AI is defined as the development of computer systems capable of performing tasks that typically require human intelligence. In other words, AI enables computers to think and behave more like people to solve problems. Whereas machine learning is a method of analyzing data that helps computer programs optimize their functionality as they learn from vast quantities of data. Machine learning is a specific form of AI that enables computers to learn and grow as they’re introduced to data-based scenarios.
If you’re looking for a solid, secure future, a career as a machine learning engineer is the right one. In fact, it was just listed as the second-most in-demand AI profession, with the pandemic bringing a greater focus on the fields of artificial intelligence and machine learning. Over the past four years, employment in AI and machine learning has increased by approximately 75%, and this growth is expected to continue. Pursuing a machine learning job is a solid choice for a high-paying career that will be in demand for decades. Industries that are already using AI and machine learning predominantly include healthcare, education, marketing, retail and ecommerce, and financial services. A career in machine learning is for you if you want to work on projects that change the world while earning a high salary and benefits.
Our Department offers choice based credit system (CBCS), which provides an opportunity for the students to choose courses from the prescribed courses comprising core, elective/minor or skill based courses. The AI/ML Engineering curriculum has been developed by considering the industry needs and technologies. Open electives are introduced from first year to final year to allow students to choose various horizons in AI/ML domain. In first year there are open electives and language courses, in second year students have open elective based on professional skill development courses, in third and final year program electives based on the various verticals such as data analysis, deep learning, natural language processing and so on are floated and in the eighth semester students are given a choice of three tracks viz. Industry Internship and Project, Undergraduate Research Experience and Entrepreneurship Development
The curriculum prepares students to tackle industrial and societal problems by applying gained domain knowledge. Students will learn best practices in solving real world problems by applying sequential methods of problem identification, formulation, design, develop, deploy and maintenance.
Students learn to use the latest programming languages along with necessary domain knowledge as and when required. Students will be given the opportunity to hone their skills in effectively by selecting one of the three tracks as per their choice. Three tracks are: Industry Internship & Project (IIP), Undergraduate Research Experience (URE), Entrepreneurship Development (ED).
Why Study AI/ML at RIT?
The interesting, difficult, and expanding area of artificial intelligence and machine learning has a huge influence on daily life and society worldwide. The Department of AIML at RIT will examine both the theory and application of AI and ML, and classes are instructed by knowledgeable academics who are also engaged in ongoing research. Project-based learning, active learning, and significant hands-on experience will all be given more importance. At RIT, you may use a variety of facilities for learning and doing research.
The most popular topic and probably the most desirable field in both industry and academia right now is artificial intelligence and machine learning. The majority of IT businesses, including Microsoft, Google, Amazon, Tesla, and NVIDIA, have incorporated this idea into their operating systems. An area of computer science that is rapidly expanding focuses on developing and offering intelligent problem-solving solutions is artificial intelligence software, which is produced by the top artificial intelligence businesses. Speech recognition, problem-solving, learning, and planning capabilities of AI software can support or even take the place of human involvement in a process.
In general, the following are the various reasons why every student should learn AIML:
Career path you can choose after the course
Types of companies with career opportunities