Best Data Science College in Mangaluru – CSE (Data Science)

CET Code - E129 PGCET Code : MBA - B300 MCA -C484

CS Engineering in Data Science

Best College for CS Engineering in Data Science

Master the tools and technologies that transform data into data-driven decisions

Practical Learning in Data Science

Data science is not just about statistical methods; it is a modern way of simplifying complex things. Although most of them see a dataset SJEC, the best colleges for B.E in data science, students are taught to detect patterns, determine risks, and discover economic opportunities, to convert raw data into actionable insights and strategic decisions.

The programme is designed in a manner of closing the gap between abstract mathematics and real-world practice. We focus on the development of analytical thinking along with coding abilities, focusing on conceptual and technical accuracy. Graduates do not leave as technicians, but as strategic problem solvers who will be able to meet the demands of the data-driven industry, making SJEC one of the preferred B.E in Data Science colleges.

Facilities:

240

NUMBER OF STUDENTS

15

NUMBER FACULTY

07

NUMBER OF LABS

 
 

To impart value-based quality education with the motive of transforming mankind with excellence and competing areas of engineering, technology and management.

  • Focus on the practical aspects of the curriculum to make learning a meaningful and interesting experience.
  • Encourage active collaboration with industries, communities, and fellow institutions within the country and abroad.
  • Infuse strong moral and ethical principles in students in order to make them conscientious citizens and excellent human beings.
  • Cultivate the competitive spirit required for success.

  • PEO 1: To provide students with a solid foundation and the ability to use engineering concepts, mathematics, physics, and humanities required to develop, analyse, design, and implement solutions to the problems in intelligent computing and business systems.
  • PEO 2: To develop in students, the knowledge of computer science and engineering to work in domains such as artificial intelligence, machine learning and data science.
  • PEO 3: To foster in students, the capacity of teamwork through efficient communication in multidisciplinary projects.
  • PEO 4: To prepare students for building successful careers in artificial intelligence, data science and business systems to meet the needs of society while incorporating professional ethics.
  • PEO 5: To inspire learners to pursue higher education in their desired fields and engage in research.

Engineering Graduates will be able to:

  • PO1: Engineering Knowledge: Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization to develop to the solution of complex engineering problems.
  • PO2: Problem Analysis: Identify, formulate, review research literature and analyze complex engineering problems reaching substantiated conclusions using principles of mathematics, natural sciences and engineering sciences with consideration for sustainable development.
  • PO3: Design/Development of Solutions: Design creative solutions for complex engineering problems and design/develop systems/components/processes to meet identified needs with consideration for the public health and safety, whole-life cost, net zero carbon, culture, society and environment as required.
  • Ability to understand, analyze and communicate global, economic, legal, and ethical aspects of business
  • PO4: Conduct Investigations of Complex Problems: Conduct investigations of complex engineering problems using research-based knowledge including design of experiments, modelling, analysis & interpretation of data to provide valid conclusions.
  • PO5: Engineering Tool Usage: Create, select and apply appropriate techniques, resources and modern engineering & IT tools, including prediction and modelling recognizing their limitations to solve complex engineering problems.
  • PO6: The Engineer and The World: Analyze and evaluate societal and environmental aspects while solving complex engineering problems for its impact on sustainability with reference to economy, health, safety, legal framework, culture and environment.
  • PO7: Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws.
  • PO8: Individual and Collaborative Team work: Function effectively as an individual, and as a member or leader in diverse/multi-disciplinary teams.
  • PO9: Communication: Communicate effectively and inclusively within the engineering community and society at large, such as being able to comprehend and write effective reports and design documentation, make effective presentations considering cultural, language, and learning differences.
  • PO10: Project Management and Finance: Apply knowledge and understanding of engineering management principles and economic decision-making and apply these to one’s own work, as a member and leader in a team, and to manage projects and in multidisciplinary environments.
  • PO11: Life-Long Learning: Recognize the need for, and have the preparation and ability for  i) independent and life-long learning ii) adaptability to new and emerging technologies  and iii) critical thinking in the broadest context of technological change.

