The Artificial Intelligence and Data Science Program teaches students how to do intelligent data analysis, which is a critical component in many real-world applications. Data science has evolved as one of the most high-growth, dynamic, and profitable jobs in technology during the last 10 years.
This course intends to provide not only basic technologies like artificial intelligence, data mining, and data modelling, but also extensive inputs in machine learning and big data analytics. Students will gain cross-disciplinary skills in fields such as statistics, computer science, machine learning, and logic, as well as data scientists, and may have career opportunities in healthcare, business, eCommerce, social networking companies, climatology, biotechnology, genetics, and other important areas as a result of taking this course.
The primary goal of this curriculum is to provide students with abilities in statistical reasoning, mathematical reasoning, machine learning, knowledge discovery, and visualisation.
To produce globally competent graduates in Artificial Intelligence and Data Science through value-based technical education to outperform in the vibrant computing world and adapt to life-long learning.
MD1: MD1. Creating technocrats with strong core competencies in the field of Artificial Intelligence and Data Science which serve as the foundation for career.
MD2: MD2. Providing the best practical experience and innovative concepts which help them to solve societal issues in ethical manner.
MD3:MD3. Providing the value based technical education to specialize in the field of Artificial Intelligence and Data Science
PEO1: 1. Graduates will establish themselves as effective computer professionals by solving real world problems using cutting edge technologies in Artificial Intelligence and Data Science.
PEO2: 2. Graduates will be inculcated with professional and ethical attitude, team work, effective communication, multi-disciplinary approach with an ability to relate computer engineering issues with social awareness.
PEO3: 3. Graduates will actively pursue graduate studies in advanced areas of Artificial Intelligence, Data Science and related fields by succeeding in competitive exams.
PSO 1: Ability to understand and analyze the real world computational problems and to develop solutions by applying mathematical logic, appropriate data structures and algorithms.
PSO 2: Ability to become a successful software engineer by creating and using modern IT tools.
PSO 3: Graduate will have communication and leadership skills to endure themselves working as a member or managing a team.
At the time of graduation, the students of B.Tech.- Artificial Intelligence and Data Science should have the
PO1: ENGINEERING KNOWLEDGE: Ability to apply knowledge of mathematics, Science and Engineering applicable to Computer Science and Engineering discipline.
PO2: PROBLEM ANALYSIS: Ability to analyze and develop solutions to computational problems using appropriate algorithms.
PO3: DESIGN /DEVELOPMENT: Ability to design, implement and evaluate a computational system to meet desired needs within realistic constraints such as economic, environmental, social, ethical, health and safety, manufacturability and sustainability.
PO4: CONDUCT INVESTIGATIONS OF COMPLEX PROBLEMS: Ability to apply design and development principles in the construction of software systems of varying complexity and perform testing.
PO5: MODERN TOOL USAGE: Ability to use appropriate techniques, skills, and modern tools to produce quality software products and solutions using Software Engineering principles.
PO6: THE ENGINEER AND SOCIETY: Ability to develop innovative ideas that can be translated into products benefiting the society and the economic growth.
PO7: ENVIRONMENT & SUSTAINABILITY: Ability to assess the impact of engineering practices on societal and environmental sustainability.
PO8: ETHICS: Ability to understand and apply professional, ethical, security, social issues and responsibilities for the computing profession.
PO9: INDIVIDUAL AND TEAM WORK: Ability to function effectively as individuals and as a member of a team to share computing design, assessment or implementation of a common goal.
PO10: COMMUNICATION: Ability to communicate, write effective reports, design documentation and make effective presentations.
PO11: PROJECT MANAGEMENT AND FINANCE: Ability to work with good engineering and managerial skills and teamwork for successful completion of projects.
PO12: LIFE LONG LEARNING: Ability to recognize the need and an ability to engage in life-long learning.
The Machine Learning Laboratory was established to address one of science's most pressing questions: how can we harness the mechanics of intelligence to enhance the world around us? Machine learning illuminates the solution by converting data into a mathematical blueprint that can be used to automate difficult, high-value cognitive operations. This blueprint has had a significant impact on our capacity to duplicate human skills like language comprehension and eyesight.
In a collaborative, multidisciplinary atmosphere, the Data Visualization Lab delivers visualisation solutions for a wide range of data sets. This lab aids with the setup and consulting of visualisation infrastructure, as well as visualisation training, workshops, and support. It investigates innovative visualisation technologies such as 3D virtual worlds, interactive data visualisation, visual analytics, information and scientific visualisation, and seeks grant opportunities to increase visualisation capacity and applications.
The Data Science Laboratory seeks to examine and analyse the massive amounts of data created by electronic devices and the digital world on a daily basis. The people who are the generating centre through their interaction with the digital world and the new digitised physical environment that surrounds us (IoT) are the main element in the generation of all this data, causing the amount of data that is being and will continue to be generated to grow exponentially. The Data Science Lab's goal in this context is to comprehend and model all of this huge quantity of data by personalising our settings, developing new ways of human-machine interaction, and increasing our quality of life in a sustainable manner.