Finishing School

B.Voc Course in Automotive Electronics ( AVCC Approved )

Our institute is proud to offer a comprehensive B.Voc program in Automotive Electronics, approved by the Autonomous Vehicle Computing Consortium (AVCC). This unique program is designed to equip students with the knowledge and skills required to excel in the dynamic field of automotive electronics.

Throughout this course, students will delve into the intricacies of modern automotive systems, gaining expertise in electronic control systems, vehicle diagnostics, electric powertrains, and more. Hands-on practical training, industry-relevant projects, and internships with leading automotive companies will provide a holistic learning experience, ensuring our graduates are well-prepared for a rewarding career in the automotive industry.

Join us in shaping the future of automotive technology with our B.Voc in Automotive Electronics. Explore the exciting world of electric vehicles, hybrid systems, and advanced automotive electronics under the guidance of experienced faculty and state-of-the-art facilities. Make a meaningful impact in the automotive sector and secure your place in this rapidly evolving industry.

Duration

4 Semesters

Semester 1

Total Hours: 150

Introduction to automotive electronics, basic components, and systems. Overview of industry standards and safety practices.

Total Hours: 180

Fundamental concepts of electricity, electronic circuits, and Ohm's law. Hands-on experiments and circuit analysis.

Semester 2

Total Hours: 160

Study of automotive electrical systems, including starting, charging, and lighting systems. Diagnosis and repair techniques.

Total Hours: 200

Types of sensors and actuators used in vehicles. Calibration and troubleshooting. Integration with electronic control units.

Semester 3

Total Hours: 180

Introduction to electric powertrains, batteries, and energy storage systems in electric vehicles (EVs) and hybrid electric vehicles (HEVs).

Total Hours: 160

Study of vehicle control systems, including engine control, transmission control, and stability control. Practical control system design and analysis.

Semester 4

Total Hours: 180

Exploration of autonomous vehicles, ADAS, and sensor technologies. Hands-on experience with advanced driver assistance systems.

Total Hours: 160

Understanding automotive cybersecurity, threat analysis, and security measures to protect electronic systems in vehicles.

Assessment

Assessment includes continuous assessments (quizzes, assignments, and class participation), midterm examinations, final examinations, project work and presentations, and internship evaluations.

Graduation Requirements

To graduate, students must successfully complete all modules and projects, achieve satisfactory performance in the final-year industry internship and project, and maintain a minimum required cumulative GPA.

P.G. Diploma In Data Science (Association With NVIDIA)

Our institute is thrilled to introduce a cutting-edge P.G. Diploma program in Data Science, in collaboration with NVIDIA, a global leader in accelerated computing and artificial intelligence technology. This exclusive partnership ensures that our students receive the most advanced tools and resources available in the field of data science.

Throughout this program, students will embark on an exciting journey to harness the potential of data. From data collection and analysis to machine learning and deep learning, our curriculum covers a comprehensive range of topics. The NVIDIA association adds a unique dimension to our program, providing students with access to high-performance GPUs and AI platforms, empowering them to tackle complex data challenges with speed and precision.

Join us to be at the forefront of data science, leveraging the expertise of NVIDIA, and equip yourself with the skills required to excel in a data-driven world. Our P.G. Diploma in Data Science with NVIDIA opens doors to a wide array of career opportunities in industries like finance, healthcare, technology, and more, where data-driven decision-making is pivotal.

Syllabus

• Introduction to Data Science and its Importance

• Python Programming for Data Science

• Data Exploration and Visualization

• Statistical Analysis and Probability

• Data Cleaning and Transformation

• Supervised and Unsupervised Learning

• Machine Learning Algorithms

• Model Evaluation and Validation

• Feature Engineering and Selection

• Time Series Analysis and Forecasting

• Natural Language Processing (NLP)

• Deep Learning and Neural Networks

• Introduction to Big Data and Hadoop

• Big Data Tools and Technologies

• Cloud Computing for Data Science

• Data Warehousing and ETL

• Advanced Data Science Topics

• Industry Applications and Case Studies

• Capstone Project: Real-world Data Science Project

• Presentation and Project Showcase

Course Evaluation System

• Quizzes: Regular quizzes at the end of each module (e.g., 10 multiple-choice questions per module).

• Homework Assignments: Weekly assignments for each module (e.g., problem-solving exercises and short essays).

• Weightage: Quizzes (20% of the module grade), Homework (30% of the module grade).

• A midterm examination (e.g., 2 hours) assessing the knowledge and skills acquired in the first half of the course.

• Weightage: Midterm Examination (15% of the overall course grade).

• A comprehensive final examination (e.g., 3 hours) covering all course modules.

• Weightage: Final Examination (25% of the overall course grade).

• Assessing the quality and depth of the projects completed by students (e.g., 20 hours of project work per module).

• Weightage: Project Evaluation (30% of the module grade).

• Encouraging active participation in discussions, group activities, and problem-solving sessions within each module.

• Weightage: Class Participation (10% of the module grade).