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AWS

This introductory course provides an overview of Deep Learning (DL) concepts. In the course, we discuss the AWS services available for DL and walk through a case study of an AWS customer who is innovating with DL.

This introductory course provides an overview of Deep Learning (DL) concepts. In the course, we discuss the AWS services available for DL and walk through a case study of an AWS customer who is innovating with DL.

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What's inside

Syllabus

What is Deep Learning?

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores Deep Learning, which is a rapidly growing field in artificial intelligence
Offers a foundational understanding of cutting-edge machine learning techniques
Examines practical applications of Deep Learning in various industries
Provides a hands-on lab and interactive materials to enhance practical learning
Taught by AWS, a well-known and respected provider in the field of cloud computing and artificial intelligence

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in What is Deep Learning? with these activities:
Review 'Deep Learning with Python'
Refamiliarize yourself with foundational knowledge of Deep Learning essential for this course.
Show steps
  • Read the first three chapters of 'Deep Learning with Python' by François Chollet.
  • Take notes on the key concepts and techniques discussed in the chapters.
  • Complete the practice exercises at the end of each chapter.
Practice solving Deep Learning coding challenges
Enhance your practical Deep Learning skills and improve understanding of core concepts.
Show steps
  • Find a reputable online coding challenge platform such as HackerRank or LeetCode.
  • Filter for Deep Learning-related challenges.
  • Attempt to solve at least 10 challenges.
  • Review your solutions and identify areas for improvement.
Show all two activities

