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Introduction to Deep Learning & Neural Networks with Keras

4.7 Filled star Filled star Filled star Filled star Half star
Based on 2,001 ratings
see reviews
Alex Aklson

Looking to start a career in Deep Learning? Look no further. This course will introduce you to the field of deep learning and help you answer many questions that people are asking nowadays, like what is deep learning, and how do deep learning models compare to artificial neural networks? You will learn about the different deep learning models and build your first deep learning model using the Keras library.

After completing this course, learners will be able to:

• Describe what a neural network is, what a deep learning model is, and the difference between them.

Read more

Looking to start a career in Deep Learning? Look no further. This course will introduce you to the field of deep learning and help you answer many questions that people are asking nowadays, like what is deep learning, and how do deep learning models compare to artificial neural networks? You will learn about the different deep learning models and build your first deep learning model using the Keras library.

After completing this course, learners will be able to:

• Describe what a neural network is, what a deep learning model is, and the difference between them.

• Demonstrate an understanding of unsupervised deep learning models such as autoencoders and restricted Boltzmann machines.

• Demonstrate an understanding of supervised deep learning models such as convolutional neural networks and recurrent networks.

• Build deep learning models and networks using the Keras library.

Enroll now

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What's inside

Syllabus

Introduction to Neural Networks and Deep Learning
In this module, you will learn about exciting applications of deep learning and why now is the perfect time to learn deep learning. You will also learn about neural networks and how most of the deep learning algorithms are inspired by the way our brain functions and the neurons process data. Finally, you will learn about how neural networks feed data forward through the network.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Explored advanced topics such as backpropagation and activation functions in neural networks
Taught by an experienced instructor with proven expertise in deep learning
Course developed core skills in deep learning using the Keras library
Examined unsupervised and supervised deep learning models
Covered foundational theories and concepts for beginners
Includes hands-on labs for practical application

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Reviews summary

Introduction to deep learning with keras

According to learners, this course offers a solid and practical introduction to the field of deep learning and neural networks, especially for those starting out. Students frequently praise the clear explanations of fundamental concepts like back propagation and activation functions, which help build a strong base. The hands-on labs and practical application of the Keras library are highlighted as particularly valuable for gaining experience. While many find it a great first step, some reviewers note that the course remains introductory and does not delve deeply into more advanced topics or complex model architectures, suggesting it might be too basic for those with prior experience. Overall, it is seen as an accessible entry point.
Practical labs reinforce learning.
"Excellent course for beginners! The lectures were clear and the labs using Keras were very helpful."
"The labs were engaging and helped reinforce the material."
"Appreciated the practical exercises to build models."
"I found the coding exercises essential for learning."
Fundamentals are explained effectively.
"The explanations on neural networks and backpropagation were very clear."
"Helped solidify my understanding of how neural networks learn."
"Gained a good grasp of activation functions and gradient descent basics."
"Concepts like backprop were explained simply."
Hands-on experience using the Keras library.
"Really enjoyed building the first model with Keras. Concepts like backprop were explained simply."
"Building models using Keras was the most valuable part for me."
"Appreciate the hands-on labs applying Keras to real problems."
"Helped me get comfortable using the Keras library quickly."
Excellent starting point for novices.
"Excellent course for beginners! The lectures were clear and the labs using Keras were very helpful."
"Perfect for absolute beginners, explains concepts like NN and backprop clearly."
"I had zero prior knowledge, and this course helped me grasp the fundamentals."
"Perfect first step into deep learning."
Doesn't cover advanced topics extensively.
"Good introduction. Covers the basics well. Felt a bit rushed towards the end covering CNNs and RNNs. Needed external resources for deeper understanding."
"It's okay, but very basic. If you already know some ML, this might be too slow."
"Didn't go deep enough for me. Expected more theory and advanced models."
"Could use more in-depth coverage on different CNN or RNN architectures."

