{"id":4048,"date":"2020-11-18T06:36:59","date_gmt":"2020-11-18T06:36:59","guid":{"rendered":"https:\/\/www.rathinamcollege.edu.in\/arts-college\/?page_id=4048"},"modified":"2025-02-13T07:26:07","modified_gmt":"2025-02-13T07:26:07","slug":"m-sc-data-science-and-business-analysis","status":"publish","type":"page","link":"https:\/\/rathinamglobal.edu.in\/blog\/m-sc-data-science-and-business-analysis\/","title":{"rendered":"M.Sc Data Science and Business Analysis"},"content":{"rendered":"<div class=\"wpb-content-wrapper\">[vc_row][vc_column css=&#8221;.vc_custom_1605681894134{border-top-width: 2px !important;border-right-width: 2px !important;border-bottom-width: 2px !important;border-left-width: 2px !important;border-left-color: #0095d4 !important;border-left-style: solid !important;border-right-color: #0095d4 !important;border-right-style: solid !important;border-top-color: #0095d4 !important;border-top-style: solid !important;border-bottom-color: #0095d4 !important;border-bottom-style: solid !important;border-radius: 2px !important;}&#8221;][vc_tta_tabs][vc_tta_section title=&#8221;Overview of the Program&#8221; tab_id=&#8221;Overview-of-the-Program&#8221;][vc_column_text]The Department of Computer Application was established in the year 2001 with the objective of imparting quality education in the field of Computer Applications. The Department has started M.Sc. Data Science and Business Analysis program in the year of 2018. The department has modern facilities for teaching, learning, and research. The Department offers a wide array of research opportunities and programs of study at the postgraduate level. M.Sc. DSBA and the syllabi for these courses are designed by keeping under consideration the requirement of time as well as the demand of the IT industry. With rapidly evolving technology and the continuous need for innovation, the Department of Computer Applications has produced quality professionals holding important positions in the IT industry in India and abroad. Students from both undergraduate and postgraduate courses have been able to secure a place in the IT market even before the completion of their final examination, which gives an idea of strong placement in this department. There are a plethora of companies, which visit the department every year for the recruitment of students, like TCS, Accenture, Infosys, IBM, MindTree, HCL, Info system, NIC, WIPRO, and many more.<\/p>\n<p>The battle for high-quality jobs is getting tougher in this competitive world, so it\u2019s more important than ever to have the best qualifications possible for better career opportunities. Studying for an MSc forsake, won\u2019t be enough by itself to get into the commendable level, but it could be extremely rewarding in other ways if one plans better. Masters in the cross-level program from under graduation would widen the scope of career opportunity in this competitive world with a higher quotient in selection for both fields.<\/p>\n<p>Upgrading one\u2019s qualifications and getting an M.Sc. is a brilliant way to prove to the potential and sustainable employers that one has what it takes to work in a high-profile position. Not only does it demonstrate the potential candidate can handle additional responsibility, but it also suggests that added value and asset to the organization. That is the reason, why many of the senior managers at leading companies tend to have a master\u2019s degree. Master in Business Analytics will prove the quality of a candidate in this \u201cData Era\u201d.<\/p>\n<p>Career? Or Job? Both the terms are actionably seeming to be related but not for sustainable development and goal achievement. Career meant for the long term, futuristic and sustainable. Job doesn\u2019t. Choosing a career after university education is a deciding factor for one\u2019s living standards. In this current situation, in a heavily populated country like India, getting employment is a bigger challenge. Making better decisions about career plans is the primary achievement, as career plans enhance one\u2019s future value. After globalization, career evangelists come up with a new era called the \u201cData Era\u201d, as from the last two years of data generation is approximately equal to the data generated in past all years. Hence, every industry dumped with 4V\u2019s of data \u2013 Volume, Velocity, Variety, and Veracity, and they need to be analyzed for the better nurturement of business with meaningful insights.<\/p>\n<p>Irrespective of any business domain, industries are in dire need of analyzing their huge volume of data in a proper way to come up with new insights which will help them in revenue generation and business development. There is a huge dearth of resource person on analyzing the data and bringing with new ideas in parallel and vertical development of their business.<\/p>\n<p>Business Analytics refers to the skills, technologies, practices that are applied to past data and\/or processes to derive insights that can be used for future business planning. It is a field that is now applied across all domains and industries.