MACHINE LEARNING INTERN

About the program The Machine Learning Internship is designed for students and recent graduates who want to develop practical skills in data driven application development and intelligent systems. This virtual internship provides hands on experience in designing building and evaluating machine learning models using real world datasets. During the internship interns will learn Python data preprocessing feature engineering supervised learning unsupervised learning model evaluation and deployment techniques. They will work with popular libraries including Scikit Learn TensorFlow PyTorch Pandas and NumPy while building practical projects such as recommendation systems prediction models classification systems and data analysis applications. Participants will receive guidance from experienced mentors through technical training project reviews and collaborative learning sessions. The internship encourages analytical thinking problem solving teamwork and software development best practices while providing exposure to industry workflows and version control. By the end of the internship interns will have completed multiple portfolio ready projects demonstrating their machine learning knowledge and practical development skills. Successful participants will receive a Certificate of Completion and a Letter of Recommendation. Outstanding performers may also be considered for future internship or placement opportunities. Perks Certificate of Completion Letter of Recommendation Work From Home Flexible Working Hours Hands on Machine Learning Projects Mentorship Portfolio Development Pre Placement Opportunity Who can apply? Only those candidates can apply who: are from Any and specialisation from Any are available for duration of 2 Months have relevant skills and interests Terms of Engagement This is a full time virtual internship for three months. Interns are expected to dedicate approximately forty hours per week attend virtual meetings complete assigned project tasks maintain confidentiality and submit deliverables on time. Successful participants will receive a certificate and a letter of recommendation based on performance. Number of openings 10