Global Institute of Engineering and Technology (GIT)

About the department

Department of Artificial Intelligence and Data Science, Global Institute of Engineering and Technology, facilitates the students to emphasize practical methods in statistics and data science, focusing on applications and computational aspects, rather than theory. We ensure to transform the students as a Data Analyst professional on completion of this programme. The students are well trained with relevant and conceptualized skills to become industry ready professionals.

The field of AI and DS is emerging as the most promising one for young engineers who have a flair for data and visualization.

To be a supreme centre of excellence in the field of electronics and communication by focusing research. Cater to the needs of nation who can address the changes in global scenario and to attain international repute by becoming a trend setter in the field.

  • To provide technical education that combines rigorous academic study and the excitement of innovation enabling the students to engage in lifelong learning.
  • To develop simple, appropriate and cost effective inclusive technologies which are instrumental in the upliftment of rural society.
  • To cultivate a well balanced portfolio of research of the highest quality with a wide range of interests.
  • Proactive and adaptive service systems that provide students with a flexible yet solid learning infrastructure.
    • This course is designed to prepare graduates who can conduct data-driven investigations, and visual & advanced analytics by acquiring and managing data of all types. 
    • Well qualified doctorate faculties in the field of Data Science with good research exposures are available to train the students to achieve their goals. 
    • The department is equipped with highly configured computer systems in the ratio of 1:1(Student:System).
    • The Labs facilitates database designing and management through dedicated tools such as MySQL, Python, R, Tensorflow, Tableau, Spark, Qlikview, DataRobot, Rapidminer.

    MODULE HIGHLIGHTS

    • The programme is designed to prepare students for the workforce by providing in-depth knowledge of basic and advanced probability and statistics, as well as rigorous practical skills in a variety of programming languages such as Python, R and C Programming.
    • This programme intends to prepare students for careers as data scientists and analysts by requiring them to complete a semester-long capstone project.
    • Expertising the students in latest technologies like Artificial Intelligence, Machine Learning, Deep Learning frameworks and Big data analytics where the students can apply their knowledge and skills to work on real-world data analytic projects.

     CAREER OPPORTUNITIES

    The goal of this degree programme is to prepare students for direct employment as

    • Data Analysts
    • DataBase Developer
    • AI Data Engineers
    • Interactive Visualizer
    • Big Data Engineer
    • Robotics Scientist
    • Database Developer or Data Scientists in business, industry or government organizations.
  • To equip students with essential background in computer science, basic electronics and applied mathematics.
  • To prepare students with fundamental knowledge in programming languages, and tools and enable them to develop applications.
  • To encourage the research abilities and innovative project development in the field of AI, ML,DL, networking, security, web development, Data Science and also emerging technologies for the cause of social benefit.
  • To develop professionally ethical individuals enhanced with analytical skills, communication skills and organizing ability to meet industry requirements.

       PROGRAMME OUTCOMES (POs)

Engineering Graduates will be able to,
  • PO1: Apply the knowledge of Mathematics, Science, Engineering fundamentals, and an engineering specialization to the solution of complex engineering problems.
  • PO2: 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.
  • PO3: 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.
  • PO4: 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..
  • PO5: 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.
  • PO6: 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.
  • PO7: 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.
  • PO8: Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of the engineering practice.
  • PO9: Individual and team work: Function effectively as an individual, and as a member or leader in diverse teams, and in multidisciplinary settings.
  • PO10: 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.
  • PO11: 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.
  • PO12: 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 (PSOs) A graduate of the Artificial Intelligence and Machine Learning Program will demonstrate
  • Foundation Skills: Ability to understand, analyze and develop computer programs in the areas related to algorithms, system software, web design, AI, machine learning, deep learning, data science, and networking for efficient design of computer-based systems of varying complexity. Familiarity and practical competence with a broad range of programming language, tools and open source platforms.
  • Problem-Solving Skills: Ability to apply mathematical methodologies to solve computational task, model real world problem using appropriate AI and ML algorithms. To understand the standard practices and strategies in project development, using open-ended programming environments to deliver a quality product.
  • Successful Progression: Ability to apply knowledge in various domains to identify research gaps and to provide solution to new ideas, inculcate passion towards higher studies, creating innovative career paths to be an entrepreneur and evolve as an ethically social responsible AI and ML professional.