<\/p>\n<p>The comprehensive Business Analytics curriculum provides a framework through which participants learn to enhance their management skills, expand their knowledge of Business Analytics, and gain a strategic perspective of the industry. Business analytics refers to the ways in which enterprises such as businesses, non-profits, and governments can use data to gain insights and make better decisions. Business analytics is applied in operations, marketing, finance, and strategic planning among other functions. The ability to use data effectively to drive rapid, precise, and profitable decisions has been a critical strategic advantage for companies as diverse as Walmart, Google, Capital One, and Disney. For example, Capital One uses sophisticated analytic capabilities to match credit card offerings to customers more accurately than their competition. Walmart uses analytics to monitor and update its inventory in a way that allows it to serve its customers at an exceptionally low cost. The program\u2019s courses and the final project are designed around the real-world integration of business disciplines. Apart from these courses, there are preparatory courses that will have to be completed before the program begins.<\/p>\n<p>Some of the important positions of Business Analyst Professionals in an organization are as follows:<\/p>\n<ul>\n<li>Business Analyst<\/li>\n<li>Associate Business Analyst<\/li>\n<li>Statistician<\/li>\n<li>Data Architect<\/li>\n<li>Junior Statistician<\/li>\n<li>Market Research Analyst<\/li>\n<li>Data Analytics Manager<\/li>\n<li>Health Care Analyst<\/li>\n<\/ul>\n<p><strong>Salient features:<\/strong><\/p>\n<ul>\n<li>This program offers a Business Analytics specialization focused on pre-processing, Storing, and analytics of data for the business environments.<\/li>\n<li>The Program is designed to impart strong knowledge of R programming and Python fundamentals, Business Management Concepts followed by conceptual and practical knowledge of Data Science Techniques and Big Data Analytics.<\/li>\n<li>The Program offers a unique value proposition by combining the important subject areas in each of these new-age fields of study for the Analyst industry.<\/li>\n<li>The program offers a wide range of technical and programming skill sets that complement the specialization subjects on Business Analytics.<\/li>\n<li>This program is primarily aimed at offering students flexibility in making their career choices in Business Management, Project Management, Data Management, Data Analytics, and Data Visualisation.<\/li>\n<li>The program ignites a spark of interest in widening their knowledge on business analytics techniques in different business domains.<\/li>\n<\/ul>\n[\/vc_column_text][\/vc_tta_section][vc_tta_section title=&#8221;PEO, PO &amp; PSO&#8221; tab_id=&#8221;PEO-PO-PSO&#8221;][vc_column_text]<strong>DepartmentProgram Educational Objectives (PEO)<\/strong><\/p>\n<div style=\"overflow-x: auto;\">\n<table width=\"639\">\n<tbody>\n<tr>\n<td width=\"54\">PEO1<\/td>\n<td width=\"567\">Graduates of this program will establish themselves as effective professionals by learning technical skills in the Business Analytics field and can pursue higher education by accruing knowledge and research.<\/td>\n<\/tr>\n<tr>\n<td width=\"54\">PEO2<\/td>\n<td width=\"567\">To apply hardware and software technologies that provide computing solutions for successful careers in industry\/higher education\/research.<\/td>\n<\/tr>\n<tr>\n<td width=\"54\">PEO3<\/td>\n<td width=\"567\">To apply hardware and software technologies that provide computing solutions for successful careers in industry\/higher education\/research.<\/td>\n<\/tr>\n<tr>\n<td width=\"54\">PEO4<\/td>\n<td width=\"567\">To set the foundation of mathematics, computer science, and problem-solving methodology for efficient implementation in the area of software services and developments.<\/td>\n<\/tr>\n<tr>\n<td width=\"54\">PEO5<\/td>\n<td width=\"567\">To apply hardware and software technologies that provide computing solutions for successful careers in industry\/higher education\/research.<\/td>\n<\/tr>\n<tr>\n<td width=\"54\">PEO6<\/td>\n<td width=\"567\">To adopt lifelong learning and act with Integrity requires engaging with commitment towards social responsibilities.<\/td>\n<\/tr>\n<tr>\n<td width=\"54\">PEO7<\/td>\n<td width=\"567\">To learn and explore how visualization makes decision-makers understand the business quickly and making rightful decisions.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n[\/vc_column_text][wgl_spacing spacer_size=&#8221;30px&#8221;][vc_column_text]<strong>Department Program Specific Outcome (PSO):<\/strong><\/p>\n<p>By the completion of the Data Science and Business Analysis program, the student will have the following Program specific outcomes.<\/p>\n<p><strong>PSO1<\/strong>: To Understand the difference between a continuous class label and discrete class label classification methods and to Predict the continuous class variable using linear regression analysis.<\/p>\n<p><strong>PSO2<\/strong>: To Analyze the various techniques\/types of Execution Types in Apache Pig and Understand the concept of different types of tables in Apache Hive.