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The syllabus lists core theory courses, laboratory courses, professional electives, and open electives, including foundational subjects such as Matrices and Calculus, Engineering Chemistry, Programming for Problem Solving, Digital Electronics, Data Structures, Operating Systems, Database Management Systems, and Algorithms. It also covers advanced data science topics like Machine Learning, Big Data Analytics, ETL-Kafka/Talend, Predictive Analytics, and web/social media analytics, plus projects and internships, with L-T-P credit distribution for each offering.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":51,"@type":70,"position":76},"https://docshare.wps.com/template/general/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/r22-btech-cse-data-science-course-structure-syllabus-2/191509/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/r22-btech-cse-data-science-course-structure-syllabus-2/191509.png","ImageObject",442,249,{"name":88,"@type":89},"Jacob","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-09-28","2026-09-03",true,{"@type":98,"interactionType":99,"userInteractionCount":47},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"What types of courses are included in this B.Tech CSE (Data Science) course structure?","Question",{"text":108,"@type":109},"The structure includes theory courses, lab courses, professional electives, open electives, and project stages/internship or skill development courses.","Answer",{"name":111,"@type":106,"acceptedAnswer":112},"Which advanced Data Science subjects appear in the curriculum?",{"text":113,"@type":109},"It includes subjects such as Introduction to Data Science, Machine Learning, Big Data Analytics, ETL-Kafka/Talend, Predictive Analytics, and Web and Social Media Analytics, along with corresponding lab components.",{"name":115,"@type":106,"acceptedAnswer":116},"How is the curriculum organized across semesters?",{"text":117,"@type":109},"The document presents semester-wise course tables, showing course codes/titles and the L-T-P components with credits for each semester.","https://schema.org",{"og:url":78,"og:type":120,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":122,"canonical":78},"index,follow",{"doc_id":124,"site_id":56},191509,1788408987,{"code":4,"msg":5,"data":127},{"doc_id":124,"user_id":128,"nickname":88,"user_avatar":129,"doc_module":9,"category_id":50,"category_name":51,"doc_title":59,"doc_description":61,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":47,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":135,"language":136,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":61,"update_tm":125,"read_time":140},962084931830,"https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd","| S.\u003Cbr>No. | Course\u003Cbr>Code | Course | L | T | P |  | Credits |\n| --- | --- | --- | --- | --- | --- | --- | --- |\n| 1. | MA101BS | Matrices and Calculus | 3 | 1 | 0 |  | 4 |\n| 2. | CH102BS | Engineering Chemistry | 3 | 1 | 0 |  | 4 |\n| 3. | CS103ES | Programming for Problem Solving | 3 | 0 | 0 |  | 3 |\n| 4. | EE104ES | Basic Electrical Engineering | 2 | 0 | 0 |  | 2 |\n| 5. | ME105ES | Computer Aided Engineering Graphics | 1 | 0 | 4 |  | 3 |\n| 6. | CS106ES | Elements of Computer Science & Engineering | 0 | 0 | 2 |  | 1 |\n| 7. | CH107BS | Engineering Chemistry Laboratory | 0 | 0 | 2 |  | 1 |\n| 8. | CS108ES | Programming for Problem Solving Laboratory | 0 | 0 | 2 |  | 1 |\n| 9. | EE109ES | Basic Electrical Engineering Laboratory | 0 | 0 | 2 |  | 1 |\n|  |  | Induction Program |  |  |  |  |  |\n|  |  | Total | 12 | 2 |  | 12 | 20 |\n\n\n| S.