Our artificial engineering course taps into the transformative power of Artificial Intelligence to solve real-world challenges. It is an interdisciplinary field that intersects with computer science, data science, mathematics and human science. Students benefit from state-of-the-art labs and cutting-edge technology, ensuring hands-on experience and practical application of theoretical knowledge. Additionally, our partnership with the EC Council enriches their understanding of cybersecurity challenges, providing an opportunity for certification by the company.
High Demand: AI tools are being utilized across diverse industries to enhance their products and services. With the ongoing advancement of AI technology , there is a growing demand for skilled AI professionals.
Problem Solving: AI graduates can be part of groundbreaking advancements, thereby contributing to solutions for real-world challenges by developing new AI features.
Versatile Career Opportunities: An AI engineering degree opens doors to diverse career opportunities. Opportunities are aplenty in IT services, finance, healthcare, manufacturing, telecommunications, and aerospace.
To become an expert machine learning engineer, one has to obtain a bachelor degree in computer science, mathematics, statistics, or a related field along with strong data modeling and architecture skills. Expertise in Python, R, or Java programming is mandatory to be a successful machine learning engineer.
As a Machine learning Engineer one needs to understand the machine learning system, model, or scheme which is designed, developed, and researched. Data science prototypes are studied, transformed, and converted. Prior to performing data collection and data modeling, search for and select appropriate data sets. AI/Machine Learning Engineers are truly changing the world.
Yes, AI/Machine Learning is an excellent career track. According to reports, Machine Learning Engineer is the most in-demand job in terms of salary, postings, and general demand.
AI Engineering is a combination of research and continuous practice that includes software development, computer vision, system engineering knowledge along with human-centered design to develop AI systems that bring changes to the world.
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