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Join this free deep learning course to explore neural networks, model training, and AI applications. Get expert-led deep learning training, and hands-on insights, and earn a free certification.
28 hours of learning
Neural Networks
Development News Story
Deep Learning

What You Will Learn
Learn more about the course content and upGrad here
In this module, you'll be introduced to the basics of Neural Networks and various concepts related to Deep Neural Network
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Earn and Share Your Certificate
Official & Verifiable
Receive a signed and verifiable e-certificate from upGrad upon successfully completing the course.
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Maximize Your Learning Experience
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Access to Online Learning | ||
Certificate at Completion | ||
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This deep learning neural networks course online provides a comprehensive introduction to neural networks, covering key concepts like perceptrons, backpropagation, and model optimization. It includes hands-on learning and real-world applications to help you master deep learning.
The deep learning neural networks course eligibility includes students, working professionals, AI enthusiasts, and business leaders. Whether you’re a beginner or experienced in AI, this course is designed to help you develop deep learning expertise.
The deep learning neural networks syllabus includes neural network architecture, feedforward networks, backpropagation, regularization techniques, and hyperparameter tuning. It also covers hands-on projects using frameworks like TensorFlow and Keras.
The deep learning neural networks course duration is approximately 28 hours. However, since it is self-paced, you can complete it at your convenience, revisiting concepts anytime with lifetime access.
Yes, you will earn a deep learning neural networks certification online upon successfully completing the course. This certificate validates your skills and can be added to your resume or LinkedIn profile to enhance job prospects.
No, these deep learning neural network classes are designed for all skill levels. Whether you are a beginner or have some experience, the structured lessons and hands-on exercises will help you build expertise from scratch.
Yes, this course is designed for learners of all levels, including beginners. It starts with fundamental concepts and gradually progresses to advanced topics, making it easy to follow for students, professionals, and AI enthusiasts.
This deep learning neural networks program provides you with industry-relevant AI skills, making you job-ready for roles in machine learning, data science, and AI development. Companies actively seek professionals skilled in deep learning.
After completing this deep learning neural networks course online, you can explore careers as a Deep Learning Engineer, AI Researcher, Data Scientist, Machine Learning Engineer, or AI Consultant in top tech firms.
Yes, deep learning neural networks online skills are highly sought after in AI-driven industries like healthcare, finance, robotics, and automation. Businesses use deep learning for predictive analytics, image recognition, and NLP applications.
Yes! This deep learning neural networks certification online provides hands-on learning, enabling you to build AI models for image recognition, natural language processing, and predictive analytics using real-world datasets.
To take this deep learning neural networks online course, you’ll need a basic computer or laptop with internet access. Familiarity with Python is helpful but not mandatory. The course uses user-friendly tools like TensorFlow and Keras, making it accessible even to beginners.
While not mandatory, installing tools like Jupyter Notebook, TensorFlow, or Google Colab can enhance your learning experience. The deep learning neural networks training online includes step-by-step guidance on how to set up your environment.
You can enroll directly through upGrad’s platform by signing up with your email. The enrollment process is quick, and you’ll instantly gain access to all course materials, including the full deep learning neural networks syllabus and lifetime access to video lectures and assignments.
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