Undergraduate

CSE Machine Learning Department

Welcome to the forefront of technology in Computer Science and Engineering with a specialization in Machine Learning. Our department is dedicated to advancing machine learning technologies, fostering innovation, and preparing the next generation of tech leaders.

About Us

Established in the academic year 2024, our Department of CSE Machine Learning offers a 4-year undergraduate program with an annual intake of 60 students. The faculty members of the department have global experience and training. The departmental research is focused in the areas of Artificial Intelligence, Parallel Processing, Software Engineering, Image Processing, and Computer Vision, Medical Image Processing, Pattern Recognition, Data mining and Web mining, Biometrics, Natural Language Processing (NLP), Machine Learning, and Information Extraction. The department has all the facilities to carry out the related teaching and research work. The Department enthusiastically supports and initiatives students to create intellectual communities that extend beyond the classroom, and we encourage students at all levels to take advantage of the programs offered at the global level.

Scopes of Machine Learning:

1. Healthcare

1. Disease Diagnosis and Prediction: ML models analyze medical images, genetic data, and patient history to diagnose diseases like cancer and predict the likelihood of disease occurrence.
2. Personalized Medicine: Tailoring treatments based on individual patient data and predicting the effectiveness of treatments.
3. Drug Discovery: Accelerating the process of discovering new drugs by predicting molecular behavior and potential outcomes

2. Finance

1. Fraud Detection: Identifying fraudulent transactions and activities by analyzing patterns and anomalies in financial data.
2. Algorithmic Trading: Developing models that can make high-frequency trading decisions.
3. Risk Management: Assessing the risk associated with loans and investments by analyzing historical data and trends.

3. Marketing and Sales

1. Customer Segmentation: Grouping customers based on behaviors and preferences to target marketing efforts more effectively.
2. Recommendation Systems: Suggesting products or services to customers based on their past behavior and preferences (e.g., Netflix, Amazon).
3. Sentiment Analysis: Analyzing customer reviews and social media to gauge public opinion about products or brands.

4. Manufacturing and Supply Chain

1. Predictive Maintenance: Predicting equipment failures before they occur to minimize downtime and maintenance costs.
2. Quality Control: Using computer vision and other techniques to detect defects in manufacturing processes.
3. Supply Chain Optimization: Enhancing inventory management, demand forecasting, and logistics.

5. Transportation

1. Autonomous Vehicles: Developing self-driving cars and drones that can navigate and make decisions without human intervention.
2. Traffic Prediction: Analyzing traffic patterns to optimize routes and reduce congestion.
3. Fleet Management: Optimizing the operation and maintenance of vehicle fleets.

6. Retail

1. Inventory Management: Predicting product demand to maintain optimal stock levels.
2. Dynamic Pricing: Adjusting prices in real-time based on demand, competition, and other factors.
3. Customer Experience: Enhancing in-store experiences using ML-powered chatbots and personalized recommendations.

7. Energy

1. Energy Consumption Forecasting: Predicting energy usage patterns to optimize energy distribution and reduce waste.
2. Smart Grids: Managing and distributing energy more efficiently using ML algorithms.
3. Renewable Energy: Improving the efficiency of renewable energy sources through predictive maintenance and optimization.

8. Agriculture

1. Precision Farming: Using ML to analyze soil data, weather patterns, and crop health to optimize farming practices.
2. Yield Prediction: Predicting crop yields based on various environmental factors and historical data.
3. Pest Detection: Identifying pest infestations early through image recognition and other ML techniques.

9. Education

1. Personalized Learning: Tailoring educational content and methods to individual student needs and learning styles.
2. Performance Prediction: Predicting student performance and identifying those at risk of falling behind.
3. Administrative Efficiency: Streamlining administrative tasks and improving resource allocation.

10. Entertainment

1. Content Creation: Generating music, art, and literature using machine learning algorithms.
2. Game Development: Enhancing game AI to create more immersive and challenging gaming experiences.
3. Audience Analysis: Understanding viewer preferences and optimizing content delivery.

