In this course, you will go in-depth to discover how Machine Learning is used to handle and interpret Big Data. You will get a detailed look at the various ways and methods to create algorithms to incorporate into your business with such tools as Teachable Machine and TensorFlow. You will also learn different ML methods, Deep Learning, as well as the limitations but also how to drive accuracy and use the best training data for your algorithms. You will then explore GANs and VAEs, using your newfound knowledge to engage with AutoML to help you start building algorithms that work to suit your needs. You will also see exclusive interviews with industry leaders, who manage Big Data for companies such as McDonald's and Visa. By the end of this course, you will have learned different ways to code, including how to use no-code tools, understand Deep Learning, how to measure and review errors in your algorithms, and how to use Big Data to not only maintain customer privacy but also how to use this data to develop different strategies that will drive your business.
The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.
- 5 stars81.63%
- 4 stars12.24%
- 3 stars2.04%
- 1 star4.08%
來自AI FUNDAMENTALS FOR NON-DATA SCIENTISTS的熱門評論
Helping me to clear doubts and i feel like getting required information. Thank you Coursera and Professinal Team.
Excellent information and presentation. The only drawback in being so thought provoking, the format does not allow for active convesations in expanding understanding or ideas.
Excellent introduction to the basic concepts of using AI and Machine Learning in a business context.
關於 AI For Business 專項課程
This specialization will provide learners with the fundamentals of using Big Data, Artificial Intelligence, and Machine Learning and the various areas in which you can deploy them to support your business. You'll cover ethics and risks of AI, designing governance frameworks to fairly apply AI, and also cover people management in the fair design of HR functions within Machine Learning. You'll also learn effective marketing strategies using data analytics, and how personalization can enhance and prolong the customer journey and lifecycle. Finally, you will hear from industry leaders who will provide you with insights into how AI and Big Data are revolutionizing the way we do business.