<\/p>\n<p><strong>PSO3<\/strong>: To apply appropriate management techniques for managing contemporary organizations.<\/p>\n<p><strong>PSO4<\/strong>: To Know elementary to advanced statistical methods in a Python Programming environment.<\/p>\n<p><strong>PSO5<\/strong>: To Understand the important difference between business performance management and business intelligence.<\/p>\n<p><strong>PSO6<\/strong>: To Learn the different business intelligence types, and the importance of report creation and dashboard design.<\/p>\n<p><strong>PSO7<\/strong>: To Apply and design suitable Virtualization concepts, Cloud Resource Management, and design scheduling algorithms and design scheduling algorithms for computing clouds.<\/p>\n<p><strong>PSO8<\/strong>: To Create and configure the compute, storage, and database services in the cloud which helps them to work with analytic services.[\/vc_column_text][wgl_spacing spacer_size=&#8221;30px&#8221;][vc_column_text]<strong>Department Program Outcome (PO):<\/strong><\/p>\n<p>By the completion of the Data Science and Business Analysis program, the student will have the following Program specific outcomes.<\/p>\n<div style=\"overflow-x: auto;\">\n<table width=\"662\">\n<tbody>\n<tr>\n<td width=\"53\"><strong>PO1<\/strong><\/td>\n<td width=\"591\">To plan, execute, and evaluate a computer-based system, process, component, or program to meet the requirements.<\/td>\n<\/tr>\n<tr>\n<td width=\"53\"><strong>PO2<\/strong><\/td>\n<td width=\"591\">To demonstrate the ability of professionalism in societal, environmental contexts, and discipline as individuals as well as in a team.<\/td>\n<\/tr>\n<tr>\n<td width=\"53\"><strong>PO3<\/strong><\/td>\n<td width=\"591\">To use research-based knowledge and research methods which include the design of the analysis, interpretation of data, synthesis of the information to provide valid conclusions.<\/td>\n<\/tr>\n<tr>\n<td width=\"53\"><strong>PO4<\/strong><\/td>\n<td width=\"591\">Continuous professional development through life-long learning.<\/td>\n<\/tr>\n<tr>\n<td width=\"53\"><strong>PO5<\/strong><\/td>\n<td width=\"591\">To design, formulate, and develop solutions to real-world challenges.<\/td>\n<\/tr>\n<tr>\n<td width=\"53\"><strong>PO6<\/strong><\/td>\n<td width=\"591\">Apply the understanding of computing principles to manage projects in multidisciplinary environments.<\/td>\n<\/tr>\n<tr>\n<td width=\"53\"><strong>PO7<\/strong><\/td>\n<td width=\"591\">Expertise in developing applications with required domain knowledge.<\/td>\n<\/tr>\n<tr>\n<td width=\"53\"><strong>PO8<\/strong><\/td>\n<td width=\"591\">Development of absolute written and verbal communication skills.<\/td>\n<\/tr>\n<tr>\n<td width=\"53\"><strong>PO9<\/strong><\/td>\n<td width=\"591\">To become entrepreneurs to apply the concept of computer applications to face the business challenges societal needs.<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n[\/vc_column_text][wgl_spacing spacer_size=&#8221;30px&#8221;][vc_column_text]<strong>Department Course Outcomes (CO):<\/strong><\/p>\n<ul>\n<li>Understand the fundamental concepts of data communications and networking<\/li>\n<li>Identify different components and their respective roles in a computer communication system.<\/li>\n<li>Apply the knowledge, concepts, and terms related to data communication and networking.<\/li>\n<li>know the strategies for securing network applications.<\/li>\n<li>The usefulness and importance of computer communication in today&#8217;s life and society.<\/li>\n<\/ul>\n[\/vc_column_text][vc_row_inner][vc_column_inner][wgl_spacing spacer_size=&#8221;30px&#8221;][vc_custom_heading text=&#8221;Click Here to Download Course Outcome&#8221; font_container=&#8221;tag:h4|text_align:left&#8221; use_theme_fonts=&#8221;yes&#8221;][wgl_spacing spacer_size=&#8221;15px&#8221;][wgl_button button_text=&#8221;Download&#8221; icon_type=&#8221;font&#8221; icon_pack=&#8221;fontawesome&#8221; icon_position=&#8221;right&#8221; icon_fontawesome=&#8221;fas fa-arrow-down&#8221; link=&#8221;url:https%3A%2F%2Frathinamglobal.edu.in%2Fblog%2Fwp-content%2Fuploads%2F2021%2F02%2FM.SC-DS-BA.pdf|target:_blank&#8221;][\/vc_column_inner][\/vc_row_inner][\/vc_tta_section][vc_tta_section title=&#8221;Curriculum Structure&#8221; tab_id=&#8221;Curriculum-Structure&#8221;][vc_column_text]\n<table>\n<tbody>\n<tr>\n<td>\n                Sem\n            <\/td>\n<td>\n                Part\n            <\/td>\n<td>\n                Type\n            <\/td>\n<td>\n                Sub Code\n            <\/td>\n<td>\n                Subject&nbsp;\n            <\/td>\n<td>\n                Credit\n            <\/td>\n<td>\n                Per Week\n            <\/td>\n<td>\n                CIA\n            <\/td>\n<td>\n                ESE\n            <\/td>\n<td>\n                Total\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                1.1\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                C1\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Core-I-Database Management Systems\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                5\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                