AI Value Creation and Data Monetization Strategy Masterclass from Udemy

Data is the new fuel for the 21st century, and are you ready to explore innovative use cases and real-world examples of successful data monetization and AI value creation? In today's rapidly evolving digital landscape, data has emerged as the new currency, and Artificial Intelligence as the catalyst for transformative change across different industries.

What you will learn in this course is based on my real-life strategy consulting client success stories. As an example, I recently helped my client, one of the largest banks in Europe, secure €1 million funding per year for a multi-year data and AI value creation initiative. I'll walk you through these proven data and AI value creation strategies and all of the fundamentals to set you for success in the data-led transformation journey.

What Are the Key Topics Of This Course?

How can organizations unlock the untapped business value of their data rapidly to drive revenue growth, optimize operations, and stay ahead of the competition?
What's the latest trend of Data and AI? What are the potential business impacts?
What is the tested Strategy Consulting approach to Data & AI business value creation?
How to leverage AI and LLM to monetize data both internally and externally? What are the data product strategies?
How to assess the As-Is data and AI maturity level and identify gaps to achieve the target state?
How to align Data and AI initiatives with business strategy to steer the data-driven transformation to the right direction?
How to align value creation strategies with key business drivers? What's the business value tree?
How to create data and AI use cases continuously and what is the mechanism to prioritize business-critical use cases?
What are the critical business questions to interview stakeholders?
How to craft a compelling data and AI business case to secure funding?
How to develop an actionable multi-year roadmap to implement data and AI value cases?

If these questions resonate with you, you are in the right place to find insights and answers.

Enroll now and embark on a journey towards unlimited possibilities in the Data and AI business value creation world. Thank you for your interest and I will see you in my course.

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Taught by Bing, data value creation strategy expert

Focuses on data monetization and AI value creation, which is highly relevant to many industries

Provides a structured approach to data and AI value creation, based on strategy consulting best practices

Covers key topics such as AI monetization, data product strategy, and value creation strategies

Includes hands-on exercises and case studies to reinforce learning

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 AI Value Creation and Data Monetization Strategy Masterclass with these activities:

Attend Industry Events and Meetups

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Attending industry events and meetups will help you connect with professionals in the field and learn about the latest trends.

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Research upcoming industry events and meetups.
Attend the events and engage with other attendees.
Follow up with potential connections after the events.

Review Data Science for Business

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Reviewing this book will help you brush up on essential data science concepts and techniques covered in the course.

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Read the book's introduction and first chapter.
Identify key concepts and make notes.
Review the summary and exercises at the end of each chapter.

Practice Data Analysis Techniques

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Practicing data analysis techniques will help you master the skills covered in the course.

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Use a data analysis tool such as Python or R.
Load and clean datasets.
Perform exploratory data analysis.
Build and evaluate machine learning models.

Four other activities

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Create a Data Monetization Strategy

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Creating a data monetization strategy will help you apply the course concepts to your own business context.

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Define your data monetization goals.
Identify your target audience.
Research different data monetization models.
Develop a data monetization plan.

Practice AI Model Deployment

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Practicing AI model deployment will help you gain hands-on experience in deploying models to production.

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Choose a cloud platform and create an account.
Deploy a pre-trained model or train and deploy your own model.
Monitor and evaluate the deployed model.

Follow Tutorials on Advanced AI Techniques

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Following tutorials on advanced AI techniques will help you extend your knowledge beyond the course material.

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Identify tutorials from reputable sources.
Follow the tutorials step-by-step.
Experiment with different techniques and parameters.

Develop a Data and AI Value Creation Proposal

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Developing a data and AI value creation proposal will help you apply the course concepts to a real-world scenario.

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Identify a problem or opportunity that can be addressed with data and AI.
Develop a solution that uses data and AI to address the problem or opportunity.
Quantify the benefits of the solution.
Create a proposal that outlines the problem, solution, benefits, and implementation plan.

Career center

Learners who complete AI Value Creation and Data Monetization Strategy Masterclass will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data scientists are responsible for collecting, analyzing, and interpreting large datasets to find trends and patterns. This course can help data scientists develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data mining, machine learning, and data visualization, which are all essential skills for data scientists.

