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The Building a Generative AI Ready Organization course provides components needed for a successful organizational adoption of Generative AI. This course focuses on business leaders and other decision-makers currently or potentially involved in Generative AI projects.

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What's inside

Syllabus

Building a Generative AI Ready Organization

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides components needed for a successful organizational adoption of Generative AI
Focuses on business leaders and other decision-makers currently or potentially involved in Generative AI projects

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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 Building a Generative AI-Ready Organization with these activities:
Review the basics of generative AI
Reviewing the basics of generative AI can help you build a stronger foundation for the course, making it easier to understand the more advanced concepts.
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  • Read articles and watch videos about generative AI.
  • Review your notes from previous courses or online resources on AI.
  • Take practice quizzes or tests on generative AI.
Review Course Syllabus
Build a foundation for course topics.
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  • Read the course syllabus carefully.
  • Identify the course learning objectives.
Complete AWS Cloud Practitioner Certification Practice Exam
Reinforce understanding of AWS concepts.
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  • Take the practice exam.
  • Review your results and identify areas for improvement.
Six other activities
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Follow a tutorial on building a generative AI model
Following a tutorial on building a generative AI model can help you gain hands-on experience and a deeper understanding of the process.
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  • Find a tutorial that is appropriate for your skill level.
  • Follow the steps in the tutorial carefully.
  • Test your model and make adjustments as needed.
Participate in a peer discussion group
Participating in a peer discussion group can help you connect with other students, share ideas, and learn from each other.
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  • Find a peer discussion group that is focused on generative AI.
  • Attend the group's meetings regularly.
  • Participate in the discussions.
Write a blog post or article about generative AI
Writing a blog post or article about generative AI can help you solidify your understanding of the concept and share your knowledge with others.
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  • Choose a topic that you are interested in.
  • Research your topic.
  • Write your blog post or article.
  • Publish your blog post or article.
Mentor other generative AI students or enthusiasts
Mentoring others can help you solidify your own understanding of generative AI and make a positive impact on the community.
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  • Identify someone who could benefit from your mentorship.
  • Set up a regular meeting time.
  • Provide guidance and support.
  • Celebrate your mentee's successes.
Build a simple generative AI model
Building a simple generative AI model can help you apply the concepts you have learned in the course and test your understanding.
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  • Choose a dataset that is appropriate for your model.
  • Select an appropriate model architecture.
  • Train your model on the dataset.
  • Test your model and make adjustments as needed.
Start a project that uses generative AI
Starting a project that uses generative AI can help you apply the concepts you have learned in the course and build a valuable portfolio piece.
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  • Choose a project idea.
  • Create a project plan.
  • Implement your project.
  • Test your project.
  • Deploy your project.

Career center

Learners who complete Building a Generative AI-Ready Organization will develop knowledge and skills that may be useful to these careers:
AI Research Scientist
AI Research Scientists research and develop new AI technologies. This course provides a solid grounding in Generative AI, making it easier for those interested in the subfield to dive deeper into its complexities.
AI Consultant
AI Consultants advise clients on the use of AI technologies. This course provides a strong foundation in Generative AI, making it easier for those interested in the subfield to dive deeper into its complexities.
AI Engineer
AI Engineers design, build, and maintain AI systems. This course provides a strong foundation in Generative AI, making it easier for those interested in the subfield to dive deeper into its complexities.
Product Manager
Product Managers are responsible for the planning, development, and launch of new products. This course helps build a foundation in Generative AI, a rapidly growing field with the potential to revolutionize product development.
Data Scientist
Data Scientists use their knowledge of programming, statistics, and machine learning to extract insights from data. This course provides the foundation needed for a deeper dive into the field of Generative AI, which has the potential to revolutionize the way we work with data.
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models. This course provides insights into the integration of Generative AI into ML models, which can help advance an ML Engineer's career.
Computer Scientist
Computer Scientists research and develop new computing technologies. This course provides insights into the use of Generative AI in computing, which can be valuable for those interested in the subfield.
Machine Learning Scientist
Machine Learning Scientists research and develop new machine learning algorithms. This course may provide insights into the integration of Generative AI into ML algorithms, which can help advance a Machine Learning Scientist's career.
Software Engineer
Software Engineers design, develop, and maintain software systems. This course may be useful for Software Engineers who want to learn more about Generative AI and its potential applications in software development.
Business Intelligence Analyst
Business Intelligence Analysts collect, analyze, and interpret data to identify business trends. This course may be useful for Business Intelligence Analysts who want to learn more about Generative AI and its potential in business intelligence.
Data Architect
Data Architects design and build data architectures. This course may be useful for Data Architects who want to learn more about Generative AI and its potential in data architecture.
Data Analyst
Data Analysts collect, clean, and analyze data to identify trends and patterns. This course may be useful for Data Analysts who want to learn more about Generative AI and its potential in data analysis.
Data Engineer
Data Engineers design, build, and maintain data pipelines. This course may be useful for Data Engineers who want to learn more about Generative AI and its potential in data engineering.
Business Analyst
Business Analysts identify and solve business problems. This course may be useful for Business Analysts who want to learn more about Generative AI and its potential applications in their field.
Project Manager
Project Managers plan, execute, and close projects. This course may be useful for Project Managers who want to learn more about Generative AI and its potential in project management.

Reading list

We've selected 13 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 Building a Generative AI-Ready Organization.
Provides a deep dive into the technical details of deep learning, which key technology used in generative AI. It good choice for readers who want to understand the underlying algorithms and techniques.
Provides a practical guide to building and deploying machine learning and AI systems. It good choice for readers who want to learn how to apply these technologies to real-world problems.
Provides a practical guide to using generative AI for finance. It good choice for readers who want to learn how to use generative AI to improve their financial performance.
This authoritative reference provides a comprehensive treatment of deep learning, covering the theory and practice of training and using deep neural networks for various tasks.
This influential textbook provides a rigorous mathematical foundation for statistical learning and is essential for understanding the statistical concepts underlying Generative AI models.
This practical guide focuses specifically on Generative AI and provides hands-on tutorials for building and training generative models using Python and TensorFlow.
This foundational textbook provides a comprehensive introduction to reinforcement learning, which key technique used in generative models for tasks like text generation and image generation.
Explores the challenges and prospects of developing artificial general intelligence, which could have profound implications for Generative AI in the future.
This provocative book explores the potential for technological advancements to lead to a singularity, where AI surpasses human intelligence, with implications for Generative AI.
This popular science book explores the potential future of humanity and the role that AI could play, including the potential impact of Generative AI.

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