Eligibility Norms for Admission to B. Tech Programs:
Passed 10+2 examination with Physics/ Mathematics Compulsory along with Chemistry/ Computer Science/ Electronics/ Information Technology/ Biology/ Informatics Practices/ Biotechnology/ Technical Vocational subject/ Agriculture/ Engineering Graphics/ Business Studies Obtained at least 45% marks (40% marks in case of candidates belonging to reserved category) in the above subjects taken together.
Eligibility Norms for Admission to B. Tech Programs (Lateral):
Passed Minimum THREE years / TWO years (Lateral Entry) Diploma examination with at least 45% marks (40% marks in case of candidates belonging to reserved category) in relevant branch of Engineering and Technology as mentioned in the AICTE APH 2024-25. OR Passed B.Sc. Degree from a recognized University as defined by UGC, with at least 45% marks (40% marks in case of candidates belonging to reserved category) and passed 10+2 examination with Mathematics as a subject. OR Passed B.Voc/3-year D.Voc. Stream in the same or allied sector. (The Universities will offer suitable bridge courses such as Mathematics, Physics, Engineering drawing, etc., for the students coming from diverse backgrounds to achieve desired learning outcomes of the programme)
The program is designed to meet the increasing need for highly skilled data analysts who can analyze the growing amount of data confronting them in a variety of disciplines and transform it into usable information for use in decision-making. The program delivers rigorous training in computational techniques and provides mastery of data analysis. Developing skills in solution development, database design (both SQL and NoSQL), data processing, data warehousing and data visualization help build a solid foundation to support the role of a business analyst.
Programme Overview
The program is designed to meet the increasing need for highly skilled data analysts who can analyze the growing amount of data confronting them in a variety of disciplines and transform it into usable information for use in decision-making. The program delivers rigorous training in computational techniques and provides mastery of data analysis. Developing skills in solution development, database design (both SQL and NoSQL), data processing, data warehousing, and data visualization helps build a solid foundation to support the role of a business analyst.
Course Curriculum
01Calculus and Differential Equations - MAT2301
02English for Technical Communication - ENG1900
03Optoelectronics and Quantum Physics - PHY2501
04Optoelectronics and Quantum Physics Lab - PHY2504
05Engineering Graphics - MEC1006
06Digital Design - ECE2022
07Digital Design Lab - ECE2052
08Introduction to Design Thinking - DES1146
09Computational Thinking using Python - CSE1500
10Industry Readiness Program – I - PPS1025
01Calculus and Differential Equations - MAT2301
02English for Technical Communication - ENG1900
03Chemistry of Smart Materials - CHE2501
04Chemistry of Smart Materials Lab - CHE2502
05Foundations of Integrated Engineering - CIV1200
06Basics of Electrical and Electronics Engineering - EEE1200
07Basics of Electrical and Electronics Engineering Lab - EEE1250
08Indian Constitution - LAW7601
09Computational Thinking using Python - CSE1500
10Industry Readiness Program – I - PPS1025
01Linear Algebra and Vector Calculus - MAT2303
02Data Communication and Computer Networks - CSE2051
03Data Communication and Computer Networks Lab - CSE2052
04Data Structures - CSE2053
05Data Structures Lab - CSE2054
06Object Oriented Programming Using Java - CSE2055
07Object Oriented Programming Using Java Lab - CSE2056
08Computer Organization and Architecture - CSE2057
09Introduction to Big Data - CBD2000
10Software Design and Development - CSE2071
11Universal Human Values and Ethics - CIV7601
12Introduction to Aptitude - APT4002
01Discrete Mathematics - MAT2404
02Database Management Systems - CSE2060
03Database Management Systems Lab - CSE2061
04Data Visualization and Reporting - CBD2502
05Data Visualization and Reporting Lab - CBD2503
06Analysis of Algorithms - CSE2062
07Analysis of Algorithms Lab - CSE2063
08Essentials of AI - CSE2064
09Essentials of AI Lab - CSE2065
10Essentials of Finance - FIN1002
11Aptitude Training – Intermediate - APT4004
01Theory of Computation - CSE2066
02Web Technologies - CSE2058
03Web Technologies Lab - CSE2059
04Operating Systems - CSE2069
05Operating Systems Lab - CSE2070
06Data Mining and Predictive Analytics - CBD2506
07Data Mining and Predictive Analytics Lab - CBD2507
08Big Data Technologies - CBD2508
09Big Data Technologies Laboratory - CBD2509
10Professional Elective – I - CSEXXXX
11Internship - CSE7000
12Logical and Critical Thinking - APT4006
01No SQL Databases - CBD2510
02No SQL Databases Lab - CBD2511
03Web Intelligence and Analytics - CBD2512
04Web Intelligence and Analytics Lab - CBD2513
05Competitive Programming and Problem Solving - CSE2274
06Professional Elective – II - CSEXXXX
07Professional Elective – III - CSEXXXX
08Open Elective – I - XXXXXXX
09Aptitude for Employability - APT4005
01Professional Elective – IV - CSEXXXX
02Professional Elective – V - CSEXXXX
03Professional Elective – VI - CSEXXXX
04Open Elective – II - XXXXXXX
05Mini Project - CSE7100
06Preparedness for Interview - PPS3018
01Capstone Project – CSE7300
Programme Educational Objectives
After four years of successful completion of the program, the graduates shall be:
PEO 1: Graduates will demonstrate their knowledge in science and engineering as problem solvers and researchers.
