AI Fundamentals for Non-Data Scientists

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.

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Syllabus

Syllabus - What you will learn from this course
Week 1
Module 1 – Big Data and Artificial Intelligence
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.
Week 2
Module 2 – Training and Evaluating Machine Learning Algorithms
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.
Week 3
Module 3 – ML Application and Emerging Methods
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.
Week 4
Module 4 - Industry Interview
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.

FAQ

When will I have access to the lectures and assignments?

Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

What will I get if I subscribe to this Specialization?

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Reviews

This course was extremely helpful in presenting the basics of AI in a way that was relevant to different kinds of business decisions.

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.

Helping me to clear doubts and i feel like getting required information. Thank you Coursera and Professinal Team.

Excellent introduction to the basic concepts of using AI and Machine Learning in a business context.