Studying Artificial Intelligence & Machine Learning (AIML) under Visvesvaraya Technological University (VTU) requires consistent effort and a structured approach. The engineering curriculum is designed to build a solid foundation of theoretical principles paired with hands-on laboratory experience. To support your studies, VTUwise compiles all essential resources into a single dashboard.
VTU Passing Rules and Evaluation
VTU employs the Choice Based Credit System (CBCS) across its schemes (2018, 2021, and the latest 2022 scheme). To pass any theory course in Artificial Intelligence & Machine Learning:
- Continuous Internal Evaluation (CIE): Secure at least 40% (20 out of 50 marks) in internal college assessments to remain eligible to write final exams.
- Semester End Examination (SEE): Score at least 35% (35 out of 100 marks) in the final university theory exam.
- Overall Passing Aggregate: Your total CIE and SEE combined score must be at least 40% of the total marks.
Study Tips for Artificial Intelligence & Machine Learning Students
- Start Early with Core Subjects: High-credit courses like core programming, hardware circuits, and structural design require early conceptual learning. Do not leave them for the last week.
- Reference Official Syllabus: Always verify topics against the official VTU syllabus. This keeps you focused on high-yield exam sections.
- Practice Past 5 Years Papers: Evaluators tend to repeat structural math and derivation patterns. Solving previous year papers helps you build speed and presentation style.