Deep Learning Fundamentals with Keras from edX

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Looking to kickstart a career in deep learning? Look no further. This course will introduce you to the field of deep learning and teach you the fundamentals. You will learn about some of the exciting applications of deep learning, the basics fo neural networks, different deep learning models, and how to build your first deep learning model using the easy yet powerful library Keras.

This course will presentsimplified explanations to some oftoday's hottest topics in data science, including:

What is deep learning?
How do neural networks learn and what are activation functions?
What are deep learning libraries and how do they compare to one another?
What are supervised and unsupervised deep learning models?
How to use Keras to build, train, and test deep learning models?

The demand fordeep learning skills-- and the job salaries of deep learning practitioners -- arecontinuing to grow, as AI becomes more pervasive in our societies. This course will help you build the knowledge you need to future-proofyour career.

What you'll learn

You will learn about exciting applications of deep learning and why it is really rewarding to learn how to leverage deep learning skills.
You will learn about neural networks and how theylearn and update their weights and biases.
You will learn about thevanishing gradient problem.
You will learn about building a regression model using the Keras library.
You will learn about building a classification model using the Keras library.
You will learn about supervised deep learning models, such as convolutional neural networks and recurrent neural networks, and how to build a convolutional neural network using the Keras library.
You will learn about unsupervised learning models such as autoencoders.

What's inside

Learning objectives

You will learn about exciting applications of deep learning and why it is really rewarding to learn how to leverage deep learning skills.
You will learn about neural networks and how theylearn and update their weights and biases.
You will learn about thevanishing gradient problem.
You will learn about building a regression model using the keras library.

You will learn about building a classification model using the keras library.
You will learn about supervised deep learning models, such as convolutional neural networks and recurrent neural networks, and how to build a convolutional neural network using the keras library.
You will learn about unsupervised learning models such as autoencoders.

You will learn about exciting applications of deep learning and why it is really rewarding to learn how to leverage deep learning skills.
You will learn about neural networks and how theylearn and update their weights and biases.
You will learn about thevanishing gradient problem.
You will learn about building a regression model using the keras library.
You will learn about building a classification model using the keras library.
You will learn about supervised deep learning models, such as convolutional neural networks and recurrent neural networks, and how to build a convolutional neural network using the keras library.
You will learn about unsupervised learning models such as autoencoders.

Syllabus

Module1 - Introduction to Deep Learning - Introduction to Deep Learning - Biological Neural Networks - Artificial Neural Networks - Forward Propagation

Module2 -Artificial Neural Networks - Gradient Descent - Backpropagation - Vanishing Gradient - Activation Functions

Module3 - Deep Learning Libraries - Introduction to Deep Learning Libraries - Regression Models with Keras - Classification Models with Keras

Module4 -Deep Learning Models - Shallow and Deep Neural Networks - Convolutional Neural Networks - Recurrent Neural Networks - Autoencoders

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Targets both beginners learning about deep learning and practitioners who wish to strengthen their foundational skills

Taught by Alex Aklson, who has experience in deep learning

Provides a comprehensive overview of deep learning concepts and techniques

Leverages the Keras library for practical implementation of deep learning models, making it accessible to beginners

Covers advanced deep learning models such as convolutional neural networks and recurrent neural networks

Offers opportunities to build and train deep learning models hands-on, fostering practical skills development

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 Deep Learning Fundamentals with Keras with these activities:

Review Neural Networks

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Review the basics of neural networks before taking this course to ensure a stronger foundation and smoother learning experience.

Browse courses on Neural Networks

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Identify the different types of neural networks.
Understand how neural networks learn.
Be able to apply neural networks to simple problems.

Review Deep Learning Book

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Supplement your learning by reading a book on deep learning to gain a deeper understanding of the concepts and techniques.

View Deep Learning on Amazon

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Find a book on deep learning that is appropriate for your level of knowledge.
Read the book carefully and take notes.
Complete any exercises or projects that are included in the book.

Network with Deep Learning Professionals

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Network with other deep learning professionals to learn about new trends and opportunities in the field.

Browse courses on Networking

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Attend meetups and conferences related to deep learning.
Join online communities and forums dedicated to deep learning.
Reach out to deep learning professionals on LinkedIn.

Four other activities

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Show all seven activities

Practice Building Neural Networks

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Build several neural networks using Keras to solidify your understanding of the process and improve your skills.

Browse courses on Keras

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Create a simple neural network to solve a regression problem.
Create a more complex neural network to solve a classification problem.
Experiment with different neural network architectures.

Follow Tutorials on Deep Learning

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Supplement your learning by following tutorials on deep learning to gain a deeper understanding of the concepts and techniques.

Browse courses on TensorFlow

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Find a tutorial on a specific deep learning topic that you are interested in.
Follow the tutorial step-by-step and complete all of the exercises.
Apply what you have learned from the tutorial to a project of your own.

Attend a Deep Learning Workshop

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Attend a deep learning workshop to learn from experts and network with other professionals in the field.

Show steps

Find a deep learning workshop that is relevant to your interests.
Register for the workshop and pay the registration fee.
Attend the workshop and participate in all of the activities.

Mentor a Junior Deep Learning Learner

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Share your knowledge and skills with a junior deep learning learner to help them succeed in their learning journey.

Browse courses on Mentoring

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Find a junior deep learning learner who is looking for a mentor.
Set up regular meetings with your mentee to discuss their progress and provide guidance.
Answer your mentee's questions and provide feedback on their work.

Career center

Learners who complete Deep Learning Fundamentals with Keras will develop knowledge and skills that may be useful to these careers:

Deep Learning Engineer

Deep Learning Engineers design, develop, and maintain deep learning models. Deep Learning Fundamentals with Keras can help Deep Learning Engineers understand the fundamentals of deep learning and how to build deep learning models using Keras, a powerful and popular deep learning library.