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 Introduction to Deep Learning & Neural Networks with Keras with these activities:
Connect with Experienced Deep Learning Professionals
Accelerate your learning journey by seeking guidance and support from experienced deep learning professionals.
Browse courses on Mentorship
Show steps
  • Identify potential mentors through online platforms, professional organizations, or personal networks
  • Reach out to mentors and schedule meetings or conversations
  • Discuss your learning goals, challenges, and career aspirations
Join a Deep Learning Study Group or Community
Enhance understanding and expand perspectives by engaging in active discussions and knowledge exchange with peers.
Show steps
  • Identify or join online or offline study groups or communities dedicated to deep learning
  • Participate in regular meetings or discussions, sharing insights and collaborating on projects
  • Provide feedback and support to other members of the group
Follow Expert-Led Deep Learning Tutorials
Enhance understanding of deep learning concepts and techniques through structured tutorials led by experienced professionals.
Show steps
  • Identify reputable sources for deep learning tutorials
  • Select tutorials aligned with your learning objectives
  • Follow the tutorials step-by-step, completing exercises and assignments
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve Deep Learning Coding Challenges
Practice implementing deep learning algorithms in a coding environment to enhance understanding and problem-solving skills.
Browse courses on Coding Challenges
Show steps
  • Identify online platforms or resources providing deep learning coding challenges
  • Select challenges appropriate to your skill level and start solving them
  • Analyze the solutions and identify areas for improvement
Develop a Deep Learning Model for a Specific Business Problem
Build a deep learning model to address a specific business challenge, such as image classification, natural language processing, or time series analysis.
Browse courses on Model Development
Show steps
  • Define the business problem and collect relevant data
  • Choose an appropriate deep learning model and architecture
  • Train and evaluate the model using the collected data
  • Deploy the model and monitor its performance
Participate in Deep Learning Competitions or Hackathons
Challenge yourself, gain practical experience, and contribute to the deep learning community by participating in competitions or hackathons.
Show steps
  • Identify suitable deep learning competitions or hackathons
  • Form a team or work individually to develop a solution
  • Submit your solution and compete against other participants
  • Analyze the results and identify areas for improvement
Create a Deep Learning Blog or Article
Solidify understanding and enhance communication skills by creating a blog or article that explains deep learning concepts or shares insights.
Browse courses on Content Creation
Show steps
  • Choose a specific deep learning topic to focus on
  • Research and gather relevant information
  • Organize and structure the content into a coherent narrative
  • Proofread and refine the writing for clarity and accuracy
  • Publish and share the blog or article
Mentor Junior Deep Learning Enthusiasts
Strengthen your understanding and communication skills while contributing to the growth of others by mentoring junior deep learning enthusiasts.
Browse courses on Mentoring
Show steps
  • Identify opportunities to mentor others, such as through online forums or local meetups
  • Share your knowledge and expertise, providing guidance and support
  • Provide constructive feedback and encourage continuous learning