1.2\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                C2\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Core-II-Business Intelligence\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                5\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                1.3\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                C3\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Core-III<br \/>\n                Business Statistics and Probability\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                5\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                1.4\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                C4\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Core-IV<br \/>\n                Data Analytics using Excel\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                5\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                1.5\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                SEC 1\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Skill &#8211; I&nbsp; (Practical \/ Training)<br \/>\n                R Programming Language\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                5\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                1.6\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                ELE 1\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Elective-1<br \/>\n                Operations Research \/ Business Economics\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                5\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>&nbsp;<\/td>\n<td>&nbsp;<\/td>\n<td>\n                &nbsp;\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                2.1\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                C5\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Core V-Linux Administration\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                5\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                2.2\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                C6\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Core VI- Business Ethics &ndash; I\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                5\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                2.3\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                C7\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Core VII- Sentiment Analytics\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                5\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                2.4\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                C8\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Core VIII- Market Research and Analytics\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                5\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                2.5\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                SEC 2\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Skill &#8211; II&nbsp; (Practical \/ Training)<br \/>\n                Python Programming\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                5\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                2.6\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                ELE 2\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Elective-2 Big Data Analytics\/Data Visualization\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                5\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>&nbsp;<\/td>\n<td>&nbsp;<\/td>\n<td>\n                &nbsp;\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                3.1\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                C9\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Core-IX-Advanced Machine Learning\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                6\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                3.2\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                C10\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Core-X- Business Ethics &ndash; II\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                6\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                3.3\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                C11\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Core &ndash; XI- Financial Econometrics\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                6\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                3.4\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                SEC 3\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Skill &#8211; III&nbsp; (Practical \/ Training)<br \/>\n                Exploratory Data Analysis\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                6\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                3.5\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                ELE 4\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Elective-3- Advanced