BCA in Data Analytics at Moodlakatte Institute Of Technology - Course, Fees, Admission, Seats, Syllabus

In my recent update as of April 2023 the specific course outlines for the BCA program in Data Analytics at Moodlakatte Institute Of Technology or other institutions may differ due to updates in the curriculum decisions made by faculty members and changing industry trends. However I can offer you an overview of key topics typically included in a BCA program with a focus on Data Analytics. These topics aim to provide students with a grounding in computer applications and specialized knowledge in data analytics. Here's a general outline; 1. **Introduction to Computer Science**; Covers concepts of computer science, including hardware, software and basic computing principles. 2. **Programming Fundamentals**; Involves learning programming languages like Python, R or Java essential for data analysis and manipulation. 3. **Database Management Systems (DBMS)**; Provides understanding of databases SQL (Structured Query Language) and efficient data management and retrieval techniques. 4. **Data Structures and Algorithms**; Focuses on how to store, manage and process data using various structures and algorithms. 5. **Statistics and Probability**; Establishes a foundation in statistics and probability, for effective data analysis and interpretation. Exploring Data Analysis and Visualization; Delving into the world of analyzing data sets to uncover insights and presenting data visually using tools such as Tableau, Power BI or Pythons Matplotlib and Seaborn libraries. Introduction to Machine Learning; Getting acquainted with the basics of machine learning concepts, algorithms and their practical applications in data analysis. Understanding Big Data Technologies; Grasping the principles behind big data technologies like Hadoop, Spark and their significance in managing extensive datasets. Mastering Data Mining Techniques; Acquiring skills in extracting valuable information and patterns from large datasets effectively. Diving into Business Intelligence; Discovering how data analytics can be leveraged in business settings to drive decision making processes. Ethics and Data Privacy Awareness; Recognizing the implications and privacy regulations associated with handling and analyzing data responsibly. Engaging in Capstone Projects/Internships; Gaining hands on experience through real world projects or internships to apply knowledge in practical scenarios. It is advisable to review the curriculum provided by Moodlakatte Institute Of Technology for the most up to date information. Additionally keeping up with advancements in tools, technologies and methodologies within the realm of data analytics is crucial due, to its nature."}

Module	Important Topics
Introduction to Data Analytics	Basics of Data Analytics, Data Types, Data Analytics Process
Programming for Data Analytics	Python/R Programming, Data Structures, Control Structures
Statistical Methods for Data Analysis	Descriptive Statistics, Inferential Statistics, Probability Distributions
Data Visualization	Principles of Data Visualization, Tools (Tableau, Power BI), Dashboard Design
Database Management	SQL, NoSQL, Data Warehousing, Data Mining
Machine Learning	Supervised Learning, Unsupervised Learning, Model Evaluation
Big Data Analytics	Hadoop, Spark, Big Data Processing Frameworks
Business Intelligence	BI Concepts, Tools, Strategic Decision-Making
Project Work	Real-world Data Analytics Project, Project Management, Reporting

Please note that the specific topics and modules might vary slightly based on the current syllabus and updates to the course content. It's always a good idea to refer to the official Moodlakatte Institute Of Technology curriculum or contact the institute directly for the most accurate and up-to-date information.