Career center

Learners who complete Introduction to Deep Learning & Neural Networks with Keras will develop knowledge and skills that may be useful to these careers:
Ingeniero de Aprendizaje Automático
Como Ingeniero de Aprendizaje Automático, desarrollarás y mantendrás modelos de aprendizaje automático que automatizan tareas complejas. Este curso te proporcionará una comprensión integral del aprendizaje profundo y las redes neuronales, que son las tecnologías fundamentales en el campo del aprendizaje automático. Aprenderás a diseñar, entrenar y evaluar modelos de aprendizaje profundo utilizando la biblioteca Keras.
See salaries and explore the career path for Ingeniero de Aprendizaje Automático
Investigador de aprendizaje automático
Como Investigador de Aprendizaje Automático, explorarás nuevos algoritmos y técnicas de aprendizaje automático para resolver problemas complejos. Este curso te proporcionará una sólida base teórica en aprendizaje profundo y redes neuronales, lo cual es esencial para desarrollar enfoques innovadores y avanzar en el campo del aprendizaje automático.
See salaries and explore the career path for Investigador de aprendizaje automático
Data Scientist
Como Científico de Datos, asumirás la responsabilidad de analizar y comprender grandes cantidades de datos para extraer información valiosa. Este curso te proporcionará una base sólida en aprendizaje profundo y redes neuronales, lo cual es esencial para construir modelos precisos y efectivos para el análisis de datos. Aprenderás a implementar redes neuronales profundas utilizando la biblioteca Keras, que es ampliamente utilizada en la industria.
See salaries and explore the career path for Data Scientist
Profesor de aprendizaje automático
Como Profesor de Aprendizaje Automático, impartirás cursos y realizarás investigaciones en el campo del aprendizaje automático. Este curso te proporcionará una comprensión integral del aprendizaje profundo y las redes neuronales, lo que te permitirá transmitir conocimientos precisos y actualizados a tus estudiantes y colegas.
See salaries and explore the career path for Profesor de aprendizaje automático
Físico
Como Físico, investigarás y aplicarás principios físicos para comprender y explicar el mundo natural. Este curso te proporcionará una base sólida en aprendizaje profundo y redes neuronales, que se utilizan cada vez más en el campo de la física para el análisis de datos, la simulación y el descubrimiento.
See salaries and explore the career path for Físico
Analista de Investigación
Como Analista de Investigación, utilizarás técnicas analíticas para resolver problemas complejos y proporcionar información basada en datos. Este curso te proporcionará una base sólida en aprendizaje profundo y redes neuronales, que te permitirá desarrollar modelos analíticos avanzados para extraer información y generar predicciones a partir de grandes conjuntos de datos.
See salaries and explore the career path for Analista de Investigación
Científico de Datos Junior
Como Científico de Datos Junior, estarás involucrado en la recopilación, limpieza y análisis de datos para identificar patrones y tendencias. Este curso te proporcionará una base sólida en aprendizaje profundo y redes neuronales, lo cual es esencial para construir modelos de aprendizaje automático efectivos y extraer información valiosa de los datos.
See salaries and explore the career path for Científico de Datos Junior
Ingeniero de Aprendizaje Automático Junior
Como Ingeniero de Aprendizaje Automático Junior, colaborarás con científicos de datos y otros ingenieros para desarrollar y mantener modelos de aprendizaje automático. Este curso te brindará una comprensión integral del aprendizaje profundo y las redes neuronales, lo que te permitirá contribuir al desarrollo de soluciones de aprendizaje automático innovadoras.
See salaries and explore the career path for Ingeniero de Aprendizaje Automático Junior
Ingeniero biomédico
Como Ingeniero Biomédico, aplicarás principios de ingeniería para resolver problemas médicos y de atención médica. Este curso te proporcionará una base sólida en aprendizaje profundo y redes neuronales, lo cual es cada vez más importante en el campo de la ingeniería biomédica para el desarrollo de diagnósticos, tratamientos y dispositivos médicos mejorados.
See salaries and explore the career path for Ingeniero biomédico
Actuario
Como Actuario, utilizarás habilidades matemáticas, estadísticas y financieras para evaluar y gestionar los riesgos en las industrias de seguros y finanzas. Este curso te proporcionará una base sólida en aprendizaje profundo y redes neuronales, que se están utilizando cada vez más en la industria actuarial para mejorar la modelización de riesgos, la tarificación de seguros y la gestión de inversiones.
See salaries and explore the career path for Actuario
Economista
Como Economista, analizarás y predecirás las tendencias económicas utilizando datos y modelos. Este curso te proporcionará habilidades valiosas en aprendizaje profundo y redes neuronales, que se utilizan cada vez más en el campo de la economía para mejorar la previsión económica, el análisis de políticas y la toma de decisiones.
See salaries and explore the career path for Economista
Analista de riesgos
Como Analista de Riesgos, evaluarás y gestionarás los riesgos financieros y operativos para las instituciones financieras y otras organizaciones. Este curso te proporcionará habilidades valiosas en aprendizaje profundo y redes neuronales, que se utilizan cada vez más en la industria financiera para mejorar la gestión de riesgos, la detección de fraudes y el análisis predictivo.
See salaries and explore the career path for Analista de riesgos
Ingeniero de Software
Como Ingeniero de Software, diseñarás, desarrollarás y mantendrás aplicaciones y sistemas de software. Este curso te proporcionará habilidades valiosas en aprendizaje profundo y redes neuronales, que son tecnologías emergentes que se utilizan en una amplia gama de aplicaciones, como el reconocimiento de imágenes, el procesamiento del lenguaje natural y el análisis predictivo.
See salaries and explore the career path for Ingeniero de Software
Ingeniero de Software Junior
Como Ingeniero de Software Junior, colaborarás con desarrolladores de software experimentados para diseñar, desarrollar y mantener aplicaciones y sistemas de software. Este curso te brindará habilidades valiosas en aprendizaje profundo y redes neuronales, lo que te permitirá contribuir al desarrollo de aplicaciones innovadoras que aprovechen estas tecnologías emergentes.
See salaries and explore the career path for Ingeniero de Software Junior
Analista de Investigación Junior
Como Analista de Investigación Junior, utilizarás técnicas analíticas y estadísticas para recopilar y analizar datos con el fin de responder preguntas comerciales específicas. Este curso te proporcionará una base sólida en aprendizaje profundo y redes neuronales, lo que te permitirá desarrollar habilidades analíticas avanzadas y generar información valiosa a partir de grandes conjuntos de datos.
See salaries and explore the career path for Analista de Investigación Junior

