Access subject-wise notes, unit-wise study material, important questions and previous year question papers for RGPV B.Tech Computer Science & Data Science 6th Semester students.
Select a subject to access its notes, units, important questions and examination resources.
Neural networks, backpropagation, optimization, CNN, RNN, LSTM, attention mechanisms and generative models.
Open NotesNetwork architecture, data link layer, MAC protocols, routing, TCP/IP and application layer protocols.
Open NotesBig data concepts, Hadoop, HDFS, MapReduce, Hive, Pig, NoSQL and social network mining.
Open NotesDigital data systems, data analysis, file systems, data recovery and digital communication.
Open NotesObject databases, distributed databases, advanced transactions, active databases, multimedia databases and web databases.
Open NotesInformation retrieval models, TF-IDF, search engines, PageRank, ranking, recommendation and text mining.
Open NotesAgile principles, Scrum, XP, product backlog, sprint planning, refactoring, continuous integration and TDD.
Open NotesNLP fundamentals, text preprocessing, POS tagging, parsing, semantics, speech processing and NLP applications.
Open NotesOrganise every subject into individual units for faster examination preparation.
Each subject page can contain unit-wise notes, important questions and previous year question papers. Students can directly open the required unit instead of searching through the complete subject.
The sixth semester is an important stage for students pursuing Computer Science and Data Science because the curriculum focuses on advanced areas such as deep learning, big data, databases, information retrieval, natural language processing and software development.
This page provides an organised structure for accessing RGPV Data Science sixth semester study material. Students can select individual subjects and then access unit-wise notes, important questions and previous year question papers.
The major subjects listed on this page include Deep Learning, Computer Networks, Big Data Analytics, Data Acquisition, Advanced Database Management System, Information Extraction & Retrieval, Agile Software Development and Natural Language Processing.
Subject pages can contain PDF notes, unit-wise study material, important questions, previous year question papers and examination-oriented resources.
Start by understanding the syllabus and divide your preparation subject-wise and unit-wise. Focus on understanding concepts first, then practise important questions and previous year papers before the examination.
Access useful study resources for CS-DS students.
Neural networks, CNN, RNN, LSTM, optimization and modern deep learning concepts.
Open Deep Learning →Hadoop, HDFS, MapReduce, Hive, Pig, NoSQL and big data technologies.
Open Big Data →Text processing, POS tagging, parsing, semantics and NLP applications.
Open NLP →Network architecture, routing, TCP/IP, MAC protocols and application layer protocols.
Open Computer Networks →Common questions about sixth semester study material.
Select the required subject from the subject section and then open its notes page.
This page currently includes eight subjects and elective subjects under CD 603 and CD 604.
The subjects include Deep Learning, Computer Networks, Big Data Analytics, Data Acquisition, Advanced DBMS, Information Extraction & Retrieval, Agile Software Development and Natural Language Processing.
Yes. Each subject page can be organised into five units so students can directly access the required topic.
PYQ papers can be added to each subject page along with important examination questions.
No. RGPV Notes is an independent educational platform created to help students access study material and prepare for university examinations.
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