  • PSO 1: Entrepreneurship and Freelancing: Recognize the tenets of entrepreneurship, freelancing and the prerequisites for starting a business in the IT or related fields.
  • PSO 2: Competitive Exams: Participate skillfully in competitive examinations for certification, professional advancement, and admission to higher studies.

The Pillars of Expertise

We avoid generalised learning. Instead, we focus on the high-stakes domains that define the modern technical landscape

Robotics Systems Engineering
Automation & Control Systems
Smart Manufacturing & Industry 4.0
Mechatronics & Embedded Integration
Mechanical Design & Simulation
Sensors, Actuators & Intelligent Machine Systems

The Timeline

4 Years | 8 Semesters

The Requirement

  • We seek candidates with a strong foundation in Physics and Mathematics (10+2). Beyond the grades
  • Diploma pass with minimum 45% aggregate (5th & 6th sem) eligible for B.E. 3rd semester lateral entry; 40% for SC/ST/OBC Karnataka candidates
  • We look for analytical willingness to look at a problem until it is resolved.

Admission Process

Online Enquiry

Online Enquiry

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Entrance Examination

Entrance Examination

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Application Submission

Application Submission

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Counselling & Merit Selection

Counselling & Merit Selection

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Document Verification

Document Verification

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Fee Payment

Fee Payment

The Reasons to Select SJEC for Data Science

Why Is It Suitable for You?

The B.Tech programme in Data Science at SJEC, Mangaluru, places students at the core of the modern AI and data revolution. Being among the data science colleges in Mangaluru and reputed data science engineering colleges, SJEC offers a strong computing infrastructure whereby students learn to use predictive modelling techniques, analytics, and real-world data applications.

Effective Placement Opportunities

Our graduates are hired in leading corporations, such as Samsung, Amazon, and Cohesity, and they are paid salaries up to 24.5 LPA.

Research Exposure

Students have a chance to participate in data mining and intelligent system-related projects, hence making contributions to research activities and academic publications.

Updated Curriculum

The autonomous status of the institution allows revising the curriculum regularly and introducing new areas of knowledge to the curriculum, like blockchain and cloud computing.

Active Student Community

Students are involved in national hackathons and other technology events such as Google Cloud DevFest and FOSS United.

Our independent rule allows introducing the latest technologies like generative AI and cloud computing, which will keep students up-to-date in the industry

Testimonials

Feedback on Student Success

The Data Science programme offered by SJEC allows students to become confident professionals who are ready to work with technologies that will define the future.

Head of Department

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Dr Harivinod N

Professor & HOD

M.Sc, M.Tech, Ph.D

harivinodn@sjec.ac.in

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Frequently Asked Questions

Yes. Although the Data Science programme has similar foundations to Computer Science & Engineering (CSE), it enables students to major in Big Data, Machine Learning, and Statistical Modelling as early as the second year. This specialisation makes SJEC one of the sought-after Data Science B.E colleges.

The skills gained during this programme would equip graduates for jobs that are in demand, like Data Scientist, AI Engineer, Big Data Architect, and Business Intelligence Developer. Students from B.E in Data Science and Engineering colleges like SJEC are highly valued across industries.

Absolutely. The curriculum will include practical labs in Deep Learning, Data Visualisation, and Natural Language Processing (NLP), which will guarantee that students acquire practical experience with the industry-standard tools.

SJEC, which is recognised as one of the best colleges for B.E in data science, has a specific Campus to Corporate training to enable the students to get high package placements. Technical interviews, soft skills, and competitive coding are provided to students to ensure that they are as employable as possible.

Yes. The curriculum will focus on business applications, and Business Intelligence and Project Management are integrated in a way that enables students to implement their technical knowledge in the business environment.