University of Pennsylvania
AI Fundamentals for Non-Data Scientists
University of Pennsylvania

AI Fundamentals for Non-Data Scientists

This course is part of AI For Business Specialization

Taught in English

Some content may not be translated

Kartik Hosanagar
Prasanna Tambe

Instructors: Kartik Hosanagar

23,686 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.8

(310 reviews)

7 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

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Assessments

3 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.8

(310 reviews)

7 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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This course is part of the AI For Business Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
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There are 4 modules in this course

In this module, you will be introduced to Big Data and examine how machine learning is used throughout various business segments. You will also learn how data is analyzed and extracted, and how digital technologies have been used to expand and transform businesses. You will also get a detailed look at data management tools and how they are best implemented and the value of data warehouses. By the end of this module, you will have gained insight into how machine learning can be used as a general-purpose technology, and some best techniques and practices for data mining.

What's included

11 videos1 reading1 quiz

In this module, you will get an in-depth look at contrasting Machine Learning methods, including logistic regression and neural nets. You will also learn about Deep Learning and its relationship to neural networks and how to best optimize Machine Learning algorithms. Lastly, you will be introduced to loss functions and how to best measure and review errors to maintain the integrity of your algorithms. By the end of this module, you will have learned about Machine Learning methods, the limitations and value of Deep Learning, how best to drive precision and accuracy in algorithms, and how to get the best training data for those algorithms.

What's included

13 videos1 reading1 quiz

In this module, you will take a look at Machine Learning within natural language processing and using generative modeling to create new data. You will also focus on AutoML and how to best utilize automated processes to make your algorithms more efficient. You will also review the no-code Machine Learning tool Teachable Machine, which serves to make Deep and Machine Learning more accessible. By the end of this module, you will be able to use AutoML in your algorithms and be able to navigate and use Teachable Machine in practice for no-code solutions to building an algorithm.

What's included

8 videos1 reading1 quiz

In this module, you will hear from an industry leader and gain valuable insight into data sampling and building realistic usable models. Ed Lee, VP of Global Menu Strategy & Global Marketing at McDonald's, will allow you to review real-world solutions and how they handle data issues as one of the most successful global brands. By the end of this module, you will have heard from a top industry expert in their field and gained firsthand knowledge and understanding of how Big Data plays into maintaining privacy in data and also utilizing that data to enhance your marketing, content, and refine your algorithms.

What's included

1 video1 peer review

Instructors

Instructor ratings
4.8 (111 ratings)
Kartik Hosanagar
University of Pennsylvania
8 Courses207,067 learners

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