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IBM AI Academy
The Generative AI for Executives and Business Leaders, presented by IBM AI Academy, explores topics and assets that span three core learning areas: strategic essentials, key elements for enterprise AI, and how to put AI to work.
This course is designed for executives and business leaders. In addition, line of business leaders and practitioners curious about the rapidly developing field of generative AI and its capabilities across industries and domains can benefit by taking the course.
Register for this course and see more details by visiting:
OpenCourser.com/course/j5d2j3/introduction
What's inside
Learning objectives
- Understand the history and impact of generative ai for business.
- Learn about the importance of your data in relation to generative ai.
- Know the importance of trusted, transparent and governed ai.
- Apply generative ai to key use cases like customer service and application modernization.
- Understand the history and impact of generative ai for business.
- Learn about the importance of your data in relation to generative ai.
- Know the importance of trusted, transparent and governed ai.
- Apply generative ai to key use cases like customer service and application modernization.
Syllabus
Module 1: Generative AI for Business Leaders: Overview
Lesson 0: Welcome to the course
Lesson 1: Strategic essentials
Lesson 2: Elements of AI in enterprise
Read more
Syllabus
Module 1: Generative AI for Business Leaders: Overview
Lesson 0: Welcome to the course
Lesson 1: Strategic essentials
Lesson 2: Elements of AI in enterprise
Read more
Lesson 3: Putting AI to work
Lesson 4: Final quiz and course wrap up
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches the importance of trusted, transparent, and governed AI, which is critical for responsible implementation in business
Explores the strategic essentials of generative AI for executives and business leaders, providing valuable insights for decision-making
Introduces key elements of enterprise AI, helping learners understand how generative AI fits into larger organizational strategies
Provides practical guidance on applying generative AI to key use cases, such as customer service and application modernization
Examines the history and impact of generative AI for business, offering a comprehensive understanding of its evolution and significance
Save this course
Save Introduction to Generative AI for Executives and Business Leaders to your list so you can find it easily later:
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Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Introduction to Generative AI for Executives and Business Leaders with these
activities:
Review elements of Artificial Intelligence
Show steps
Start the course off on the right foot by revisiting the basics and improving your familiarity with AI
Browse courses on
Artificial Intelligence
Show steps
-
Reread your old AI notes
-
Watch videos on YouTube about the history of AI
-
Take practice quizzes on AI concepts
Review probability and statistics
Show steps
Review the basics of probability and statistics to strengthen your understanding of generative AI models.
Browse courses on
Statistics
Show steps
-
Go through your notes or textbooks on probability and statistics.
-
Solve practice problems to test your understanding.
-
Take an online quiz or assessment to gauge your proficiency.
Follow online courses or tutorials on generative AI
Show steps
Supplement your learning by exploring online courses or tutorials that provide step-by-step guidance on generative AI concepts and techniques.
Show steps
-
Search for reputable online platforms or MOOCs offering generative AI courses.
-
Enroll in a course that aligns with your interests and learning goals.
-
Follow the course modules, complete assignments, and engage in discussions.
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Build a generative AI model using a tutorial
Show steps
Gain practical experience by building a generative AI model from scratch following a structured guide
Browse courses on
Generative AI Models
Show steps
-
Find a well-rated tutorial on generative AI modeling
-
Follow the tutorial steps carefully
-
Troubleshoot any issues you encounter
-
Deploy and test your generative AI model
Join a study group or discussion forum on generative AI
Show steps
Engage with peers by joining study groups or discussion forums to share knowledge, collaborate on projects, and deepen your understanding of generative AI.
Show steps
-
Search for online or in-person study groups or discussion forums dedicated to generative AI.
-
Join the group or forum and actively participate in discussions.
-
Share your insights, ask questions, and collaborate with other members.
Experiment with generative AI platforms
Show steps
Gain hands-on experience by exploring and experimenting with different generative AI platforms and their capabilities.
Show steps
-
Sign up for free trials or use open-source generative AI platforms.
-
Try out different models and techniques to generate text, images, or code.
-
Experiment with different parameters and settings to optimize results.
