+ VISION
The department of Technology aims at being recognized globally as a pioneer in the field of emerging technologies and their applications to benefit society through innovation-based development.
+ MISSION
- To provide knowledge-based academic infrastructure to bridge the gap between academia and industry.
- To create a nurturing environment for lifelong learning through value-based education and enhance analytical skills through continuous improvement.
- To develop competent professionals with a visionary approach.
- To develop competent professionals in the emerging areas of artificial intelligence and data science.
+ PROGRAM EDUCATIONAL OBJECTIVES (PEOs)
- PEO1: In depth understanding of the fundamentals of Artificial Intelligence and Data Science and cultivate problem solving ability and analytical skills.
- PEO2: To facilitate the students with data analytics and machine learning skills and motivate them to solve complex real world problems using predictive and cognitive modelling.
- PEO3: To train the students with good communication, interpersonal and leadership skills to enable them to fulfill social and professional responsibilities.
- PEO4: Expose students to various contemporary issues which will enable them to become ethical and responsible towards society and work for the betterment of mankind
+ PROGRAM SPECIFIC OUTCOMES (PSO)
- PSO1: The graduates are proficient in fundamental principles and methods of Artificial Intelligence, Data Science and other related mathematical and scientific reasoning and are able to:
a) Apply fundamental concepts of advanced statistics, random variables, queuing theory, correlation and regression, and discrete mathematics.
b) Design, create & evaluate statistical models for decision making.
- PSO2: The graduates possess in-depth knowledge of various components of artificial intelligence and data science. The students have thorough understanding of:
a) Artificial Intelligence based systems and functionality of various units.
b) Role of data science in the benefit of society.
- PSO3: The graduates are competent in logic based programming languages and possess basic knowledge of several interactive data visualization software.
- PSO4: The graduates exhibit knowledge of best data mining practices and optimization techniques and can work as a team leader or member in developing expert systems.
- PSO5: The graduates possess the ability to explore emerging technologies and provide innovative solutions to real time problems within constraints such as financial, environmental, social and ethical.
** PROGRAM OUTCOMES (POs)**
- PO1: Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals, and their 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 public health and safety, as well as 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 modelling, to complex engineering activities with an understanding of their 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 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 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.
+ BRANCH BENEFITS
- Rajasthan's first AICTE approved college to offer Under Graduate course in Artificial Intelligence and Data Science.
- UpGrad and Cipher School as Knowledge Partner.
- Builds a solid foundation in futuristic technologies through an industry-oriented curriculum.
- Hands-on with industry projects and regular sessions by industry experts.
- Ability to design intelligent solutions in a variety of domains & business applications
- Hands-on experience Data Science components, tools & technologies.
- Gain expertise in advanced topics such as Business Intelligence, machine learning, Big Data analytics, Statistics, Mathematics, data mining, visual analytics, cognitive analytics, etc.
+ Career Path
Big Data Engineer are responsible for developing, constructing, testing, and maintaining frameworks like large-scale data processing systems and databases. In addition, they are trained to understand real-time data processing, offline data processing methods, and the implementation of large-scale machine learning.
- ** Business Intelligence Developer**
A business intelligence developer develops, deploy, and maintain Business Intelligence interfaces. These include query tools, data visualization and interactive dashboards, ad hoc reporting, and data modelling tools.
- ** Machine Learning Engineer**
Machine Learning Engineer focuses on researching, building and designing self-running Artificial Intelligence systems to automate predictive models. They develop and create the AI algorithms capable of learning and making predictions that define Machine Learning. Thus, we can say that they are responsible for creating programmes and algorithms that enable machines to take actions without being directed.
They are experts in multiple AI disciplines, including applied mathematics, machine learning, deep learning, and computational statistics. In addition, they have extensive knowledge and experience in computer perception, graphical models, reinforcement learning, and natural language processing.
AI Data Analyst builds analytical solutions and models by manipulating large data sets, integrating diverse data sources, performing ad-hoc analysis, developing reproducible analytical approaches to meet business requirements, and performing exploratory and targeted data analyses using descriptive statistics.
Robotics scientists are skilled professionals who are responsible for the research, design and development of robotics systems. They ensure robots are cost-effective, reliable, and safe and make sure robots perform their functions properly.
- ** Artificial Intelligence Engineer **
An artificial intelligence engineer works with traditional machine learning techniques like natural language processing and neural networks to build models that power AI-based applications. The type of applications created by AI engineers includes Contextual advertising based on sentiment analysis, Language translation, Visual identification or perception.
- ** Machine Learning Architect **
Machine Learning Architect is responsible for designing and developing Machine Learning use cases using appropriate ML Algorithms and Tools. They transform Business Requirements into working real-life applications with Machine Learning modules and use cases.
The AI architect is like the chief data scientist, responsible for planning the implementation of solutions using the right technologies and evaluating the evolution of the architecture as the clients' needs change.
- ** Data and AI Consultant**
Data and AI Consultant translate business requirements into technical requirements. They craft high-level and detailed design documents, implement innovative solutions using the most recent technologies, and implement large data platform, business intelligence, advanced analytics, and multi-tier type solutions.
An IoT architect sorts through all the data transmitted between networks from the various machines and gadgets used every day by millions of people. IoT architects help organizations fix business problems by designing IoT solutions. They are also responsible for creating and communicating the IoT concept, message, and architecture.
+ CURRICULUM
- Courses are skill-based and Industry Oriented
- Immense Domain Exposure
- Multidisciplinary Application Knowledge
- Major Thrust on Hands-on Training
- Involving stakeholders in the practices of curriculum design
- Courses for Holistic Development
- Latest technology skill development