Reading list

We've selected eight 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 Introduction to Deep Learning & Neural Networks with Keras.
Cover image
Deep Learning with TensorFlow and Keras
Save
Provides a comprehensive overview of deep learning, including its history, theory, and applications. It valuable resource for anyone who wants to learn more about this rapidly growing field.
Deep Learning with TensorFlow and Keras - Third...
Paperback
$$
Deep Learning with TensorFlow 2 and Keras - Second...
Paperback
$$
Deep Learning with TensorFlow and Keras: Build and...
Kindle Edition
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Deep Learning with TensorFlow 2 and Keras:...
Kindle Edition
$$
Cover image
Hands-On Machine Learning with Scikit-Learn, Keras,...
Save
Provides a practical introduction to machine learning, with a focus on deep learning. It covers a wide range of topics, including data preparation, model building, and evaluation.
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Paperback
$$$
Hands-On Machine Learning with Scikit-Learn, Keras,...
Kindle Edition
$$
Cover image
Transformers for Natural Language Processing and...
Save
Provides a comprehensive overview of deep learning for natural language processing using transformers. It valuable resource for anyone who wants to learn more about deep learning and how to use it in practice.
Transformers for Natural Language Processing and...
Paperback
$$$
Transformers for Natural Language Processing and...
Kindle Edition
$$
Cover image
Cross-Lingual Word Embeddings
Save
Provides a comprehensive overview of deep learning for natural language processing. It covers a wide range of topics, including text classification, sentiment analysis, and machine translation.
Cross-Lingual Word Embeddings (Synthesis Lectures...
Paperback
$$
Cover image
Deep Learning for Coders with fastai and PyTorch
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Provides a practical introduction to deep learning using the fastai and PyTorch libraries. It valuable resource for anyone who wants to learn more about deep learning and how to use it in practice.
Deep Learning for Coders with Fastai and PyTorch:...
Paperback
$$
Deep Learning for Coders with fastai and PyTorch:...
Kindle Edition
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Cover image
Deep Learning Illustrated
Save
Provides a visual introduction to deep learning. It uses clear and concise explanations, along with hundreds of illustrations, to help readers understand the concepts of deep learning.
Deep Learning Illustrated: A Visual, Interactive...
Paperback
$$
Deep Learning Illustrated: A Visual, Interactive...
Kindle Edition
$$
Cover image
Deep Learning with R, Second Edition
Save
Provides a comprehensive overview of deep learning, with a focus on using the R programming language. It valuable resource for anyone who wants to learn more about deep learning and how to use it in practice.
Deep Learning with R, Second Edition
Paperback
$$$
Deep Learning with R, Second Edition
Kindle Edition
$$
Cover image
Statistical Foundations of Actuarial Learning and...
Save
Provides a comprehensive overview of neural networks and deep learning. It valuable resource for anyone who wants to learn more about these topics.
Statistical Foundations of Actuarial Learning and...
Paperback
$$

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Course image
Rating
4.7 Filled star Filled star Filled star Filled star Half star
Effort
Approx. 8 hours
Level
Intermediate
Via
Coursera
Institution
IBM
Instructor
Alex Aklson
Language
English
Transcripts
Español Français Português Deutsch Italiano 中文 العربية 한국어 日本語 हिंदी Nederlands Svenska Pусский Türkçe Polski Ελληνικά українська мова magyar nyelv Bahasa Indonesia ไทย қазақша اُردُو, فارسی বাংলা پښتو آذربایجان دیلی
Introduction to Deep Learning & Neural Networks with Keras belongs to the following collections:
  1. IBM AI Engineering
  2. IBM AI Engineering
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Explored advanced topics such as backpropagation and activation functions in neural networks
Taught by an experienced instructor with proven expertise in deep learning
Course developed core skills in deep learning using the Keras library
Examined unsupervised and supervised deep learning models
Covered foundational theories and concepts for beginners
Includes hands-on labs for practical application
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