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GRV Business Management Academy BCA in Data Science

BCA in Data Science at GRV Business Management Academy - Course, Fees, Admission, Seats, Syllabus

location Bangalore ( Karnataka )
location Estd In: 2009
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BCA in Data Science at GRV Business Management Academy - Course, Fees, Admission, Seats, Syllabus
location
Bangalore ( Karnataka )
location
Estd In: 2009
Last Updated on February 21, 2024 5:28 PM
The GRV Business Management Academy, a known institution recognized for its wide range of educational offerings has introduced a new and unique program tailored for the growing field of data science. The Bachelor of Computer Applications (BCA) in Data Science. This crafted program is designed to provide students with the necessary skills and knowledge to succeed in the ever changing and dynamic world of data science. The curriculum covers areas such as Machine Learning, Big Data Analytics, Statistical Methods, Python Programming and Artificial Intelligence offering students a comprehensive and thorough understanding of the subject. The academy has limited the number of seats for this program to 60 students to create an environment focused on learning and individualized attention. The fees for this program have been set thoughtfully to ensure affordability without compromising on the quality of education provided. Admission to this program is based on performance in an entrance exam specifically designed to evaluate potential students suitability for a career in data science. This program not presents various career opportunities, in data science but also ensures that graduates are well equipped to face the challenges of the digital era with confidence and expertise.
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GRV Business Management Academy BCA in Data Science Highlights 2024

Course Duration3 Years
Course levelUndergraduate
Course Tuition FeesVaries
Mode of StudyFull Time
Institute TypePrivate

GRV Business Management Academy BCA in Data Science Syllabus 2024

The BCA program in Data Science at the GRV Business Management Academy aims to provide students with the skills and knowledge needed to succeed in the data science field. While the specific course content may vary slightly each year the core subjects typically encompass an array of topics that combine elements of computer science, statistical methods and management principles to effectively analyze data. Here are some key subjects usually covered in such a program; 1. **Foundations of Data Science**; This introductory course delves into the basics of data science exploring its origins, significance and applications across industries. 2. **Programming for Data Science**; Students acquire proficiency in programming languages for data science work particularly focusing on Python and R which are commonly used for data manipulation, analysis and visualization. 3. **Mathematics for Data Science**; Understanding mathematical principles like linear algebra, calculus and statistics is essential for applying various data science techniques. 4. **Data Structures and Algorithms**; This area explores concepts related to data structures (such, as arrays, lists, trees) and algorithms that play a crucial role in efficiently managing and analyzing data. In the course on Database Management Systems students will explore how to design, implement and oversee database systems learning about SQL for managing data The section on Data Mining and Predictive Analytics focuses on extracting insights from large datasets and utilizing statistical models to forecast future trends and patterns. Students will delve into Machine Learning algorithms covering supervised and unsupervised learning methods, neural networks, deep learning techniques and their practical applications in the field of data science. An overview of Big Data Technologies will introduce students to the tools and technologies for processing and analyzing large volumes of data including platforms like Hadoop, Spark and NoSQL databases. The curriculum also includes a segment on Data Visualization that teaches techniques and tools for visually representing data and interpreting it effectively using software such as Tableau and Power BI. Ethical considerations surrounding data privacy laws, protection regulations and responsible data usage are discussed in the Ethics and Data Privacy module to ensure students understand the importance of practices in handling data. Lastly Business Intelligence covers the strategies and technologies utilized by organizations, for analyzing business information to aid decision making processes.**Final Project**; A culminating assignment where students utilize their acquired knowledge to address data science challenges frequently working alongside industry collaborators. 13. **Internship/Work Placement**; Hands on learning opportunities gained from internships or industrial training to gain experience."

GRV Business Management Academy BCA in Data Science Important Topics 2024

As of my update in April 2023 detailed information about the BCA in Data Science program at the GRV Business Management Academy may not be easily accessible without reaching out to the institution directly or visiting their official website for the most up to date course offerings. However I can give you an overview of key subjects typically included in a Bachelor of Computer Applications (BCA) program specializing in Data Science. These subjects aim to equip students with the skills and knowledge required to succeed in the field of data science and analytics; **Introduction to Data Science**; Grasping the fundamentals of data science, its importance and its applications across various industries. **Fundamentals of Programming**; Acquiring proficiency in programming languages for data science, such as Python and R with emphasis on syntax, data structures and basic algorithms. **Mathematics for Data Science**; Delving into mathematical principles like linear algebra, calculus and statistics that form the foundation for comprehending and working with data science algorithms. **Database Management Systems (DBMS)**; Understanding how database management systems operate and their significance, in organizing and manipulating amounts of information effectively. In the realm of database systems SQL is utilized for data manipulation while NoSQL databases are adept at managing amounts of data. When it comes to Data Analysis and Visualization various techniques and tools are employed to analyze and draw insights from data. This often involves visualizing data using software like Tableau, Power BI or programming libraries such as Matplotlib and Seaborn in Python. Machine Learning delves into a spectrum of algorithms that encompass supervised and unsupervised learning, neural networks and deep learning. These algorithms find applications across domains. Big Data Technologies cover concepts such as the Hadoop ecosystem, Spark and other technologies used for processing and analyzing extensive datasets. Data Mining involves employing techniques and tools to uncover patterns, anomalies and derive insights from large datasets. Understanding Data Warehousing and Business Intelligence entails grasping the architecture design principles of data warehouses along with the pivotal role business intelligence plays in decision making processes. Ethics and Data Privacy discussions center around considerations in data science projects encompassing data protection laws. Emphasis is placed on maintaining privacy and security throughout all stages of data analysis. The Capstone Project serves as a culminating endeavor where students apply their acquired knowledge to tackle real world data science challenges. Collaboration with industry partners often enhances the projects real world applicability. It's essential to note that the specific curriculum details may vary among institutions with differing emphases, on topics. For the accurate and current information about the BCA, in Data Science course its recommended to check the official GRV Business Management Academy website or reach out to their admissions office directly.

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