PEO 2: Graduates will exhibit skills in cutting-edge technologies to solve societal needs in multidisciplinary areas.
PEO 3: Graduates will develop an attitude towards lifelong learning and ethics to emerge as socially committed entrepreneurs.
PEO 4: Graduates will develop as a freelancing consultant to the computer science and technology & Big Data Industry.
Programme Outcomes (POs)
On successful completion of the Program, the students shall be able to:
PO 1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
PO 2: Problem analysis: Identify, formulate, research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
PO 3: Design/development of solutions: Design solutions for complex engineering problems and design system components or processes that meet the specified needs with appropriate consideration for the public health and safety, and the cultural, societal, and environmental considerations.
PO 4: Conduct investigations of complex problems: Use research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.
PO 5: Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modelling to complex engineering activities with an understanding of the limitations.
PO 6: The engineer and society: Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal and cultural issues, and the consequent responsibilities relevant to professional engineering practice.
PO 7: Environment and sustainability: Understand the impact of professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
PO 8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of engineering practice.
PO 9: Individual and teamwork: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
PO 10: Communication: Communicate effectively on complex engineering activities with the engineering community and with society at large, such as, being able to comprehend and write effective reports and design documentation, make effective presentations, and give and receive clear instructions.
PO 11: Project management and finance: Demonstrate knowledge understanding of the engineering and management principles and apply these to one’s own work, as a member and leader in a team, to manage projects and in multidisciplinary environments.
PO 12: Life-long learning: Recognize the need for and have the preparation and ability to engage in independent and life-long learning in the broadest context of technological change.
Programme Specific Outcomes
On successful completion of the Program, the students shall be able to:
PSO 01: [Problem Analysis]: Identify, formulate, research literature, and analyse complex engineering problems related to Software Engineering principles & practice, Programming, Big Data computing & analytics, reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
PSO 02: [Design/development of Solutions]: Design solutions for complex engineering problems related to Software Engineering principles & practice, Programming, Big Data Computing & analytics, and design system components or processes that meet the specified needs with appropriate consideration for public health and safety, as well as cultural, societal, and environmental considerations.
PSO 03: [Modern Tools Usage]: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools, including prediction and modelling, to complex engineering activities related to Software Engineering principles & practice, Programming, Big Data Computing & analytics, with an understanding of the limitations.
Cutting-Edge Curriculum covering big data analytics, machine learning, AI, cloud computing, and data security.
Advanced Data Labs equipped with high-performance computing, Hadoop, Spark, and other big data technologies.
Industry-Experienced Faculty providing in-depth knowledge and hands-on training.
Practical Learning Approach through live projects, case studies, and real-world data analysis.
Global Internship & Study Abroad Opportunities for international exposure and career growth.
Strong Industry Collaborations with top tech firms for internships, certifications, and research projects.
Big Data & AI Certifications to enhance employability in high-demand fields.
Excellent Placement Records with top recruiters in data science, analytics, and AI-driven industries.
Career Opportunities
Core Big Data Roles
Big Data Engineer: Design, build, and maintain scalable data pipelines and infrastructure for large datasets using tools like Hadoop, Apache Spark, Kafka, and Hive.
Data Analyst: Perform exploratory data analysis and generate actionable insights using tools like SQL, Tableau, Power BI, and Python.
Data Scientist: Develop predictive models and apply machine learning techniques to extract insights from structured and unstructured data using tools like TensorFlow, R, and Scikit-learn.
Database Administrator: Manage and optimize databases for storing and querying large datasets using tools like MySQL, PostgreSQL, and MongoDB.
Industry-Specific Roles
Business Intelligence (BI) Analyst: Develop dashboards and reports to support business decision-making using tools like Tableau, Looker, and QlikView.
Healthcare Data Analyst: Analyze patient data for improved diagnosis, treatment planning, and resource optimization.
Retail Data Specialist: Work on customer segmentation, inventory optimization, and pricing strategies for e-commerce and retail companies.
Financial Data Analyst: Focus on fraud detection, risk assessment, and financial forecasting using big data.
Telecom Data Engineer: Manage and analyze massive data generated in telecommunications for optimizing networks and customer services.
Emerging and Specialized Roles
IoT Data Analyst: Analyze data from IoT devices in smart homes, cities, and industrial applications using tools like MQTT and Apache Flink.
Cloud Data Engineer: Manage cloud-based big data solutions for storage, processing, and analysis using platforms like AWS, Azure, and Google Cloud.
AI/ML Specialist in Big Data: Apply AI and machine learning techniques to big data for predictive and prescriptive analytics, focusing on recommendation engines and customer sentiment analysis.
Cybersecurity Analyst (Big Data Focus): Use big data tools to detect, prevent, and analyze cybersecurity threats with tools like Splunk and Elastic Stack.
Geospatial Data Analyst: Analyze spatial data for urban planning, environmental monitoring, and logistics using tools like GIS and Google Earth Engine.
Academic and Research Opportunities
Research Scientist in Big Data: Focus on innovative big data algorithms, optimization techniques, and distributed computing.
Lecturer/Professor: Teach big data technologies and mentor students in academic institutions.
Entrepreneurship
Big Data Startup Founder: Create solutions for industries like healthcare, finance, or e-commerce using big data technologies.
Your Next Move Awaits
Begin an extraordinary journey with Presidency University.
+91 9022092222
admission@presidencyuniversity.in
Rajanukunte, Yelahanka, Bengaluru, Karnataka, Pin: 560119, India
+91 9022092222