Coursera

Exploring AI Possibilities (Coursera)

Offered by Fred Hutchinson Cancer Center,
Exploring AI Possibilities (Coursera)

This course on Exploring AI Possibilities for Decision Makers explores the growing use of AI across disciplines and its potential benefits and challenges. The course covers necessary context, such as discussing what AI is, how it works, and key definitions in AI. Through exploring the many AI possibilities at your fingertips, you will build leadership skills for helping your business or community work more efficiently, creatively, and ethically.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

Unique Features of this Course

  • Explanation of AI with minimal jargon
  • Beginner friendly for those who want to get started learning how to leverage generative AI
  • Focus on the application for busy workplace leaders
  • Emphasis on responsible and ethical use of AI
  • Useful ideas for how to leverage tools to make your work better and more efficient
  • A fun and playful approach to learning

Key Words
Artificial Intelligence (AI), Generative AI, Large Language Models (LLMs), Data Science, Technology Leadership, Technology-driven Workplace

Intended Audience

  • Professionals looking to understand AI at a strategic level
  • Industry and non-profit leaders and decision makers
  • Anyone curious about how AI can be harnessed for technology

Learning Objectives

  • Define AI using our three part framework: the data, algorithm, and interface
  • Identify common technologies and whether or not they are AI
  • Explain the essential "behind the scenes" technology of how AI works
  • Identify possibilities for using AI while understanding its limitations

Syllabus

Exploring AI Possibilities
This course on Exploring AI Possibilities for Decision Makers explores the growing use of AI across disciplines and its potential benefits and challenges.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Deep learning in Electronic Health Records - CDSS 2 (Coursera) Coursera
University of Glasgow

Deep learning in Electronic Health Records - CDSS 2 (Coursera)

Data Science

Overview of the main principles of Deep Learning along with common architectures. Formulate the problem for time-series classification and apply it to vital signals such as ECG. Applying this methods in Electronic Health Records is challenging due to the missing values and the heterogeneity in EHR, which include both continuous, ordinal and categorical variables. Subsequently, explore imputation techniques and different encoding strategies to address these issues. Apply these approaches to formulate clinical prediction benchmarks derived from information available in MIMIC-III database.

Jun 22nd 2026
4 Weeks
Artificial Intelligence Deep Learning Recurrent Neural Networks
Details
AI Applications in Marketing and Finance (Coursera) Coursera
University of Pennsylvania

AI Applications in Marketing and Finance (Coursera)

Economics & Finance Business

In this course, you will learn about AI-powered applications that can enhance the customer journey and extend the customer lifecycle. You will learn how this AI-powered data can enable you to analyze consumer habits and maximize their potential to target your marketing to the right people. You will also learn about fraud, credit risks, and how AI applications can also help you combat the ever-challenging landscape of protecting consumer data.

Jun 22nd 2026
4 Weeks
Finance Marketing Artificial Intelligence
Details
Scalable Machine Learning on Big Data using Apache Spark (Coursera) Coursera
IBM

Scalable Machine Learning on Big Data using Apache Spark (Coursera)

Data Science

This course will empower you with the skills to scale data science and machine learning (ML) tasks on Big Data sets using Apache Spark. Most real world machine learning work involves very large data sets that go beyond the CPU, memory and storage limitations of a single computer. Apache Spark is an open source framework that leverages cluster computing and distributed storage to process extremely large data sets in an efficient and cost effective manner. Therefore an applied knowledge of working with Apache Spark is a great asset and potential differentiator for a Machine Learning engineer.

Jun 22nd 2026
4 Weeks
Artificial Intelligence Machine Learning Big Data
Details
The AI Ladder: A Framework for Deploying AI in your Enterprise (Coursera) Coursera
IBM

The AI Ladder: A Framework for Deploying AI in your Enterprise (Coursera)

Management & Leadership Business

This course is intended for business and technical professionals involved in strategic decision-making focused on bringing AI into their enterprises. Through the use of a conceptual model called “The AI Ladder”, participants in this course will learn the requirements, terms and concepts associated with successfully developing and deploying AI solutions in their enterprises.

Jun 22nd 2026
1 Week
Innovation Management Artificial Intelligence
Details
Learn to code with AI (Coursera) Coursera
Scrimba

Learn to code with AI (Coursera)

CS: Software Engineering

Imagine waking up tomorrow as a web developer. What would you want to build? With AI tools like ChatGPT, you're already a developer, regardless of your experience, if you know how to work with them. So in this course, you'll build functional, interactive front-end projects while learning how to write effective prompts and debug and refine your code with the help of AI.

Jun 24th 2026
2 Weeks
Programming Artificial Intelligence HTML
Details
Navigating Generative AI: A CEO Playbook (Coursera) Coursera
Coursera Instructor Network

Navigating Generative AI: A CEO Playbook (Coursera)

Robotics & Computer Vision

Created by Coursera's CEO, this course is your key to unlocking the transformative power of GenAI. It features hands-on labs with access to Google Gemini Pro in a secure, private environment. These labs not only teach you how to use GenAI, but also how to apply it to design your GenAI strategy, identify specific opportunities to enhance customer value, increase productivity, and navigate risks and ethical considerations in order to move quickly but safely in adopting generative AI.

Jun 25th 2026
5-12 Weeks
Artificial Intelligence CEO AI
Details
AI Fundamentals for Non-Data Scientists (Coursera) Coursera
University of Pennsylvania

AI Fundamentals for Non-Data Scientists (Coursera)

Management & Leadership

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.

Jun 22nd 2026
4 Weeks
Artificial Intelligence Machine Learning Big Data
Details
AI Workflow: Machine Learning, Visual Recognition and NLP (Coursera) Coursera
IBM

AI Workflow: Machine Learning, Visual Recognition and NLP (Coursera)

Data Science

This is the fourth course in the IBM AI Enterprise Workflow Certification specialization. You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones. Course 4 covers the next stage of the workflow, setting up models and their associated data pipelines for a hypothetical streaming media company.

Jun 22nd 2026
2 Weeks
Artificial Intelligence NLP Machine Learning
Details
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera) Coursera
DeepLearning.AI

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (Coursera)

CS: Software Engineering Computer Science

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.

Jun 22nd 2026
4 Weeks
Artificial Intelligence Machine Learning Neural Networks
Details