PSN Institute of Technology and Science

Artificial Intelligence and Data Science is a new branch of study that deals with scientific methodologies, processes, and techniques drawn from different domains like statistics, cognitive science, and computing and information science to extract knowledge from structured data and unstructured data. This knowledge is applied in making various intelligent decisions in business applications. Artificial Intelligence and data science engineering colleges in Bangalore focus on collecting, categorizing, strategizing, analyzing and interpreting data. It is a specialised branch that deals with the development of data-driven solutions, data visualization tools and techniques to analyse big data. It also incorporates the concepts of machine learning and deep learning model building for solving various computational and real-world problems.

As the demand for Artificial Intelligence and Data Science is rapidly increasing, so job opportunities are also increasing day by day.

After pursuing B.Tech in AI, a lot of career opportunities or scope are there in the field of business, telecommunication, e-commerce, healthcare, climatology, social networking companies, biotechnology, genetics, Research and Development, IT industry, and IT-enabled service industries, banking, government agencies, insurance, aerospace, etc.
Students can even opt to go for higher education in Artificial Intelligence and Data Science after completing their graduation. Some students even opt to prepare for competitive exams.
Lastly, it can be said that graduates in B.Tech AI have a very bright career in the future.

Lab

Vision

To achieve excellent standards of quality-education by using the latest tools, nurturing collaborative culture and disseminating customer oriented innovations to relevant areas of academia and industry towards serving the greater cause of society.

Mission

To develop professionals who are skilled in the area of Artificial Intelligence and Data Science.
To impart quality and value based education and contribute towards the innovation of computing, expert system, Data Science to raise satisfaction level of all stakeholders.
Our effort is to apply new advancements in high performance computing hardware and software.

I. Program Educational Objectives (PEOs)

Graduates can

Utilize their proficiencies in the fundamental knowledge of basic sciences, mathematics, Artificial Intelligence, data science and statistics to build systems that require management and analysis of large volumes of data.
Advance their technical skills to pursue pioneering research in the field of AI and Data Science and create disruptive and sustainable solutions for the welfare of ecosystems.
Think logically, pursue lifelong learning and collaborate with an ethical attitude in a multidisciplinary team.
Design and model AI based solutions to critical problem domains in the real world.
Exhibit innovative thoughts and creative ideas for effective contribution towards economy building.

II. Program Outcomes (POs)

Graduate Attribute

Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
Problem analysis: Identify, formulate, review research literature, and analyze complex engineering problems reaching substantiated conclusions using first principles of mathematics, natural sciences, and engineering sciences.
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.
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.
Modern tool usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
The engineer and society: Apply reasoning informed by the contextual knowledge to assess societal, health, safety, legal and cultural issues and the consequent responsibilities relevant to the professional engineering practice.
Environment and sustainability: Understand the impact of the professional engineering solutions in societal and environmental contexts, and demonstrate the knowledge of, and need for sustainable development.
Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
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.
Project management and finance: Demonstrate knowledge and 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.
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.

III. Program Sepcific Outcomes (PSOs)

Graduates should be able to:

Evolve AI based efficient domain specific processes for effective decision making in several domains such as business and governance domains.
Arrive at actionable Foresight, Insight, hindsight from data for solving business and engineering problems.
Create, select and apply the theoretical knowledge of AI and Data Analytics along with practical industrial tools and techniques to manage and solve wicked societal problems.
Develop data analytics and data visualization skills, skills pertaining to knowledge acquisition, knowledge representation and knowledge engineering, and hence be capable of coordinating complex projects.
Able to carry out fundamental research to cater the critical needs of the society through cutting edge technologies of AI.