Artificial Intelligence & Data Science

B.Tech in Artificial Intelligence & Data Science

B.Tech in Artificial Intelligence & Data Science

B.Tech in Artificial intelligence & Data Science is an under graduate programme offered by the department of AI & DS. The programme imparts knowledge on the basic principles of Artificial Intelligence & Data Science. The programme will foster students’ ability to apply the AI models and techniques on data to solve complex real world intelligence applications. Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data science practitioners apply machine learning algorithms to numbers, text, images, video, audio, and more to produce artificial intelligence (AI) systems to perform tasks that ordinarily require human intelligence. In turn, these systems generate insights which analysts and business users can translate into tangible business value. As the world is getting automated with various upcoming paradigms like Big data, Robotics, Internet of Things etc., bringing up artificial intelligence becomes inevitable. Autonomous devices, like robots, use machine learning approaches to combine algorithms with experiences. Aim of the programme is to equip the students with the knowledge on foundational principles, algorithms and learning techniques in the field of AI and Data Science. In future, students will be able to handle machine learning and automation tasks, which have wide application in the industry in terms of mechanical systems and data science. 

B.Tech in Artificial Intelligence & Data Science
B.Tech in Artificial Intelligence & Data Science
B.Tech in Artificial Intelligence & Data Science
B.Tech in Artificial Intelligence & Data Science

Opportunities

PEOs
PSOs
POs
PEO1

Graduates will be able to create sustainable AI models.

PEO2

Graduates will be able to implement AI responsibly in research development and technology transfer.

PEO3

Graduates will be able to deliver AI solutions for entrepreneurial activities leading to employment generation.

PSO1

Interpret high dimensional data for decision making systems.

PSO2

Develop computational models for system automation.

PO1

Engineering knowledge: Apply knowledge of mathematics, natural science, computing, engineering fundamentals and an engineering specialization as specified in WK1 to WK4 respectively 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 with consideration for sustainable development. (WK1 to WK4)

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. (WK5)

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. (WK8).

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. (WK2 and WK6)

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. (WK1, WK5, and WK7).

PO7

Ethics: Apply ethical principles and commit to professional ethics, human values, diversity and inclusion; adhere to national & international laws. (WK9)

PO8

Individual and Collaborative teamwork: 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. (WK8)

What you will learn

Core Courses

Advanced Machine Learning

Deep Learning Fundamentals

Artificial Intelligence Principles

Statistical Inference & Data Modelling

Big Data Systems

Computer Vision

Natural Language Processing

Reinforcement Learning

 

Labs & Projects

Machine Learning Lab

Deep Learning Lab

AI Algorithms Lab

Big Data Analytics Lab

Vision & NLP Lab

Capstone / Mini Project Lab

 

Electives

Pattern Recognition & Fuzzy Systems

Nature-Inspired Computing

Responsible AI & Fairness

AI for Cybersecurity

Advanced Computer Vision

Speech & Audio Processing

Predictive Analytics & Business Intelligence

Internet of Things (AI Applications in IoT)

Blockchain & Secure Data Systems

Cloud-Based AI Deployments

Syllabus / Curriculum

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