\u003Cbr>No. | Course\u003Cbr>Code | Course | L | T | P | Credits |\n| --- | --- | --- | --- | --- | --- | --- |\n| 1. | MA201BS | Ordinary Differential Equations and Vector Calculus | 3 | 1 | 0 | 4 |\n| 2. | PH202BS | Applied Physics | 3 | 1 | 0 | 4 |\n| 3. | ME203ES | Engineering Workshop | 0 | 1 | 3 | 2.5 |\n| 4. | EN204HS | English for Skill Enhancement | 2 | 0 | 0 | 2 |\n| 5. | EC205ES | Electronic Devices and Circuits | 2 | 0 | 0 | 2 |\n| 6. | CS206ES | Python Programming Laboratory | 0 | 1 | 2 | 2 |\n| 7. | PH207BS | Applied Physics Laboratory | 0 | 0 | 3 | 1.5 |\n| 8. | EN208HS | English Language and Communication Skills Laboratory | 0 | 0 | 2 | 1 |\n| 9. | CS209ES | IT Workshop | 0 | 0 | 2 | 1 |\n| 10. | *MC210 | Environmental Science | 3 | 0 | 0 | 0 |\n|  |  | Total | 13 | 4 | 12 | 20 |\n\n\n| S. No. | Course\u003Cbr>Code | Course Title |  | L | T | P | Credits |\n| --- | --- | --- | --- | --- | --- | --- | --- |\n| 1 | DS301PC | Digital Electronics |  | 3 | 0 | 0 | 3 |\n| 2 | DS302PC | Data Structures |  | 3 | 0 | 0 | 3 |\n| 3 | DS303PC | Computer Oriented Statistical Methods |  | 3 | 1 | 0 | 4 |\n| 4 | DS304PC | Computer Organization and Architecture |  | 3 | 0 | 0 | 3 |\n| 5 | DS305PC | Object Oriented Programming through Java |  | 3 | 0 | 0 | 3 |\n| 6 | DS306PC | Data Structures Lab |  | 0 | 0 | 3 | 1.5 |\n| 7 | DS307PC | Object Oriented Programming through Java Lab |  | 0 | 0 | 3 | 1.5 |\n| 8 | DS308PC | Data visualization-R Programming/ Power BI |  | 0 | 0 | 2 | 1 |\n| 9 | *MC309 | Gender Sensitization Lab |  | 0 | 0 | 2 | 0 |\n|  |  |  | Total | 15 | 1 | 10 | 20 |\n\n\n| S. No. | Course\u003Cbr>Code | Course Title | L | T | P | Credits |\n| --- | --- | --- | --- | --- | --- | --- |\n| 1 | DS401PC | Discrete Mathematics | 3 | 0 | 0 | 3 |\n| 2 | SM402MS | Business Economics & Financial Analysis | 3 | 0 | 0 | 3 |\n| 3 | DS403PC | Operating Systems | 3 | 0 | 0 | 3 |\n| 4 | DS404PC | Database Management Systems | 3 | 0 | 0 | 3 |\n| 5 | DS405PC | Software Engineering | 3 | 0 | 0 | 3 |\n| 6 | DS406PC | Operating Systems Lab | 0 | 0 | 2 | 1 |\n| 7 | DS407PC | Database Management Systems Lab | 0 | 0 | 2 | 1 |\n| 8 | DS408PC | Real-time Research Project/ Societal Related Project | 0 | 0 | 4 | 2 |\n| 9 | DS409PC | Node JS/ React JS/ Django | 0 | 0 | 2 | 1 |\n| 10 | *MC410 | Constitution of India | 3 | 0 | 0 | 0 |\n|  |  | Total | 18 | 0 | 10 | 20 |\n\n\n| S. No. | Course\u003Cbr>Code | Course Title | L | T | P | Credits |\n| --- | --- | --- | --- | --- | --- | --- |\n| 1 | DS501PC | Algorithms Design and Analysis | 3 | 0 | 0 | 3 |\n| 2 | DS502PC | Introduction to Data Science | 3 | 1 | 0 | 4 |\n| 3 | DS503PC | Computer Networks | 3 | 0 | 0 | 3 |\n| 4 |  | Professional Elective- I | 3 | 0 | 0 | 3 |\n| 5 |  | Professional Elective- II | 3 | 0 | 0 | 3 |\n| 6 | DS504PC | R Programming Lab | 0 | 0 | 2 | 1 |\n| 7 | DS505PC | Computer Networks Lab | 0 | 0 | 2 | 1 |\n| 8 | EN508HS | Advanced English Communication Skills Lab | 0 | 0 | 2 | 1 |\n| 9 | DS506PC | ETL-Kafka/Talend | 0 | 0 | 2 | 1 |\n| 10 | *MC510 | Intellectual Property Rights | 3 | 0 | 0 | 0 |\n|  |  | Total | 18 | 1 | 08 | 20 |\n\n\n| S. No. | Course\u003Cbr>Code | Course Title | L | T |  | P | Credits |\n| --- | --- | --- | -","cbCaieTAhNEeVuFG","https://ap.wps.com/l/cbCaieTAhNEeVuFG","pdf",1819875,147,"English","# Semester-wise Course List\n## Theory Courses\n## Laboratory Courses\n## Professional Electives\n## Open Electives\n## Projects and Internship","[{\"question\":\"What types of courses are included in this B.Tech CSE (Data Science) course structure?\",\"answer\":\"The structure includes theory courses, lab courses, professional electives, open electives, and project stages/internship or skill development courses.\"},{\"question\":\"Which advanced Data Science subjects appear in the curriculum?\",\"answer\":\"It includes subjects such as Introduction to Data Science, Machine Learning, Big Data Analytics, ETL-Kafka/Talend, Predictive Analytics, and Web and Social Media Analytics, along with corresponding lab components.\"},{\"question\":\"How is the curriculum organized across semesters?\",\"answer\":\"The document presents semester-wise course tables, showing course codes/titles and the L-T-P components with credits for each semester.\"}]","R22 B.Tech CSE (Data Science) Course Structure Syllabus 2 | PDF",51]