Career center

Learners who complete What is Deep Learning? will develop knowledge and skills that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineers design, build, and maintain computer vision systems. This course provides an overview of Deep Learning (DL) concepts, which are essential for Computer Vision Engineers to understand. DL is a powerful technique that can be used to solve a wide range of problems, from image recognition to object detection. By taking this course, Computer Vision Engineers can learn how to use DL to improve their work and develop new innovative solutions.
Deep Learning Engineer
Deep Learning Engineers design, build, and maintain deep learning models. This course provides an overview of Deep Learning (DL) concepts, which are essential for Deep Learning Engineers to understand. DL is a powerful technique that can be used to solve a wide range of problems, from image recognition to natural language processing. By taking this course, Deep Learning Engineers can learn how to use DL to improve their work and develop new innovative solutions.
Data Scientist
Data Scientists use their knowledge of mathematics, statistics, and computer science to extract meaningful insights from data. This course provides an overview of Deep Learning (DL) concepts, which are essential for Data Scientists to understand. DL is a powerful technique that can be used to solve a wide range of problems, from image recognition to natural language processing. By taking this course, Data Scientists can learn how to use DL to improve their work and develop new innovative solutions.
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models. This course provides an overview of Deep Learning (DL) concepts, which are essential for Machine Learning Engineers to understand. DL is a powerful technique that can be used to solve a wide range of problems, from image recognition to natural language processing. By taking this course, Machine Learning Engineers can learn how to use DL to improve their work and develop new innovative solutions.
Natural Language Processing Engineer
Natural Language Processing Engineers design, build, and maintain natural language processing systems. This course provides an overview of Deep Learning (DL) concepts, which are essential for Natural Language Processing Engineers to understand. DL is a powerful technique that can be used to solve a wide range of problems, from text classification to machine translation. By taking this course, Natural Language Processing Engineers can learn how to use DL to improve their work and develop new innovative solutions.
Artificial Intelligence Engineer
Artificial Intelligence Engineers design, build, and maintain artificial intelligence systems. This course provides an overview of Deep Learning (DL) concepts, which are essential for Artificial Intelligence Engineers to understand. DL is a powerful technique that can be used to solve a wide range of problems, from image recognition to natural language processing. By taking this course, Artificial Intelligence Engineers can learn how to use DL to improve their work and develop new innovative solutions.
Research Scientist
Research Scientists conduct research in a variety of scientific fields. This course provides an overview of Deep Learning (DL) concepts, which are essential for Research Scientists to understand. DL is a powerful technique that can be used to solve a wide range of problems, from drug discovery to climate modeling. By taking this course, Research Scientists can learn how to use DL to improve their work and develop new innovative solutions.
Software Engineer
Software Engineers design, build, and maintain software systems. This course provides an overview of Deep Learning (DL) concepts, which are becoming increasingly important for Software Engineers to understand. DL is a powerful technique that can be used to solve a wide range of problems, from fraud detection to predictive analytics. By taking this course, Software Engineers can learn how to use DL to improve their work and develop new innovative solutions.
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. This course provides an overview of Deep Learning (DL) concepts, which can be useful for Data Analysts to understand. DL is a powerful technique that can be used to solve a wide range of problems, from customer segmentation to fraud detection. By taking this course, Data Analysts can learn how to use DL to improve their work and develop new innovative solutions.
Business Analyst
Business Analysts help businesses improve their performance by identifying and solving problems. This course provides an overview of Deep Learning (DL) concepts, which may be useful for Business Analysts to understand. DL is a powerful technique that can be used to solve a wide range of problems, from customer segmentation to fraud detection. By taking this course, Business Analysts can learn how to use DL to improve their work and develop new innovative solutions.
Product Manager
Product Managers are responsible for the development and launch of new products. This course provides an overview of Deep Learning (DL) concepts, which may be useful for Product Managers to understand. DL is a powerful technique that can be used to solve a wide range of problems, from customer segmentation to fraud detection. By taking this course, Product Managers can learn how to use DL to improve their work and develop new innovative solutions.
Marketing Manager
Marketing Managers are responsible for developing and executing marketing campaigns. This course provides an overview of Deep Learning (DL) concepts, which may be useful for Marketing Managers to understand. DL is a powerful technique that can be used to solve a wide range of problems, from customer segmentation to fraud detection. By taking this course, Marketing Managers can learn how to use DL to improve their work and develop new innovative solutions.
Sales Manager
Sales Managers are responsible for leading and motivating sales teams. This course provides an overview of Deep Learning (DL) concepts, which may be useful for Sales Managers to understand. DL is a powerful technique that can be used to solve a wide range of problems, from customer segmentation to fraud detection. By taking this course, Sales Managers can learn how to use DL to improve their work and develop new innovative solutions.
Financial Analyst
Financial Analysts provide financial advice to individuals and businesses. This course provides an overview of Deep Learning (DL) concepts, which may be useful for Financial Analysts to understand. DL is a powerful technique that can be used to solve a wide range of problems, from fraud detection to risk assessment. By taking this course, Financial Analysts can learn how to use DL to improve their work and develop new innovative solutions.
Operations Manager
Operations Managers are responsible for planning and overseeing the day-to-day operations of a company. This course provides an overview of Deep Learning (DL) concepts, which may be useful for Operations Managers to understand. DL is a powerful technique that can be used to solve a wide range of problems, from supply chain management to quality control. By taking this course, Operations Managers can learn how to use DL to improve their work and develop new innovative solutions.

Reading list

We've selected nine books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in What is Deep Learning?.
Provides a comprehensive overview of deep learning, from its history and foundations to its current applications. It valuable resource for anyone who wants to learn more about deep learning, whether they are new to the field or have some experience.
Provides a hands-on introduction to machine learning, with a focus on deep learning. It great resource for anyone who wants to learn how to build and train deep learning models.
Provides a comprehensive overview of deep learning for natural language processing. It valuable resource for anyone who wants to learn how to apply deep learning to NLP tasks.
Provides a practical introduction to deep learning using Python. It great resource for anyone who wants to learn how to build and train deep learning models in Python.
Provides a comprehensive overview of deep learning for computer vision. It valuable resource for anyone who wants to learn how to apply deep learning to computer vision tasks.
Provides a comprehensive overview of deep learning for audio, speech and language processing. It valuable resource for anyone who wants to learn how to apply deep learning to these tasks.
Provides a comprehensive overview of deep learning for healthcare. It valuable resource for anyone who wants to learn how to apply deep learning to healthcare applications.
Provides a comprehensive overview of deep learning for the web. It valuable resource for anyone who wants to learn how to apply deep learning to web applications.
Provides a comprehensive overview of deep learning for recommender systems. It valuable resource for anyone who wants to learn how to apply deep learning to recommender system applications.

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