Internship in Machine Learning & AI

Objective of course

• Develop a strong foundation in Artificial Intelligence (AI) and Machine Learning (ML), including essential math and core concepts.
• Equip learners with hands-on experience in building predictive models, image classifiers, and text classifiers.
• Introduce practical applications of neural networks, natural language processing (NLP), and computer vision.
• Enable participants to understand and implement end-to-end ML workflows, from data preprocessing to model evaluation.
• Prepare students for AI/ML industry roles by enhancing their professional profiles and interview readiness.

Job roles in industry:

• Machine Learning Engineer
• Data Scientist
• AI Engineer
• NLP specialist
• AI/ML Researcher

Included in this course

• Fundamentals of machine learning & AI
• Building and evaluating supervised ML models
• Building and training a convolutional neural network (CNN) on image datasets
• Building ML models for text classification (e.g., sentiment analysis)
• Assignment in each topic.
• Mock interviews with feedback on core and advanced AI/ML topics.
• Dedicated sessions for Q&A and project documentation reviews to ensure clarity and thorough understanding.

Passing criteria:

Learner needs to score minimum 60% to pass the exam. Scores are given for every quiz & assignment.