See salaries and explore the career path for Deep Learning Engineer

Machine Learning Engineer

Machine Learning Engineers design, develop, and maintain machine learning models. They use a variety of techniques to build models that can learn from data and make predictions. Deep Learning Fundamentals with Keras can help Machine Learning Engineers build a strong foundation in the field of deep learning, which is a powerful technique for building machine learning models. It covers the basics of neural networks, different deep learning models, and how to build deep learning models using the easy yet powerful library Keras.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists collect, organize, analyze, and interpret large amounts of data in order to extract meaningful insights and patterns. This information can be used to better understand customer needs, improve business processes, and develop new products or services. Deep Learning Fundamentals with Keras can help Data Scientists build a strong foundation in the field of deep learning, which is a powerful technique for analyzing large and complex datasets. It covers the basics of neural networks, different deep learning models, and how to build deep learning models using the easy yet powerful library Keras.

See salaries and explore the career path for Data Scientist

Artificial Intelligence Engineer

Artificial Intelligence Engineers design, develop, and maintain artificial intelligence systems. Deep Learning Fundamentals with Keras can help Artificial Intelligence Engineers build a strong foundation in the field of deep learning, which is a powerful technique for building AI systems. It covers the basics of neural networks, different deep learning models, and how to build deep learning models using the easy yet powerful library Keras.

See salaries and explore the career path for Artificial Intelligence Engineer

Data Analyst

Data Analysts collect, organize, analyze, and interpret data in order to extract meaningful insights and patterns. Deep Learning Fundamentals with Keras can help Data Analysts build a strong foundation in the field of deep learning, which is a powerful technique for analyzing large and complex datasets. It covers the basics of neural networks, different deep learning models, and how to build deep learning models using the easy yet powerful library Keras.

See salaries and explore the career path for Data Analyst

Marketing Analyst

Marketing Analysts research, analyze, and interpret marketing data in order to develop and implement marketing campaigns. Deep Learning Fundamentals with Keras can help Marketing Analysts build a strong foundation in the field of deep learning, which is a powerful technique for analyzing large and complex marketing datasets. It covers the basics of neural networks, different deep learning models, and how to build deep learning models using the easy yet powerful library Keras.

See salaries and explore the career path for Marketing Analyst

Product Manager

Product Managers are responsible for the development and management of products. They work with stakeholders to define product requirements, develop product roadmaps, and track product performance. Deep Learning Fundamentals with Keras can help Product Managers build a foundation in the field of deep learning, which is a powerful technique for building products that can learn from data and make predictions.

See salaries and explore the career path for Product Manager

Consultant

Consultants provide advice and guidance to businesses on a variety of topics, including deep learning. Deep Learning Fundamentals with Keras can help Consultants build a strong foundation in the field of deep learning, which is a powerful technique for solving business problems. It covers the basics of neural networks, different deep learning models, and how to build deep learning models using the easy yet powerful library Keras.

See salaries and explore the career path for Consultant

Customer Success Manager

Customer Success Managers work with customers to ensure that they are successful in using a company's products or services. Deep Learning Fundamentals with Keras can help Customer Success Managers build a foundation in the field of deep learning, which is a powerful technique for building customer success tools and techniques that can learn from data and make predictions.

See salaries and explore the career path for Customer Success Manager

Project Manager

Project Managers are responsible for planning, executing, and closing projects. They work with stakeholders to define project goals, develop project plans, and track project progress. Deep Learning Fundamentals with Keras can help Project Managers build a foundation in the field of deep learning, which is a powerful technique for building project management tools and techniques that can learn from data and make predictions.

See salaries and explore the career path for Project Manager

Sales Analyst

Sales Analysts research, analyze, and interpret sales data in order to develop and implement sales strategies. Deep Learning Fundamentals with Keras can help Sales Analysts build a strong foundation in the field of deep learning, which is a powerful technique for analyzing large and complex sales datasets. It covers the basics of neural networks, different deep learning models, and how to build deep learning models using the easy yet powerful library Keras.

See salaries and explore the career path for Sales Analyst

Business Analyst

Business Analysts research, analyze, and document business processes and systems. They work with stakeholders to identify business needs and develop solutions to improve efficiency and effectiveness. Deep Learning Fundamentals with Keras can help Business Analysts build a foundation in the field of deep learning, which is a powerful technique for analyzing large and complex datasets. It covers the basics of neural networks, different deep learning models, and how to build deep learning models using the easy yet powerful library Keras.

See salaries and explore the career path for Business Analyst

Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve business problems. They work with stakeholders to identify inefficiencies and develop solutions to improve operations. Deep Learning Fundamentals with Keras can help Operations Research Analysts build a foundation in the field of deep learning, which is a powerful technique for analyzing large and complex datasets. It covers the basics of neural networks, different deep learning models, and how to build deep learning models using the easy yet powerful library Keras.

See salaries and explore the career path for Operations Research Analyst

Software Engineer

Software Engineers design, develop, and maintain software systems. Deep Learning Fundamentals with Keras can help Software Engineers build a foundation in the field of deep learning, which is a powerful technique for building software systems that can learn from data and make predictions.

See salaries and explore the career path for Software Engineer

Financial Analyst

Financial Analysts research, analyze, and interpret financial data in order to make investment recommendations. Deep Learning Fundamentals with Keras can help Financial Analysts build a strong foundation in the field of deep learning, which is a powerful technique for analyzing large and complex financial datasets. It covers the basics of neural networks, different deep learning models, and how to build deep learning models using the easy yet powerful library Keras.

See salaries and explore the career path for Financial Analyst