Master of Science in Machine Learning (STEM)

at EDUCO - Stevens Institute of Technology USA

The robotics master’s program at Stevens, offered by the Department of Mechanical Engineering, gives students an edge in a competitive and multidisciplinary profession where a mastery of modeling, design, research, and implementation skills is just as important as the next big idea.

This distinctive master’s degree program exposes students to both the mathematical foundations of robotics, and relevant hands-on laboratory projects in robotics and mechatronics. The robotics master's degree program integrates the study of fundamentals in robot modeling, analysis, design, and control with modern and advanced applications of robotics technology to meet today’s specialized needs within the industry. The curriculum is designed to ensure that graduating students are well-prepared for a future that will increasingly demand multidisciplinary training for engineers, especially for careers involving robotics, automation, and autonomous and intelligent systems.

Robotics graduates will be prepared to solve complex engineering problems, position emerging technologies, lead the development of high-quality products, manage projects and maintain exacting standards in a fast-evolving economy.

The finance world's rapid transition to a digital discipline has created incredible opportunities for experts in computer science, statistics, economics and mathematics to develop solutions to increasingly complex problems, such as how to value an asset, how to assess risk and the smartest ways to manage a portfolio. Quants are some of the most-sought professionals on Wall Street for their coding versatility and ability to model financial data to drive better decision-making.

The Financial Engineering program at Stevens resides in the School of Business, giving it a practical orientation that few other programs offer. Lessons emphasize how technical tools can address specific challenges in the markets, while preparing you to identify inefficiencies, recognize opportunities and develop innovative new products. The Stevens program also recognizes the systemic nature of financial markets and prepares you for the challenges of working in large, interconnected environments.

In the applied artificial intelligence masters program, graduate students develop a strong background in the theoretical foundations and algorithm development in artificial intelligence and deep learning with a thorough understanding of a variety of engineering applications. Students will learn a blend of software and hardware skills that are applicable across multiple engineering domains.

Students are immersed in a hands-on approach to learning within a mix of course offerings, from fundamental core courses to state-of-the art topics such as internet of things (IoT), information systems security, and big data applications.

Masters students in the applied artificial intelligence program have the opportunity to work on exciting new projects and applications relating to:

• Machine learning
• Deep learning
• Image processing and computer vision
• Autonomous robotics
• Smart health
• Biomedical engineering
• Transportation engineering
• Financial engineering
• Embedded systems
• Software engineering
• Intelligent communications networks

Concentrations

• Artificial Intelligence in Design and Construction
• Biomedical Engineering
• Computer Engineering
• Data Engineering
• Electrical Engineering
• Mechanical Engineering
• Software Engineering
• Systems Biology

Unlike financial engineers, who use mathematical modeling and computer science skills to create algorithms and tools, financial analysts combine their programming skills with talents in data analysis and statistics to design innovative solutions to finance problems. They also use excellent business and communication skills to assess client needs and make recommendations to executive teams.

The Stevens master’s in Financial Analytics teaches professionals to apply their physics, statistics or engineering skills to the lucrative finance industry. You’ll learn from faculty whose insights are changing how the industry is thinking about concepts like machine learning, data modeling and optimization in finance. You’ll take courses in one-of-a-kind financial labs, home to the data analysis and visualization tools used on Wall Street. Most importantly, our location on the Hudson River ensures you’ll have regular interaction with industry recruiters in New York City, just 10 minutes away by train or ferry.

In the 21st century, the demand for capable systems leaders with the technical knowledge to design, operate and maintain cutting-edge systems in an increasingly complex, globally interconnected business and policy environment is at an all-time high. The systems leaders of tomorrow come to the School of Systems & Enterprises (SSE) today to develop the knowledge base necessary to succeed in systems engineering across industries.

The SSE is the largest provider of systems engineering education to the United States federal government and to industries worldwide, such as aerospace, automotive, defense and healthcare industries. Our Master of Engineering program teaches students the multidisciplinary skills and approaches needed for the architecture/design and management of complex technical systems and processes throughout their life cycles.

Students are exposed to the right blend of engineering, technology and management training to prepare them to immediately step into technical leadership roles post-graduation. Master of Engineering program graduates aren't just able to successfully navigate and manage complex systems — they are also able to apply their systems thinking at the system and enterprises levels to spearhead systems integration, address life cycle issues and standout in a market where globalization, quality, complexity and productivity are business drivers.

Get on the fast track to make an impact in one of today’s fastest growing fields with a machine learning master’s degree.

The machine learning master’s program establishes the theoretical and practical foundations necessary to be at the forefront of progress in the next technological revolution. Advancements made in machine learning and related disciplines will soon touch every piece of technology, making an advanced degree an essential asset for a successful career.

The rapidly expanding field of machine learning has a multitude of applications in diverse areas such as intelligent systems, computer vision, speech recognition, natural language processing, robotics, finance, information retrieval, bioinformatics, healthcare, and weather prediction.

Our unique machine learning master’s program develops a thorough understanding of deep learning theory and familiarizes students with the most important paradigms. This allows them to apply or develop the appropriate methods in real-world applications, whether pursuing a career in industry, academia, or research.

The engineering physics master’s program prepares students for a successful career in industry or research by combining courses in fundamental physics with specializations that focus on applications to current research and technology. Students will gain deeper insight and skills in specific branches of engineering and interdisciplinary physics research including quantum engineering, applied optics, solid state device engineering and nanotechnology.

The program prepares students with broad coverage of fundamentals as well as state-of-the-art industrial practices in the areas of design, fabrication, integration, and application of microelectronic and photonic devices in communication and information systems. Designed for maximum flexibility, the program accommodates the backgrounds and interests of students with either a master's degree or graduate certificate.

To apply for this program, select "Interdisciplinary Science" or "Interdisciplinary Engineering" on the application, and indicate your desire to pursue the program in microelectronics and photonics on your statement of purpose.?

In the applied artificial intelligence masters program, graduate students develop a strong background in the theoretical foundations and algorithm development in artificial intelligence and deep learning with a thorough understanding of a variety of engineering applications. Students will learn a blend of software and hardware skills that are applicable across multiple engineering domains.

Students are immersed in a hands-on approach to learning within a mix of course offerings, from fundamental core courses to state-of-the art topics such as internet of things (IoT), information systems security, and big data applications.

Masters students in the applied artificial intelligence program have the opportunity to work on exciting new projects and applications relating to:

• Machine learning
• Deep learning
• Image processing and computer vision
• Autonomous robotics
• Smart health
• Biomedical engineering
• Transportation engineering
• Financial engineering
• Embedded systems
• Software engineering
• Intelligent communications networks

Concentrations

• Artificial Intelligence in Design and Construction
• Biomedical Engineering
• Computer Engineering
• Data Engineering
• Electrical Engineering
• Mechanical Engineering
• Software Engineering
• Systems Biology

The cybersecurity master’s program is designed for security professionals who seek an in-depth understanding of the technical knowledge related to information security as well as an appreciation of the organizational, social, managerial and legal aspects of security and privacy.

Cybersecurity is a high-growth field currently experiencing a demand far greater than the supply of trained professionals available. The White House has reported that in the coming years as many as 30,000 new cybersecurity professionals are needed by the United States government alone.