PEO/PSO/PO

PEO-I

Mathematical and Statistical Proficiency

Outcome: Graduates will develop a strong foundation in mathematics and statistics, enabling them to understand and apply complex algorithms and models in data science and AI.

PEO-II

Data Analysis and Interpretation Skills

Outcome: Students will acquire the ability to collect, process, and analyze large datasets, and draw meaningful insights to inform decision-making.

PEO-III

AI and Machine Learning Competence

Outcome: Graduates will gain expertise in AI and machine learning techniques, including the design, implementation, and evaluation of AI models.

PEO-IV

Programming and Software Development Skills

Outcome: Students will become proficient in programming languages and tools commonly used in data science and AI, such as Python, R, and TensorFlow, enabling them to develop and deploy AI applications.

PSO-I

Advanced Data Science and AI Proficiency:

· Master advanced techniques in data science and specialized AI sub-fields, including machine learning, deep learning, and natural language processing, to develop sophisticated data-driven solutions.

PSO-II

Data Mining and Real-time Analytics:

· Utilize Data Mining technologies and real-time data processing tools to handle large-scale datasets, ensuring efficient analysis and timely insights for decision-making.

PSO-III

Interdisciplinary and Ethical Application:

· Apply data science and AI methodologies to various domains, addressing ethical considerations, fairness, and transparency in AI development and deployment.

PSO-IV

 Innovation, Research, and Industry Collaboration:

· Drive innovation through research and development, engage in industry collaborations, and cultivate an entrepreneurial mindset to create impactful, data-driven solutions and ventures.

• Technical Knowledge and Skills

PO-1

Core Competency in Data Science:

• Demonstrate a comprehensive understanding of data science concepts, methodologies, and tools.
• Apply statistical methods, machine learning algorithms, and data mining techniques to analyze and interpret data.

PO-2

Proficiency in Artificial Intelligence:

• Understand and implement fundamental concepts of artificial intelligence, including neural networks, natural language processing, and computer vision.
• Develop and deploy AI models using appropriate frameworks and tools.

PO-3

Programming and Software Development:

• Write efficient, well-documented code in multiple programming languages (e.g., Python, R, SQL).
• Develop and manage software projects, including version control, debugging, and testing.

• Analytical and Problem-Solving Skills

PO-4

Critical Thinking and Problem-Solving:

• Analyze complex problems and identify appropriate data-driven solutions.
• Apply logical reasoning and critical thinking to interpret results and make informed decisions.

PO-5

Data Analysis and Visualization:

• Utilize data visualization tools and techniques to effectively communicate findings.
• Interpret and present data insights to both technical and non-technical audiences.

• Research and Innovation

PO-6

Research Skills:

• Conduct independent research and contribute to the body of knowledge in data science and AI.
• Stay updated with the latest trends and advancements in the field.

PO-7

Innovation and Creativity:

• Innovate new approaches and techniques in data science and AI.
• Apply creative problem-solving to develop novel solutions.

• Ethical and Social Responsibility

PO-8

Ethical Practices:

• Understand and adhere to ethical principles and standards in data handling, privacy, and AI applications.
• Evaluate the societal and ethical implications of data science and AI solutions.

PO-9

Social Responsibility:

• Recognize the impact of data science and AI on society and contribute to positive social change.
• Promote inclusive and equitable AI solutions.

• Communication and Teamwork

PO-10

Effective Communication:

• Communicate effectively in written, oral, and visual forms.
• Collaborate with multidisciplinary teams and stakeholders.

PO-11

Teamwork and Leadership:

• Work effectively in team settings, demonstrating leadership and collaborative skills.
• Manage projects and lead initiatives in data science and AI.

• Lifelong Learning

PO-12

Continuous Learning:

• Engage in lifelong learning and professional development.
• Adapt to new technologies and methodologies in the rapidly evolving fields of data science and AI.