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Deep Learning

Deep Learning is a critical skill in today's data-driven world, empowering machines to perform complex tasks by learning from vast amounts of data. This skill is of paramount importance as organizations increasingly rely on AI to gain insights, make accurate predictions, and automate processes. Companies hire candidates who excel in Deep Learning to develop and deploy sophisticated neural networks capable of solving intricate problems and extracting valuable information from unstructured data. With applications spanning image and speech recognition, natural language processing, and autonomous systems, Deep Learning is in high demand, making it a sought-after skill for professionals looking to contribute to cutting-edge technologies and drive innovation in the modern job market.

Assessment Details
US $15

Performance Analysis report

40 minutes
40 MCQ

Certificate of Specialization

Credential of Readiness 

Test Syllabus

The Deep Learning Skill Test measures the candidate's proficiency in deep network architecture, neural network foundation, building and tuning deep networks, and training deep neural networks using popular frameworks. It also evaluates the candidate's ability to apply Deep Learning techniques to real-world problems, extract meaningful insights from complex datasets, and optimize deep networks for optimal performance. 


Topics covered in the test:


  • Introduction to Deep Learning

  • Deep Network Architecture

  • Deep Learning and Neural Network Foundation

  • Building Deep Networks using DL4J

  • Deep Network Tuning

  • Deep Neural Network Training using TensorFlow

  • Autoencoders, RL, and GANs

  • Deep Learning and DL4J on Spark

Related Roles

Deep Learning is a crucial skill in the field of artificial intelligence and has extensive applications in areas such as computer vision, natural language processing, and robotics. The roles involve the development, implementation, and optimization of neural networks and algorithms to solve complex problems and make accurate predictions.


Internship Roles:


  • Deep Learning Intern

  • AI Research Intern

  • Machine Learning Intern

  • Data Science Intern

  • Computer Vision Intern


Full-time Roles:


  • Deep Learning Engineer

  • AI Research Scientist

  • Machine Learning Engineer

  • Data Scientist

  • Computer Vision Engineer

  • Natural Language Processing (NLP) Engineer

  • Robotics Engineer

  • AI Consultant

  • AI Solutions Architect

  • AI Product Manager

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