Department of Computer Science and Engineering (Artificial Intelligence & Machine Learning): Where Machines Learn
At Sri Harshini College of Engineering and Technology for Women, our CSE (Artificial Intelligence & Machine Learning) department empowers women technologists with deep expertise in machine learning, deep learning, and AI-driven systems. We combine strong foundations in computer science with specialized training in ML algorithms, neural networks, natural language processing, and computer vision, preparing students to design and deploy intelligent solutions for industry and society.
Why Choose CSE-AI&ML at Sri Harshini?
Our CSE-AI&ML program offers a focused curriculum on advanced machine learning algorithms, deep learning architectures, reinforcement learning, and AI applications. Students work in labs equipped with GPUs and modern ML frameworks, gaining hands-on experience in building and deploying models for classification, prediction, and intelligent automation.
We emphasize project-based learning through real-world datasets, Kaggle-style competitions, and research projects in collaboration with our ML and AI labs. Students develop portfolios in areas such as computer vision, natural language processing, recommendation systems, and predictive analytics. Strong industry partnerships provide internships and placement opportunities in roles such as ML engineer, AI researcher, and data scientist.
With a commitment to women’s leadership in AI and ML, we nurture not only technical depth but also problem formulation, model interpretability, and ethical AI practices. Our graduates are prepared to excel in sectors ranging from autonomous systems and healthcare AI to fintech and smart applications.
Vision & Mission
VISION
To emerge as a center of excellence in Artificial Intelligence and Machine Learning, empowering women graduates with strong technical and analytical skills, ethical values, innovative thinking, and lifelong learning abilities to design and deploy intelligent solutions for industry, research, and societal advancement.
MISSION
- To provide strong theoretical knowledge and practical skills in Artificial Intelligence, Machine Learning, and core computer science through quality teaching and modern learning resources.
- To encourage innovation, problem solving, and continuous learning by engaging students in projects, research activities, and emerging AI and ML technologies.
- To prepare women students for successful careers and higher studies by nurturing professional competence, ethical values, and social responsibility.
PO’s (Program Outcomes)
- PO1 — Engineering Knowledge: 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 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 to meet specified needs considering public health, safety, cultural, societal, and environmental aspects.
- PO4 — Conduct Investigations of Complex Problems: Use research-based knowledge and research methods including design of experiments, analysis, and interpretation of data to provide valid conclusions.
- PO5 — Modern Tool Usage: Create, select, and apply appropriate techniques, resources, and modern engineering and IT tools to complex engineering activities, with an understanding of their limitations.
- PO6 — The Engineer and Society: Apply reasoning informed by contextual knowledge to assess societal, health, safety, legal, and cultural issues relevant to professional engineering practice.
- PO7 — Environment and Sustainability: Understand the impact of professional engineering solutions in societal and environmental contexts and demonstrate knowledge of and need for sustainable development.
- PO8 — Ethics: Apply ethical principles and commit to professional ethics and responsibilities and norms of 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 society at large, including writing reports, design documentation, making presentations, and giving/receiving clear instructions.
- PO11 — Project Management and Finance: Demonstrate knowledge and understanding of engineering and management principles and apply these to one’s 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.
PEO’s (Program Educational Objectives)
- PEO1: Graduates will apply principles of Artificial Intelligence, Machine Learning, and computer science to analyze, design, and develop intelligent solutions for real-world problems.
- PEO2: Graduates will pursue successful careers in industry, higher education, research, or entrepreneurship by continuously upgrading their technical and analytical skills.
- PEO3: Graduates will demonstrate ethical conduct, teamwork, leadership qualities, and social responsibility while contributing to technological innovation and societal development.
PSO’s (Program Specific Outcomes)
- PSO1: Ability to design, implement, and evaluate intelligent systems using machine learning algorithms, data analytics, programming tools, and modern computing platforms.
- PSO2: Ability to apply AI and ML techniques such as deep learning, natural language processing, computer vision, and predictive analytics to solve industry-oriented and societal problems.
Faculty List
| Name of the Faculty | Designation |
|---|---|
| Dr. Sudhir Chakravarthy.K | Professor |
| Rajakumar Amara | Associate Professor |
| Jagannadham Jhansi Rani | Assistant Professor |
| Deepika Soni | Assistant Professor |
| Pavan Kumar Punugoti | Assistant Professor |
| Lingathopti Ravi Chandra | Associate Professor |
Syllabus
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Exam Notification
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Previous Question Papers
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