Learn about Neural Networks with Online Courses & Training Programs

Courses in AI and Machine Learning | Education Program  | Emeritus

Carnegie Mellon University School of Computer Science

Deep Learning

10 Weeks

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Last Date to Apply: April 25, 2024

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Carnegie Mellon University School of Computer Science

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10 Weeks

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Starts on: April 25, 2024

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MIT xPRO

Designing and Building AI Products and Services

8 Weeks

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Starts on: May 9, 2024

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Imperial College Business School Executive Education

Professional Certificate in Data Analytics

25 Weeks

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Starts on: May 9, 2024

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Emeritus

Professional Certificate in Data Engineering with Microsoft Azure

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Cambridge Judge Business School Executive Education

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11 weeks

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Courses in AI and Machine Learning | Education Program  | Emeritus

Imperial College Business School Executive Education

Professional Certificate in Machine Learning and Artificial Intelligence

25 weeks

Online

Starts on: May 21, 2024

Courses in AI and Machine Learning | Education Program  | Emeritus

Berkeley Executive Education

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2 months

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Starts on: June 20, 2024

Courses in AI and Machine Learning | Education Program  | Emeritus

Carnegie Mellon University School of Computer Science

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10 Weeks

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What are Neural Networks?

Neural networks form the basis of deep learning algorithms and are a subset of machine learning. They are also known as artificial neural networks (ANNs) or simulated neural networks (SNNs). Their structure imitates the activity of real-time neurons in the human brain, thus allowing computer systems to identify patterns and accomplish problem-solving tasks.

Neural networks are indispensable to artificial intelligence (AI). Comprising multiple node layers, they use training data to improve their accuracy. This, in turn, enables the rapid processing and classification of data for tasks such as image or face recognition.

Why are Neural Networks Important?

At the most basic level, the primary function of neural networks is to eliminate the need for human intervention in decision-making. Neural networks are developed to mimic the human brain and have important applications in various fields. Computer vision, for instance, is one of the most extensive uses of neural networks. Self-driven cars, facial recognition, and image labeling are some examples of computer vision that neural networks facilitate.

Neural networks are also programmed to identify and analyze human speech. This involves bypassing obstacles like varying pitch, tonality, language, and accent. Speech recognition underlies many day-to-day activities, such as Amazon Alexa, speech-to-text typing, and automatic transcription software. Other uses of deep learning include recommendation engines and natural language processing (NLP).

Can I learn about neural networks online?

With organizations recognizing the growing need for neural networks in their products, operations, as well as business strategies, they are on the lookout for professionals with a penchant for the same. This has, in turn, spurred job-seekers to upskill, which has led several resources to emerge. Among these, online neural networks courses have garnered immense popularity as they are affordable, engaging, and offered by some of the most distinguished institutions in the world. Most of these courses also offer certification. In addition, they are a helpful way of mastering the fundamentals of neural networks, fine-tuning the knowledge you already have, and advancing to the more complex aspects of the subject.

What kind of career can I pursue with a background in neural networks?

Valued at USD 7.03 billion in 2016, the global ANNs market will reach a valuation of USD 38.71 billion by 2023, at a CAGR of 28% between 2017 and 2023. This report, published by Allied Market Research, points to a significant proliferation of job opportunities that such growth entails.

Some of the most high-paying job roles in neural networks are that of a test engineer, research scientist, applied scientist, business intelligence developer, and full-stack developer. Many also opt for a career in data engineering, machine learning engineering, and deep learning engineering as the field of AI continues to expand at an equally astronomical rate.

Why take an online course at Emeritus?

Each Emeritus online course is designed keeping key learning outcomes in mind by a team of experts. We use the backward design methodology to develop instruction for learners of all ages. This enables us to craft unique, interactive, learning experiences that include a combination of assessments, hands-on activities, skill application, and more.

Emeritus also collaborates with the best universities and faculty around the world to curate the course curriculum that can effectively tackle present challenges in the industry, while preparing you for the trends and risks in the future. Our courses consist of assignments, exams, capstone projects, networking opportunities, a fine balance of practical and theoretical concepts, and the opportunity to learn from top minds in the industry. This adds to the holistic experience we try to provide for each learner.

We are also focused on providing courses that are standardized in quality. This is done by adhering to standards set by a global organization called Quality Matters which is focused on providing quality standards for online and innovative digital teaching and learning environments. The rigorous criteria ensure all our learners invest in quality education that is easily accessible and affordable.