VISION

To be among the best programs in Machine Learning , generating Software & IT Professionals, along with various skills like proper attitude, Techincal skills, Knowledge, ethics and to become a renowned center for the genesis of creative ideas and solutions.

MISSION

1. To provide distinctive and relevant education within scientific and professional environment.
2. To develop curricula that are holistic, flexible and dynamic in design so as to nurture heightened cognitive abilities leading to creativity and innovation.
3. To dispense quality knowledge and practical skills, to achieve excellence in education and create technologically competent manpower for the global institutions.
4. To give impetus to creative minds to transform society through innovation, design and to build entrepreneurship, leadership and to facilitate concerted action.

PROGRAM OUTCOMES (POs)

Engineering Graduates will be able to:

1. 1. Engineering knowledge: Apply the knowledge of mathematics, science, engineering fundamentals and an engineering specialization to the solution engineering problems.
2. 2. Problem analysis: Identify , formulate,review research literature and analyze complex engineering problem reaching substantiated conclusion using first principles of mathematics , natural science and engineering sciences.
3. 3. 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 the public health and safety and the cultural,society and environmental considerations.
4. 4. 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.
5. 5. Modern tool usage: Create, select and apply appropriate techniques, resources and modern engineering and IT tools including prediction and modeling to complex engineering activities with an understanding of the limitations.
6. 6. 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.
7. 7. Environment and sustainability: Understand the impact of the professional engineering solutions in societal environmental contexts and demonstrate the knowledge of and need for sustainable development.
8. 8. Ethics: Apply ethical principles and commit to professional ethics and responsibility and norms of the engineering practice.
9. 9. Individual and team work: Function effectively as an individual and as a member or leaded in diverse teams and in multidisciplinary setting.
10. 10. 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 presentation and give and receive clear instructions.
11. 11. Project management and finance: Demonstrate knowledge and understanding of the engineering and management principles and apply these to one's own work as amember and leader in a team to manage projects and multidisciplinary environments.
12. 12. 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.

PROGRAMME SPECIFIC OUTCOMES (PSOs)

After completion of this programme students will be able to attain.

1. PSO 1: Demonstrate basic knowledge of computer applications and apply standardized practices to software project development.
2. PSO 2: Apply the fundamental knowledge of computer science, analyze the real time problems and provide the computer based solutions.
3. PSO 3: Design effective systems and models for real time applications using the data structure, programming languages, machine learning, artificial intelligence models and networks.

PROGRAMME EDUCATIONAL OBJECTIVES (PEOs)

1. PEO 1: To be able to understand and analyze computer science and engineering problems and relate them to real life.
2. PEO 2: To impart in-depth knowledge of computer science and engineering to meet industrial needs, undertake and excel in graduate studies and innovation in related areas of engineering.
3. PEO 3: Promote collaborative learning and teamwork through multidisciplinary projects and a diverse professional ethics with an inclination for higher studies and research.
4. PEO 4: To inculcate a conviction to believe in self, impart professional and ethical attitude and nurture to be an effective team member, infuse leadership qualities, and build proficiency in soft skills and the abilities to relate engineering with the social, political and technical issues.

Engineering at RITEE USP's

1. First & Only Engineering College in Chhattisgarh accredited with Grade A+ by NAAC
2. Experienced faculties
3. Exceptional Laboratory Setup
4. Huge collection of books in Library
5. 7 Specialization in M.Tech
6. 5 Research Centres for Ph.D
7. Only Engineering college in India to have a commercial Bio Diesel plant within the campus
8. Only Institute in Central India to have a BARC Centre
9. First Engineering college of state to adopt Solar Power
10. Many research work in progress
11. Entrepreneur Development Cell – The story of Suraj Kumar
12. Training Program
13. Industrial Relation
14. Amazing Placement record with highest package of 12 L per annum
15. Campus placement of companies like Samsung, LG Soft, Shapoorji Pallonji, Byju’s
16. About 45 companies visit every year