Big Data Analytics\/&nbsp; Social Media Analytics\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                6\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                3.6\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                ITR\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Internship \/ Industrial Training<\/span><span style=\"font-weight: 400;\"><br \/><\/span><span style=\"font-weight: 400;\"> (Summer vacation at the end of II semester activity)\n            <\/td>\n<td>\n                2\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                0\n            <\/td>\n<td>\n                50\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>&nbsp;<\/td>\n<td>&nbsp;<\/td>\n<td>\n                &nbsp;\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                4.1\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                C12\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Core-XII- Artificial Neural Networks and Deep Learning\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                6\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                4.2\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                SEC 4\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Skill &#8211; IV (Practical \/ Training)<br \/>\n                Data Analytics using SQL\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                6\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                4.3\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                ELE 5\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Elective-4- Natural Language Processing \/ Reinforcement learning\n            <\/td>\n<td>\n                4\n            <\/td>\n<td>\n                6\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                50\n            <\/td>\n<td>\n                100\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                4.4\n            <\/td>\n<td>\n                3\n            <\/td>\n<td>\n                PRJ\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                Project with Viva-Voce\n            <\/td>\n<td>\n                8\n            <\/td>\n<td>\n                12\n            <\/td>\n<td>\n                100\n            <\/td>\n<td>\n                100\n            <\/td>\n<td>\n                200\n            <\/td>\n<\/tr>\n<tr>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<\/tr>\n<tr>\n<td colspan=\"5\">\n                TOTAL\n            <\/td>\n<td>\n                90\n            <\/td>\n<td>\n                120\n            <\/td>\n<td>\n                1150\n            <\/td>\n<td>\n                1100\n            <\/td>\n<td>\n                &nbsp;\n            <\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n[\/vc_column_text][\/vc_tta_section][vc_tta_section title=&#8221;Career Opportunities&#8221; tab_id=&#8221;Career-Opportunities&#8221;][vc_column_text]<strong>Areas of Placement opportunity <\/strong><br \/>\nBolster your job search with exclusive access to our private placement portal that\u2019s a goldmine for leads and references within the industry from both open and private networks.<\/p>\n<ul>\n<li>Data Scientist,<\/li>\n<li>Data Analyst,<\/li>\n<li>Data Engineer<\/li>\n<li>Product Analyst<\/li>\n<li>Business Analyst and<\/li>\n<li>Machine Learning Engineer<\/li>\n<\/ul>\n<p><strong>Entrepreneur opportunity \/ about alumni entrepreneur<\/strong><\/p>\n<p>Now, with data being the key criteria, the Indian society has been witnessing the rise of numerous startups which are engrossed in crunching data to develop robust data-driven models such that a proper analysis of the issue can be undertaken to formulate smart solutions. Hence, data science becomes a smart part of today\u2019s smart entrepreneurship. Because as an entrepreneur you will have to do many other things (sales, manage people, raise capital, negotiate supplies, etc).<\/p>\n<ul>\n<li>Higher Education opportunities (Research \/ Analyst )<\/li>\n<li>PG Program &#8211; Data Science &amp; Business Analytics<\/li>\n<li>Data Scientist Engineer<\/li>\n<li>Data Scientist<\/li>\n<li>Data Scientist \/ Applied Mathematician<\/li>\n<li>Education Research and Data Analyst<\/li>\n<li>Statistician (Data Scientist)<\/li>\n<\/ul>\n[\/vc_column_text][\/vc_tta_section][\/vc_tta_tabs][\/vc_column][\/vc_row]\n\n    <div class=\"xs_social_share_widget xs_share_url after_content \t\tmain_content  wslu-style-1 wslu-share-box-shaped wslu-fill-colored wslu-none wslu-share-horizontal wslu-theme-font-no wslu-main_content\">\n\n\t\t\n        <ul>\n\t\t\t        <\/ul>\n    <\/div> \n<\/div>","protected":false},"excerpt":{"rendered":"<p>[vc_row][vc_column css=&#8221;.vc_custom_1605681894134{border-top-width: 2px !important;border-right-width: 2px !important;border-bottom-width: 2px !important;border-left-width: 2px !important;border-left-color: #0095d4 !important;border-left-style: solid !important;border-right-color: #0095d4 !important;border-right-style: solid !important;border-top-color: #0095d4 !important;border-top-style: solid !important;border-bottom-color: #0095d4 !important;border-bottom-style: solid !important;border-radius: 2px !important;}&#8221;][vc_tta_tabs][vc_tta_section title=&#8221;Overview of the Program&#8221; tab_id=&#8221;Overview-of-the-Program&#8221;][vc_column_text]The Department of Computer Application was established in the year 2001 with the objective of imparting quality education in the field of Computer [&hellip;]<\/p>\n","protected":false},"author":11,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"postBodyCss":"","postBodyMargin":[],"postBodyPadding":[],"postBodyBackground":{"backgroundType":"classic","gradient":""},"footnotes":""},"class_list":["post-4048","page","type-page","status-publish","hentry"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.3 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>M.Sc Data Science and Business Analysis | Rathinam College of Arts &amp; Science<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/rathinamglobal.edu.in\/blog\/m-sc-data-science-and-business-analysis\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"M.Sc Data Science and Business Analysis | Rathinam College of Arts &amp; Science\" \/>\n<meta property=\"og:description\" content=\"[vc_row][vc_column css=&#8221;.vc_custom_1605681894134{border-top-width: 2px !important;border-right-width: 2px !important;border-bottom-width: 2px !important;border-left-width: 2px !important;border-left-color: #0095d4 !important;border-left-style: solid !important;border-right-color: #0095d4 !important;border-right-style: solid !important;border-top-color: #0095d4 !important;border-top-style: solid !important;border-bottom-color: #0095d4 !important;border-bottom-style: solid !important;border-radius: 2px !important;}&#8221;][vc_tta_tabs][vc_tta_section title=&#8221;Overview of the Program&#8221; tab_id=&#8221;Overview-of-the-Program&#8221;][vc_column_text]The Department of Computer Application was established in the year 2001 with the objective of imparting quality education in the field of Computer [&hellip;]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/rathinamglobal.edu.in\/blog\/m-sc-data-science-and-business-analysis\/\" \/>\n<meta property=\"og:site_name\" content=\"Rathinam Global Deemed to be University\" \/>\n<meta property=\"article:modified_time\" content=\"2025-02-13T07:26:07+00:00\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data1\" content=\"9 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/rathinamglobal.edu.in\\\/blog\\\/m-sc-data-science-and-business-analysis\\\/\",\"url\":\"https:\\\/\\\/rathinamglobal.edu.in\\\/blog\\\/m-sc-data-science-and-business-analysis\\\/\",\"name\":\"M.Sc Data Science and Business Analysis | Rathinam College of Arts & Science\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/rathinamglobal.edu.in\\\/blog\\\/#website\"},\"datePublished\":\"2020-11-18T06:36:59+00:00\",\"dateModified\":\"2025-02-13T07:26:07+00:00\",\"breadcrumb\":{\"@id\":\"https:\\\/\\\/rathinamglobal.edu.in\\\/blog\\\/m-sc-data-science-and-business-analysis\\\/#breadcrumb\"},\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\\\/\\\/rathinamglobal.edu.in\\\/blog\\\/m-sc-data-science-and-business-analysis\\\/\"]}]},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\\\/\\\/rathinamglobal.edu.in\\\/blog\\\/m-sc-data-science-and-business-analysis\\\/#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\\\/\\\/rathinamglobal.edu.in\\\/blog\\\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"M.Sc Data Science and Business Analysis\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\\\/\\\/rathinamglobal.edu.in\\\/blog\\\/#website\",\"url\":\"https:\\\/\\\/rathinamglobal.edu.in\\\/blog\\\/\",\"name\":\"Rathinam Global Deemed to be University\",\"description\":\"\",\"alternateName\":\"Rathinam Global Deemed to be University\",\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\\\/\\\/rathinamglobal.edu.in\\\/blog\\\/?s={search_term_string}\"},\"query-input\":{\"@type\":\"PropertyValueSpecification\",\"valueRequired\":true,\"valueName\":\"search_term_string\"}}],\"inLanguage\":\"en-US\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"M.Sc Data Science and Business Analysis | Rathinam College of Arts & Science","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/rathinamglobal.edu.in\/blog\/m-sc-data-science-and-business-analysis\/","og_locale":"en_US","og_type":"article","og_title":"M.Sc Data Science and Business Analysis | Rathinam College of Arts & Science","og_description":"[vc_row][vc_column css=&#8221;.vc_custom_1605681894134{border-top-width: 2px !important;border-right-width: 2px !important;border-bottom-width: 2px !important;border-left-width: 2px !important;border-left-color: #0095d4 !important;border-left-style: solid !important;border-right-color: #0095d4 !important;border-right-style: solid !important;border-top-color: #0095d4 !important;border-top-style: solid !important;border-bottom-color: #0095d4 !important;border-bottom-style: solid !important;border-radius: 2px !important;}&#8221;][vc_tta_tabs][vc_tta_section title=&#8221;Overview of the Program&#8221; 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