Course Summary
This course provides an introduction to how deep learning can be applied to business problems. It covers the fundamentals of neural networks, convolutional neural networks, and recurrent neural networks, and how they can be used in marketing, finance, and operations fields.Key Learning Points
- Learn how deep learning can be applied to business problems
- Understand the fundamentals of neural networks, CNNs, and RNNs
- Explore real-world applications in marketing, finance, and operations fields
Related Topics for further study
Learning Outcomes
- Understand how deep learning can be applied to business problems
- Develop skills in building neural networks, CNNs, and RNNs
- Apply deep learning techniques to real-world business scenarios
Prerequisites or good to have knowledge before taking this course
- Basic understanding of linear algebra and calculus
- Familiarity with Python and machine learning concepts
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Applied Data Science with Python
- Machine Learning
Related Education Paths
Related Books
Description
Your smartphone, smartwatch, and automobile (if it is a newer model) have AI (Artificial Intelligence) inside serving you every day. In the near future, more advanced “self-learning” capable DL (Deep Learning) and ML (Machine Learning) technology will be used in almost every aspect of your business and industry. So now is the right time to learn what DL and ML is and how to use it in advantage of your company. This course has three parts, where the first part focuses on DL and ML technology based future business strategy including details on new state-of-the-art products/services and open source DL software, which are the future enablers. The second part focuses on the core technologies of DL and ML systems, which include NN (Neural Network), CNN (Convolutional NN), and RNN (Recurrent NN) systems. The third part focuses on four TensorFlow Playground projects, where experience on designing DL NNs can be gained using an easy and fun yet very powerful application called the TensorFlow Playground. This course was designed to help you build business strategies and enable you to conduct technical planning on new DL and ML services and products.
Outline
- Deep Learning Products & Services
- 1.0 Introduction to Deep Learning for Business
- 1.1 Future Industry Evolution & Artificial Intelligence
- 1.2 IBM Watson
- 1.3 Amazon Echo, Echo Dot, Alexa
- 1.4 LettuceBot / 1.5 Athelas / 1.6 AIVA (Artificial Intelligence Virtual Artist) / 1.7 Apple watchOS 4, HomePod speaker
- Ungraded Quiz
- Graded Quiz
- Business with Deep Learning & Machine Learning
- 2.1 Business Considerations in the Machine Learning Era
- 2.2 Business Strategy with Machine Learning & Deep Learning
- 2.3 Why is Deep Learning Popular Now?
- 2.4 Characteristics of Businesses with DL & ML
- Ungraded Quiz
- Graded Quiz
- Deep Learning Computing Systems & Software
- 3.1 Deep Learning Open Source Software / 3.2 Google TensorFlow
- 3.3 Microsoft CNTK (Cognitive Toolkit) / 3.4 NVIDIA DGX-1
- 3.5 Google AlphaGo
- 3.6 ILSVRC (ImageNet Large Scale Visual Recognition Challenge)
- Ungraded Quiz
- Graded Quiz
- Basics of Deep Learning Neural Networks
- 4.1 What is Deep Learning & Machine Learning?
- 4.2 NN (Neural Network)
- 4.3 Neural Network Learning (Backpropagation)
- Ungraded Quiz
- Graded Quiz
- Deep Learning with CNN & RNN
- 5.1 Deep Learning with CNN (Convolutional Neural Network)
- 5.2 Deep Learning with RNN (Recurrent Neural Network)
- Ungraded Quiz
- Graded Quiz
- Deep Learning Project with TensorFlow Playground
- 6.1 Introduction to TensorFlow Playground
- 6.2 Project Setup, Project 1, and Project 2
- 6.3 Project 3 and Project 4
Summary of User Reviews
The Deep Learning for Business course on Coursera has received positive reviews from many users. It is well-structured and informative, providing a comprehensive understanding of the topic. One key aspect that many users thought was good is the practical approach taken in teaching the material.Pros from User Reviews
- The course is well-structured and easy to follow
- The instructors are knowledgeable and engaging
- The practical approach provides real-world examples and applications
- The course is applicable to a variety of industries
- The course includes assignments and quizzes to reinforce learning
Cons from User Reviews
- The course may be too basic for those with prior knowledge of deep learning
- Some users found the course content to be repetitive
- The course may not be suitable for those looking for a more technical or advanced course
- The course may be too time-consuming for some users
- Some users found the course to be too expensive
Jong-Moon Chung
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