About the Competition: The Bharat Academix AI & Machine Learning opportunity is a national-level competition designed to identify, evaluate, and recruit talented students and fresh graduates for the Bharat Academix AI & Machine Learning Internship Program 2026. Participants will solve a real-world Artificial Intelligence and Machine Learning problem by building an end-to-end AI solution using appropriate tools, algorithms, and technologies. This hackathon provides an opportunity to demonstrate technical expertise, analytical thinking, and problem-solving skills while gaining valuable industry experience. Selection Process: Round 1: Registration & Initial Screening Participants must register through the Unstop platform by completing their profile and submitting the required details. Applications will be shortlisted based on: Resume/Profile Academic Background Technical Skills Python & AI/ML Knowledge Relevant Projects or Certifications (if available) Interest in Artificial Intelligence and Machine Learning Duration: Registration period as announced. Only shortlisted participants will qualify for Round 2. Round 2: AI & Machine Learning Project Challenge Shortlisted participants will receive one real-world AI/ML problem statement along with the required dataset (or instructions to use a public dataset). Participants are required to build and submit a complete Machine Learning solution that includes: Data Collection (if required) Data Cleaning & Preprocessing Exploratory Data Analysis (EDA) Feature Engineering Model Selection & Training Model Evaluation Performance Optimization Result Interpretation Submission Requirements: Source Code (GitHub Repository) Jupyter Notebook (.ipynb) Project Report README File Presentation (PPT/PDF) Trained Model Files (if applicable) Demo Video (Optional) Duration: 5–7 days (as communicated after shortlisting). Only the highest-performing participants will advance to the final round. Round 3: Final Project Presentation & Jury Evaluation Finalists will present their AI/ML solution before a panel of Bharat Academix mentors and industry experts. Each participant will: Present the problem statement Explain data preprocessing and methodology Demonstrate the working model Discuss algorithms and technologies used Present evaluation metrics and results Explain challenges faced and solutions implemented Answer technical questions from the jury Presentation Duration: 10–15 minutes Question & Answer Session: 5–10 minutes The jury's decision will be final. Evaluation Criteria: Projects will be evaluated based on: Problem Understanding Data Preprocessing Feature Engineering Model Selection Model Accuracy & Performance Innovation Code Quality Documentation Presentation Skills Technical Knowledge Problem-Solving Ability Internship Benefits: Internship Offer Letter Hands-on AI & Machine Learning Projects Mentorship from Industry Professionals Internship Completion Certificate Performance-Based Letter of Recommendation (LOR) Career Development Support Networking Opportunities Pre-Placement Interview (PPI) for Outstanding Performers Rules: Individual participation only. Each participant may submit only one project. The project must be original work developed during the hackathon period. Public datasets and open-source libraries may be used with proper attribution. Plagiarism, copied code, or unauthorized use of AI-generated solutions without understanding may lead to disqualification. All submissions must be made before the deadline through the prescribed submission portal. Participants must submit all required deliverables, including source code, documentation, and presentation. Bharat Academix reserves the right to modify the schedule, evaluation process, or rules if necessary. The decision of the jury and organizing committee will be final and binding. We welcome passionate learners, innovators, and future AI engineers to participate in the Bharat Academix AI & Machine Learning Internship Hackathon 2026. Showcase your skills, solve real-world challenges, and take the first step toward your AI career with Bharat Academix.