needs in the rapidly expanding area of big data analytics. The program aims to provide skills in quantitative data analysis, data mining, data modeling and prediction, data storage and management, machine learning, big data processing, data visualization, multimedia big data, programming and communication skills. Value Added Course/ training and a large number of practical case studies have been integrated into the program to boost the learner's confidence and market acceptability.
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
Salient Features
Curriculum based on Research and Development and industry needs
Career prospects in major sectors such as Agriculture. Healthcare, education and Infrastructure, Banking etc,
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
VISION
To excel in Computer Science and Engineering education, research and project management by empowering the students with strong conceptual knowledge.
MISSION
M1: To educate the students with basic foundation blocks of core and allied disciplines of Computer Science.
M2: To provide practical skills in the advancements of the Computer Science field required for the growing dynamic IT and ITES industries.
M3: To sculpt strong personal, technical, research, entrepreneurial, and leadership skills.
M4: To inculcate knowledge in lifelong learning, professional ethics and contribution to the society.
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
Eligibility Criteria
For M.Sc. (Data Science): Bachelor’s degree in Mathematics / Computer Science / Information Technology/ Data Science/Artificial Intelligence/ Computer Application from any recognized University/institute with a minimum of 50% aggregate marks or equivalent grade Final year students can also apply
Participants
Science (Statistics, Mathematics, Physics)/ IT/ Computer Science/ Data Science/ Economics/ Engineering Graduates or its equivalent with good mathematical aptitude, basic programming skills, and inclination to pursue a career in data science. Professionals who are interested in upskilling in the field of data science.
Data Science jobs for freshers may include the job of a business analyst, data scientist, statistician or data architect.
Big Data Engineer: Big data engineers develop, maintain, test, and evaluate big data solutions within organizations.
Machine Learning Engineer: Machine learning engineers have to design and implement machine learning applications/algorithms to address business challenges.
Data Engineer/Data Architect: Data engineers/architects develop, construct, test, and maintain highly scalable data management systems.
Data Scientist: Data scientists have to understand the challenges of business and offer the best solutions using data analysis and data processing.
Statistician: The statistician interprets the results, along with strategic recommendations or incisive predictions, using data visualization tools or reports.
Data Analysts: Data analysts are involved in data manipulations and data visualization. Business Analysts: Business analysts use predictive, prescriptive, and descriptive analyses to transform complex data into easily understood actionable insights for the users.
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
FAQ
What can I do with an MSc in data science?
With an MSc in data science, you can pursue a variety of careers related to data analysis, data modeling, and data visualization. Some common job titles for individuals with an MSc in data science include data scientist, data analyst, data engineer, machine learning engineer, and business intelligence analyst.
Is an MSc in data science useful?
Yes, an MSc in data science can be very useful in today’s job market. With the increasing amount of data being generated in various industries, the demand for individuals with data science skills has also increased. Obtaining an MSc in data science can help you stand out in the job market and provide you with the necessary skills to succeed in a data-driven world.
What are the future prospects of MSc data science?
The future prospects of an MSc in data science are very promising. As the amount of data being generated continues to rapidly expand, even exponentially, the demand for skilled data scientists and analysts will only continue to grow. Additionally, emerging technologies such as artificial intelligence and machine learning are also creating new opportunities for those with data science skills.
Does data science have coding?
Yes, data science does involve coding. Individuals with data science skills should have a strong understanding of programming languages such as Python, and SQL in order to effectively work with and analyze data.
Is there any scope in data science?
Yes, there is a lot of scope in data science. As mentioned earlier, the increasing amount of data being generated in various industries has created a high demand for skilled data scientists and analysts.
Which branch is good for data science?
There are several branches that are good for data science, including computer science, statistics, mathematics, and engineering. However, it’s important to note that data science skills can be developed through a variety of educational backgrounds.
Is data science easy to get a job?
Obtaining a job in data science can be challenging, especially for individuals who are just starting out in the field. However, with the right skills and experience, it is possible to obtain a job in data science.
Is a data science job an IT job?
While data science involves working with technology and data, it is not necessarily an IT job. Data scientists and analysts work with data to provide insights and make informed decisions, whereas IT professionals focus on the management and maintenance of technology systems.
Is a career in data science safe?
It’s difficult to predict the future, but currently, a career in data science appears to be relatively safe. As mentioned earlier, the demand for skilled data scientists and analysts is high, and this trend is likely to continue as the amount of data being generated increases.
Which is better, data science or IT?
It’s not necessarily a matter of which is better, as data science and IT serve different purposes. Data science involves working with data to provide insights and make informed decisions, whereas IT focuses on the management and maintenance of technology systems.
Is data science a stable career?
Data science appears to be a stable career at the moment, as the demand for skilled data scientists and analysts is high and is likely to continue to grow as the amount of data being generated continues to increase. However, it’s important to stay up to date with emerging technologies and trends in data science.
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
PROGRAM’S EDUCATIONAL OBJECTIVES (PEO’S)
PE O1: To prepare graduates to be successful professionals in industry, government, academia, research, entrepreneurial pursuit, and consulting firms.
PE O2: To prepare graduates to achieve peer recognition, as individuals and as a team player, through demonstration of good analytical, design, implementation and interpersonal skills.
PE O3: To prepare graduates to contribute to society as broadly educated, expressive, ethical, and responsible citizens with proven expertise.
PE O4: To prepare graduates to pursue life-long learning to fulfil their goals.
PROGRAM OUTCOMES (PO'S)
PO 1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
PO 2: Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
PO 3: Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
PO 4: Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
PO 5: Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
PO 6: The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
PO 7: Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
PO 8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
PO 9: Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO 10: Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
PO 11: Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
PO 12: Life-long learning: Recognize the need for, and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
PROGRAM OUTCOMES (PO'S)
PSO 1: To model computational problems by applying mathematical concepts and solving real-world problems using algorithmic techniques.
PSO 2: To apply the mathematical and statistical approaches for analyzing, designing and development of computing systems in interdisciplinary applications.
PSO 3: To work as a socially responsible professional by drawing statistical inference using software tools in real-world problems.
SCHOOL OF LIBERAL ARTS & APPLIED SCIENCES
Our Faculty
S.NO
NAME OF THE FACULTY
DESIGNATION
EXPERIENCE
SPECIALIZATION
1
Dr.I.Lakshmi
Associate Professor
1 and 6 months in Hindustan 17 Years other
IOT,Data Science, Security,Image Compression
2
Ms. Praisy
Assistant Professor
4 Years and 10 months in others
Computer Networks, Machine Learning, Deep Learning
3
Ms.T.Vani
Assistant Professor
7 Years in others
Computer Network 1. Deep Learning 2.Machine Learning