PEO's,PSO's and PO's
Programme Educational Objectives (PEOs):
After a few years of graduation, the graduates of the B.C.A (AI and DS) programme will be able to:
- PEO1: Excel as competent AI and Data Science professionals by developing intelligent, data-driven solutions to real-world problems using modern computing technologies.
- PEO2: Build successful careers in AI, analytics, machine learning, cloud computing, and related domains, contributing to innovation and organizational growth.
- PEO3: Pursue higher education, professional certifications, research, and continuous learning to stay aligned with emerging trends in Artificial Intelligence, Big Data, and advanced analytics.
Programme Specific Outcomes (PSOs):
On successful completion of the programme, graduates will be able to:
- PSO1: Develop and deploy machine learning and deep learning models using modern programming frameworks and data science tools.
- PSO2: Apply data preprocessing, feature engineering, statistical modeling, and visualization techniques to extract actionable insights from structured and unstructured datasets.
- PSO3: Design intelligent applications integrating AI algorithms, big data technologies, and cloud platforms to support predictive and decision-making systems.
- PSO4: Implement ethical AI practices, ensuring fairness, transparency, security, and privacy in AI-driven applications.
Programme Outcomes (POs):
- PO1 – Disciplinary Knowledge - Demonstrate comprehensive knowledge of Artificial Intelligence, Machine Learning, Data Analytics, Statistics, Database Systems, and programming foundations relevant to AI and Data Science applications.
- PO2 – Scientific Reasoning - Apply logical reasoning, mathematical foundations, and statistical techniques to analyze data patterns, validate models, and derive meaningful insights.
- PO3 – Problem Solving - Design and implement AI-driven solutions, machine learning models, and data analytics systems to address complex computational and business problems.
- PO4 – Environment and Sustainability - Understand the societal, ethical, and environmental impact of AI technologies and promote responsible, sustainable, and inclusive AI solutions.
- PO5 – Research-related Skills - Analyze datasets, evaluate algorithms, interpret results, and draw evidence-based conclusions using scientific and data-driven approaches.
- PO6 – Ethics - Apply ethical AI principles, ensure data privacy, prevent algorithmic bias, and adhere to responsible data governance practices.
- PO7 – Cooperation / Teamwork - Work effectively in multidisciplinary teams to design, deploy, and maintain AI-based systems and data-driven applications.
- PO8 – Communication Skills - Communicate analytical findings, model interpretations, and AI-driven insights clearly through reports, visualizations, and presentations for technical and non-technical audiences.
- PO9 – Self-directed and Life-long Learning - Engage in continuous learning to adapt to rapidly evolving AI technologies, emerging tools, and industry advancements.