See salaries and explore the career path for Data Scientist

Data Analyst

Data analysts use data to solve business problems. They collect, clean, and analyze data to identify trends and patterns. This course can help data analysts develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data mining, machine learning, and data visualization, which are all essential skills for data analysts.

See salaries and explore the career path for Data Analyst

Machine Learning Engineer

Machine learning engineers are responsible for developing and deploying machine learning models. They use data to train models that can make predictions or decisions. This course can help machine learning engineers develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as machine learning algorithms, model deployment, and model evaluation, which are all essential skills for machine learning engineers.

See salaries and explore the career path for Machine Learning Engineer

Data Engineer

Data engineers are responsible for building and maintaining the infrastructure that supports data science and machine learning. They design and implement data pipelines, data warehouses, and other data management systems. This course can help data engineers develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data architecture, data integration, and data governance, which are all essential skills for data engineers.

See salaries and explore the career path for Data Engineer

Business Analyst

Business analysts use data to help businesses make better decisions. They analyze data to identify trends and patterns, and they develop recommendations for how businesses can improve their performance. This course can help business analysts develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data mining, machine learning, and data visualization, which are all essential skills for business analysts.

See salaries and explore the career path for Business Analyst

Product Manager

Product managers are responsible for developing and managing products. They work with engineers, designers, and other stakeholders to bring products to market. This course can help product managers develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data-driven decision making, product development, and product marketing, which are all essential skills for product managers.

See salaries and explore the career path for Product Manager

Marketing Manager

Marketing managers are responsible for developing and executing marketing campaigns. They use data to understand their target audience and to develop strategies to reach them. This course can help marketing managers develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data-driven marketing, customer segmentation, and campaign optimization, which are all essential skills for marketing managers.

See salaries and explore the career path for Marketing Manager

Sales Manager

Sales managers are responsible for leading and motivating sales teams. They use data to track sales performance and to identify opportunities for growth. This course can help sales managers develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data-driven sales, lead generation, and customer relationship management, which are all essential skills for sales managers.

See salaries and explore the career path for Sales Manager

Operations Manager

Operations managers are responsible for planning and managing the day-to-day operations of a business. They use data to improve efficiency and productivity. This course can help operations managers develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data-driven operations, process improvement, and supply chain management, which are all essential skills for operations managers.

See salaries and explore the career path for Operations Manager

Financial Analyst

Financial analysts use data to evaluate the financial performance of companies. They make recommendations to investors and other stakeholders on whether to buy, sell, or hold stocks. This course can help financial analysts develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data-driven financial analysis, portfolio management, and risk assessment, which are all essential skills for financial analysts.

See salaries and explore the career path for Financial Analyst

Consultant

Consultants provide advice to businesses on how to improve their performance. They use data to identify problems and to develop solutions. This course can help consultants develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data-driven consulting, problem solving, and client management, which are all essential skills for consultants.

See salaries and explore the career path for Consultant

Entrepreneur

Entrepreneurs start and run their own businesses. They use data to make decisions about product development, marketing, and sales. This course can help entrepreneurs develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data-driven entrepreneurship, market research, and customer acquisition, which are all essential skills for entrepreneurs.

See salaries and explore the career path for Entrepreneur

Researcher

Researchers conduct scientific investigations to answer questions and solve problems. They use data to gather evidence and to develop new theories. This course can help researchers develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data-driven research, experimental design, and data analysis, which are all essential skills for researchers.

See salaries and explore the career path for Researcher

Educator

Educators teach students about a variety of subjects. They use data to track student progress and to identify areas where students need additional support. This course can help educators develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data-driven education, personalized learning, and assessment, which are all essential skills for educators.

See salaries and explore the career path for Educator

Nonprofit Manager

Nonprofit managers lead and manage nonprofit organizations. They use data to track progress towards goals and to identify areas where the organization can improve. This course can help nonprofit managers develop the skills they need to effectively use AI and machine learning to create value from data. The course covers topics such as data-driven nonprofit management, fundraising, and volunteer management, which are all essential skills for nonprofit managers.

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