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MMYVVDDE BCA in Data Analytics

BCA in Data Analytics at MMYVVDDE - Course, Fees, Admission, Seats, Syllabus

location Katni ( Madhya Pradesh )
location Estd In: 1995
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BCA in Data Analytics at MMYVVDDE - Course, Fees, Admission, Seats, Syllabus
location
Katni ( Madhya Pradesh )
location
Estd In: 1995
Last Updated on February 15, 2024 4:35 PM
Maharishi Mahesh Yogi Vedic Vishwavidyalaya is an educational institution that stands out for its innovative educational methods. They offer a Bachelor of Computer Applications (BCA) in Data Analytics, which addresses the increasing demand for professionals in data analytics. This comprehensive program is carefully designed to provide students with a foundation in data analytics principles and equip them with practical skills to analyze interpret and transform data into actionable insights. The universitys serene learning environment, along with teaching techniques and state of the art technologies ensures a well rounded educational experience. The BCA in Data Analytics curriculum covers a range of subjects that include statistics, programming, data mining, machine learning and big data technologies. Its goal is to equip students with the tools to tackle complex data challenges across various sectors like finance, healthcare, retail and more. Through a combination of knowledge and hands on projects students are prepared to excel in the rapidly evolving field of data analytics. The commitment to excellence by Maharishi Mahesh Yogi Vedic Vishwavidyalaya and its unique approach based on Vedic science make their BCA in Data Analytics program an outstanding choice for aspiring professionals seeking opportunities, in the world of data analysis.
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MMYVVDDE BCA in Data Analytics Highlights 2024

ParameterDetail
Course Duration3 Years
Course LevelUndergraduate
Course Tuition FeesVaries
Mode of StudyFull-time
Institute TypePrivate

MMYVVDDE BCA in Data Analytics Syllabus 2024

As of my last update in April 2023, I don't have access to the specific course syllabus for the BCA in Data Analytics at Maharishi Mahesh Yogi Vedic Vishwavidyalaya. Course syllabi can vary significantly between institutions and are subject to change. However, I can provide you with a general outline of what a BCA in Data Analytics program might include, based on common subjects and topics in similar programs. For the most accurate and up-to-date syllabus, please consult the official Maharishi Mahesh Yogi Vedic Vishwavidyalaya website or contact the university directly. Below is a hypothetical table outline for a BCA in Data Analytics program, structured in a general format that such programs might follow:
SemesterSubjectsTopics
Semester 1Introduction to Programming, Mathematics for Data Science, Principles of ManagementProgramming Basics, Algebra and Calculus, Management Fundamentals
Semester 2Database Management Systems, Data Structures and Algorithms, Organizational BehaviorSQL, Data Organization, Team Dynamics
Semester 3Operating Systems, Statistics for Data Science, Web TechnologiesOS Principles, Probability and Statistics, HTML/CSS/JavaScript
Semester 4Object-Oriented Programming, Data Visualization, Business AnalyticsJava or Python, Tableau or Power BI, Analytical Decision-Making
Semester 5Machine Learning, Big Data Analytics, Elective (e.g., Cloud Computing, IoT, etc.)Supervised and Unsupervised Learning, Hadoop and Spark, Specific Technology Study
Semester 6Capstone Project, Data Ethics and Law, Advanced Data Analytics TechniquesProject Work, Privacy and Security, Deep Learning/Time Series Analysis
This table is a simplified and hypothetical example. Actual course offerings, subjects, and topics can vary. Electives and specific course content might change based on emerging technologies and industry demands. Always refer to the university's official curriculum for the most accurate information.

MMYVVDDE BCA in Data Analytics Important Topics 2024

Important Topics in BCA in Data Analytics
Introduction to Data Analytics
Programming for Data Science
Database Management Systems
Data Mining and Predictive Modeling
Big Data Technologies
Machine Learning Algorithms
Statistical Methods for Decision Making
Data Visualization Techniques
Cloud Computing for Data Analytics
Ethics and Data Security

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