Create a slide deck on AI use cases
Show steps
Deepen your understanding of generative AI's usage in business by creating your own informative content
Browse courses on
AI use cases
Show steps
-
Brainstorm a list of AI use cases in various industries and sectors
-
Gather relevant data and insights to support each use case
-
Design visually appealing and informative slides
-
Present your slide deck to an audience
Develop a generative AI use case
Show steps
Create a practical use case for generative AI within a specific industry or domain, outlining its potential benefits and challenges.
Browse courses on
Generative AI
Show steps
-
Identify a specific industry or domain where generative AI can be applied.
-
Research and understand the challenges and opportunities within that domain.
-
Develop a detailed use case that outlines the problem, solution, and expected outcomes.
-
Present your use case to a group or mentor for feedback.
Attend a workshop on Generative AI for Business
Show steps
Enhance your understanding by engaging in hands-on learning and networking with industry experts
Browse courses on
Generative AI Applications
Show steps
-
Find and register for a relevant workshop
-
Attend all sessions and actively participate
-
Ask questions and connect with experts
-
Implement what you learned in your work
Practice applying generative AI to business problems
Show steps
Put your generative AI knowledge to the test by solving realistic business challenges
Browse courses on
AI Applications
Show steps
-
Identify a real-world business problem
-
Research and explore different generative AI techniques
-
Develop and implement a generative AI solution
-
Evaluate the effectiveness of your solution
Review elements of Artificial Intelligence
Show steps
Start the course off on the right foot by revisiting the basics and improving your familiarity with AI
Browse courses on
Artificial Intelligence
Show steps
Show steps
Show steps
- Reread your old AI notes
- Watch videos on YouTube about the history of AI
- Take practice quizzes on AI concepts
Review probability and statistics
Show steps
Review the basics of probability and statistics to strengthen your understanding of generative AI models.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Go through your notes or textbooks on probability and statistics.
- Solve practice problems to test your understanding.
- Take an online quiz or assessment to gauge your proficiency.
Follow online courses or tutorials on generative AI
Show steps
Supplement your learning by exploring online courses or tutorials that provide step-by-step guidance on generative AI concepts and techniques.
Show steps
Show steps
Show steps
- Search for reputable online platforms or MOOCs offering generative AI courses.
- Enroll in a course that aligns with your interests and learning goals.
- Follow the course modules, complete assignments, and engage in discussions.
Seven other activities
Expand to see all activities and additional details
Show all ten activities
Build a generative AI model using a tutorial
Show steps
Gain practical experience by building a generative AI model from scratch following a structured guide
Browse courses on
Generative AI Models
Show steps
Show steps
Show steps
- Find a well-rated tutorial on generative AI modeling
- Follow the tutorial steps carefully
- Troubleshoot any issues you encounter
- Deploy and test your generative AI model
Join a study group or discussion forum on generative AI
Show steps
Engage with peers by joining study groups or discussion forums to share knowledge, collaborate on projects, and deepen your understanding of generative AI.
Show steps
Show steps
Show steps
- Search for online or in-person study groups or discussion forums dedicated to generative AI.
- Join the group or forum and actively participate in discussions.
- Share your insights, ask questions, and collaborate with other members.
Experiment with generative AI platforms
Show steps
Gain hands-on experience by exploring and experimenting with different generative AI platforms and their capabilities.
Show steps
Show steps
Show steps
- Sign up for free trials or use open-source generative AI platforms.
- Try out different models and techniques to generate text, images, or code.
- Experiment with different parameters and settings to optimize results.
Create a slide deck on AI use cases
Show steps
Deepen your understanding of generative AI's usage in business by creating your own informative content
Browse courses on
AI use cases
Show steps
Show steps
Show steps
- Brainstorm a list of AI use cases in various industries and sectors
- Gather relevant data and insights to support each use case
- Design visually appealing and informative slides
- Present your slide deck to an audience
Develop a generative AI use case
Show steps
Create a practical use case for generative AI within a specific industry or domain, outlining its potential benefits and challenges.
Browse courses on
Generative AI
Show steps
Show steps
Show steps
- Identify a specific industry or domain where generative AI can be applied.
- Research and understand the challenges and opportunities within that domain.
- Develop a detailed use case that outlines the problem, solution, and expected outcomes.
