About the program

VMS CONSULTIX PRIVATE LIMITED is offering a researchfocused internship opportunity in the domain of Artificial Intelligence and Healthcare Analytics, aimed at students and aspiring researchers who are interested in applying advanced machine learning techniques to realworld medical problems. The objective of this internship is to design and develop an ensemble learningbased heart disease prediction system that leverages multiple publicly available and realworld datasets while integrating Explainable Artificial Intelligence XAI techniques to enhance transparency, trust, and interpretability of the predictions. Heart disease remains one of the leading causes of mortality worldwide, and accurate early prediction plays a crucial role in preventive healthcare. While traditional machine learning models have shown promising results, they often act as black boxes. This internship focuses on overcoming this limitation by combining multiple predictive models into an ensemble framework and applying explainability methods to understand and justify model decisions. During the internship, participants will work on data preprocessing and integration from multiple heart disease datasets, including handling missing values, normalization, feature engineering, and class imbalance. Interns will explore and implement various base learners such as Logistic Regression, Decision Trees, Random Forests, Support Vector Machines, and Gradient Boosting models. These models will be combined using ensemble strategies like bagging, boosting, and stacking to improve overall prediction performance. A key component of the internship is the application of Explainable AI techniques such as SHAP SHapley Additive exPlanations, LIME Local Interpretable ModelAgnostic Explanations, and feature importance analysis. Interns will analyze both global and local explanations to interpret how individual features contribute to predictions, making the model suitable for realworld clinical decision support systems. Participants will also perform model evaluation and comparison using standard metrics such as accuracy, precision, recall, F1score, ROCAUC, and confusion matrices across multiple datasets. Emphasis will be placed on validating model robustness and generalization capability. By the end of the internship, interns will gain handson experience in endtoend machine learning pipeline development, healthcare data analysis, ensemble modeling, and explainable AI. They will also develop strong research and problemsolving skills, with exposure to realworld challenges in AIdriven healthcare solutions. This internship is ideal for candidates looking to build a strong foundation in AI for healthcare, applied machine learning, and explainable systems, and for those aspiring to pursue higher studies, research publications, or industry roles in data science and artificial intelligence.

Perks

Industry-Recognized Internship Certificate from VMS CONSULTIX PRIVATE LIMITED upon successful completion Hands-on Experience with real-world healthcare datasets and advanced AI techniques Practical Exposure to ensemble learning, explainable AI (XAI), and model interpretability tools Mentorship from Industry and Research Experts in Artificial Intelligence and Data Science Research-Oriented Learning, suitable for students aiming for publications, higher studies, or PhD work Project-Based Learning with an end-to-end AI pipeline from data preprocessing to explainability Performance-Based Letter of Recommendation (LoR) for exceptional interns Opportunity to Work on Live Research Problems aligned with current industry and healthcare challenges Skill Enhancement in Python, Machine Learning, Healthcare Analytics, and Explainable AI Flexible Learning Environment with guided milestones and structured tasks Career Guidance & Technical Support throughout the internship period Opportunity for Future Collaboration / Advanced Projects with VMS CONSULTIX PRIVATE LIMITED

Who can apply?

Only those candidates can apply who:

1. are from B.Tech. / B.E./ Equivalent
2. and specialisation from Artifical Intelligence and Machine Learning,Artificial Intelligence and Data Science,Computer Science and Engineering,Computer Science and Technology,Machine Engineering
3. are available for duration of 2 Months
4. have relevant skills and interests

Terms of Engagement

Terms of Engagement This internship is offered purely for learning, training, and academic skill development purposes and does not constitute an offer of employment. Interns are expected to actively participate in all assigned tasks, project discussions, reviews, and evaluations during the internship period. The internship may be conducted in online / offline / hybrid mode, as decided by VMS CONSULTIX PRIVATE LIMITED, and interns must ensure availability as per the defined schedule. Interns are required to maintain strict confidentiality regarding datasets, project materials, internal discussions, methodologies, and any proprietary or sensitive information shared during the internship. All intellectual property (IP), including but not limited to code, models, documentation, reports, and research outcomes developed during the internship, shall remain the exclusive property of VMS CONSULTIX PRIVATE LIMITED, unless explicitly stated otherwise in writing. Interns must ensure that all work submitted is original, and any external resources, libraries, or references used must be properly acknowledged. The use of internship deliverables for academic submissions, portfolios, or publications is subject to prior written approval from VMS CONSULTIX PRIVATE LIMITED. Interns are expected to follow ethical AI practices, especially while working with healthcare data, ensuring responsible use, fairness, transparency, and compliance with applicable guidelines. VMS CONSULTIX PRIVATE LIMITED reserves the right to modify, suspend, or terminate the internship in cases of non-performance, misconduct, violation of policies, or breach of confidentiality. Certificates, recommendations, and completion letters will be issued only upon successful fulfillment of internship requirements and evaluation criteria. Any expenses related to internet, hardware, software setup, or personal resources shall be borne by the intern, unless explicitly stated otherwise. By accepting the internship, interns agree to comply with all organizational policies, guidelines, and timelines communicated during the program.

Number of openings

4