Internships
Get yourself enrolled into semester long Internship
Introduction to Digital Circuit Design for VLSI
An Introduction to Embedded Systems with Arduino and ESP
Machine Learning with Python
Full Stack Web Development
Introduction to Digital Circuit Design for VLSI
Internships
An Introduction to Embedded Systems with Arduino and ESP
Full Stack Web Development
Learn Node.js by building real-world applications with Node JS, Express, Postgresql, ReactJs, Jest, and more!
The Full Stack Development Course is a comprehensive 10-week program designed for beginners with no prior coding experience. It aims to equip students with the skills necessary to build full-stack web applications and prepare them for entry-level web development positions.
This course on Embedded Systems and IoT provides third-year engineering students with a comprehensive understanding of microcontroller-based systems, focusing on Arduino and ESP processors. Over 10 weeks, students will learn the fundamentals of embedded systems, real-time operating systems, and IoT architecture. They will gain hands-on experience in programming and interfacing sensors and actuators, developing IoT applications, and implementing secure and energy-efficient systems. The course culminates in a project that integrates both Arduino and ESP platforms, preparing students for real-world IoT challenges and innovations.
This course introduces the principles and practices of digital circuit design for VLSI. It covers the entire design flow from basic concepts to implementation, simulation, and verification using industry-standard tools
Machine Learning with Python
This 10-week course on Machine Learning with Python is designed to provide participants with a comprehensive understanding of machine learning concepts, techniques, and applications. Through theoretical knowledge and practical, hands-on experience, participants will learn to utilize Python and its powerful libraries for data analysis, visualization, and model building. The course covers essential topics such as data preprocessing, supervised and unsupervised learning, model evaluation, and optimization. Additionally, participants will gain introductory exposure to deep learning using TensorFlow and Keras. By the end of the course, participants will be equipped with the skills to develop and deploy machine-learning models to solve real-world problems
Contacts
Location
+91 9380812867 / + 91 9110858766
aarivtechnology.23@gmail.com
#89, VGS Landmark, Surya City Phase I, Chandapura, Bengaluru, India