- Present your use case to a group or mentor for feedback.
Attend a workshop on Generative AI for Business
Show steps
Enhance your understanding by engaging in hands-on learning and networking with industry experts
Browse courses on
Generative AI Applications
Show steps
Show steps
Show steps
- Find and register for a relevant workshop
- Attend all sessions and actively participate
- Ask questions and connect with experts
- Implement what you learned in your work
Practice applying generative AI to business problems
Show steps
Put your generative AI knowledge to the test by solving realistic business challenges
Browse courses on
AI Applications
Show steps
Show steps
Show steps
- Identify a real-world business problem
- Research and explore different generative AI techniques
- Develop and implement a generative AI solution
- Evaluate the effectiveness of your solution
Career center
Learners who complete Introduction to Generative AI for Executives and Business Leaders will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists analyze data to extract insights and build predictive models. They use a variety of statistical and machine learning techniques to solve business problems. The course can help you build a foundation in generative AI, which is a rapidly growing field with a high demand for skilled professionals.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build and deploy machine learning models. They work with data scientists to identify the right models for a given problem and then develop and deploy those models in a production environment. The course can help you learn about the key elements of enterprise AI and how to put AI to work in key use cases.
Chief Data Officer
Chief Data Officer
Chief Data Officers oversee an organization's data. They manage data storage, protection, analytics, and reporting to help drive business decisions. The course can help you understand the importance of data in relation to generative AI and how to use data to drive business outcomes.
AI Architect
AI Architect
AI Architects design and build AI systems. They work with business leaders and technical teams to ensure that AI systems are aligned with business goals and that they are scalable, reliable, and secure. The course can help you understand the strategic essentials of AI and how to put AI to work in key use cases.
Chief AI Officer
Chief AI Officer
Chief AI Officers are responsible for developing and executing an organization's AI strategy. They work with business leaders to identify AI use cases and ensure that AI is used ethically and responsibly. The course can help you understand the history and impact of generative AI for business, the importance of trusted, transparent, and governed AI, and how to put AI to work in key use cases.
AI Strategy Consultant
AI Strategy Consultant
AI Strategy Consultants help organizations develop and execute their AI strategies. They work with business leaders to identify AI use cases, develop AI roadmaps, and build AI teams. The course can help you understand the history and impact of generative AI for business, the importance of trusted, transparent, and governed AI, and how to put AI to work in key use cases.
IT Manager
IT Manager
IT Managers are responsible for managing an organization's IT infrastructure. They work with business leaders to ensure that IT systems are aligned with business goals and that they are secure and reliable. The course can help you understand the key elements of enterprise AI and how to put AI to work in key use cases, which can be valuable for IT Managers who want to help their organizations adopt AI.
CIO
CIO
CIOs are responsible for overseeing an organization's IT strategy and operations. They work with business leaders to ensure that IT is aligned with business goals and that it is delivering value to the organization. The course can help you understand the strategic essentials of AI and how to put AI to work in key use cases, which can be valuable for CIOs who want to help their organizations adopt AI.
CEO
CEO
CEOs are responsible for the overall success of an organization. They work with the board of directors to set the strategic direction of the organization and to ensure that the organization is meeting its goals. The course can help you understand the history and impact of generative AI for business, the importance of trusted, transparent, and governed AI, and how to put AI to work in key use cases, which can be valuable for CEOs who want to help their organizations adopt AI.
COO
COO
COOs are responsible for the day-to-day operations of an organization. They work with the CEO to implement the strategic direction of the organization and to ensure that the organization is running smoothly. The course can help you understand the key elements of enterprise AI and how to put AI to work in key use cases, which can be valuable for COOs who want to help their organizations adopt AI.
CMO
CMO
CMOs are responsible for marketing and sales. They work with the CEO to develop and execute the marketing and sales strategy of the organization. The course can help you understand the strategic essentials of AI and how to put AI to work in key use cases, such as customer service and application modernization, which can be valuable for CMOs who want to help their organizations adopt AI.
Business Analyst
Business Analyst
Business Analysts analyze business processes and identify opportunities for improvement. They work with business leaders to develop and implement new solutions. The course can help you understand the history and impact of generative AI for business, the importance of trusted, transparent, and governed AI, and how to put AI to work in key use cases, which can be valuable for Business Analysts who want to help their organizations adopt AI.
CTO
CTO
CTOs are responsible for the technology strategy and operations of an organization. They work with the CEO to ensure that the organization is using technology to its full potential. The course can help you understand the history and impact of generative AI for business, the importance of trusted, transparent, and governed AI, and how to put AI to work in key use cases, which can be valuable for CTOs who want to help their organizations adopt AI.
Product Manager
Product Manager
Product Managers are responsible for developing and launching new products. They work with engineers, designers, and marketers to bring new products to market. The course can help you understand the strategic essentials of AI and how to put AI to work in key use cases, which can be valuable for Product Managers who want to develop AI-powered products.
Data Architect
Data Architect
Data Architects design and build data management systems. They work with data engineers to ensure that data is stored, processed, and analyzed efficiently. The course can help you understand the importance of data in relation to generative AI and how to use data to drive business outcomes.
For more career information including salaries, visit:
OpenCourser.com/course/j5d2j3/introduction
Reading list
We've selected 17 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Introduction to Generative AI for Executives and Business Leaders.
Provides real-world examples of how companies are using AI and ML to solve problems. It covers a wide range of use cases, from customer service to fraud detection.
Explores the impact of AI on the workplace and how businesses can adapt to the changing landscape. It provides practical advice on how to integrate AI into business processes, manage the workforce, and create a culture of innovation.
Provides a practical guide to using AI in business. It covers topics such as AI applications, data analytics, machine learning, and AI ethics.
Provides a hands-on approach to machine learning using Python libraries such as Scikit-Learn, Keras, and TensorFlow. It covers topics such as data preprocessing, model selection, and hyperparameter tuning.
Practical guide to building deep learning models using Fastai and PyTorch. It provides a step-by-step approach to developing and deploying deep learning solutions for various applications.
Provides a comprehensive guide to deep learning using Python and the Keras library. It covers topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks.
Save
Provides a comprehensive overview of computer vision algorithms and their applications. It covers topics such as image formation, feature extraction, object recognition, and motion analysis.
Save
Provides a comprehensive overview of generative adversarial networks (GANs), a type of generative model that has shown promising results in generating realistic images, text, and other data.
Save
Comprehensive reference on deep learning. It covers the latest advances in the field, and provides a detailed explanation of the underlying mathematics.
Provides a comprehensive overview of statistical learning. It covers the latest advances in the field, and provides a detailed explanation of the underlying mathematics.
Provides a comprehensive overview of pattern recognition and machine learning. It covers the latest advances in the field, and provides a detailed explanation of the underlying mathematics.
Provides a comprehensive overview of reinforcement learning. It covers the latest advances in the field, and provides a detailed explanation of the underlying mathematics.
Provides a comprehensive overview of natural language processing. It covers the latest advances in the field, and provides a detailed explanation of the underlying mathematics.
Provides a comprehensive overview of machine learning from a probabilistic perspective. It covers the latest advances in the field, and provides a detailed explanation of the underlying mathematics.
Provides a comprehensive overview of artificial intelligence. It covers the latest advances in the field, and provides a detailed explanation of the underlying mathematics.
Provides a comprehensive overview of speech and language processing. It covers the latest advances in the field, and provides a detailed explanation of the underlying mathematics.
Provides a comprehensive overview of computer vision. It covers the latest advances in the field, and provides a detailed explanation of the underlying mathematics.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/j5d2j3/introduction
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Effort
2 to 3 hours per week for 1 week
Level
Introductory
Via
edX
Institution
IBM
Instructor
IBM AI Academy
Session
April 15, 2024
- December 31, 2024
Language
English
Transcript
English
Good to know
Teaches the importance of trusted, transparent, and governed AI, which is critical for responsible implementation in business
Explores the strategic essentials of generative AI for executives and business leaders, providing valuable insights for decision-making
Introduces key elements of enterprise AI, helping learners understand how generative AI fits into larger organizational strategies
Provides practical guidance on applying generative AI to key use cases, such as customer service and application modernization
Examines the history and impact of generative AI for business, offering a comprehensive understanding of its evolution and significance
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