Succeeding with AI
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The big challenge for a successful AI project isn’t deciding which problems you can solve. It’s deciding which problems you should solve.
In Managing Successful AI Projects, author and AI consultant Veljko Krunic reveals secrets for succeeding in AI that he developed with Fortune 500 companies, early-stage start-ups, and other business across multiple industries.
Key Features
· Selecting the right AI project to meet specific business goals
· Economizing resources to deliver the best value for money
· How to measure the success of your AI efforts in the business terms
· Predict if you are you on the right track to deliver your intended business results
For executives, managers, team leaders, and business-focused data scientists. No specific technical knowledge or programming skills required.
About the technology
Companies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists. Too often, these AI projects focus on technology at the expense of actionable or tangible business results, resulting in scattershot results and wasted investment. Managing Successful AI Projects sets out a blueprint for AI projects to ensure they are predictable, successful, and profitable. It’s filled with practical techniques for running data science programs that ensure they’re cost effective and focused on the right business goals.
Veljko Krunic is an independent data science consultant who has worked with companies that range from start-ups to Fortune 10 enterprises. He holds a PhD in Computer Science and an MS in Engineering Management, both from the University of Colorado at Boulder. He is also a Six Sigma Master Black Belt.
The big challenge for a successful AI project isn’t deciding which problems you can solve. It’s deciding which problems you should solve.
In Managing Successful AI Projects, author and AI consultant Veljko Krunic reveals secrets for succeeding in AI that he developed with Fortune 500 companies, early-stage start-ups, and other business across multiple industries.
Key Features
· Selecting the right AI project to meet specific business goals
· Economizing resources to deliver the best value for money
· How to measure the success of your AI efforts in the business terms
· Predict if you are you on the right track to deliver your intended business results
For executives, managers, team leaders, and business-focused data scientists. No specific technical knowledge or programming skills required.
About the technology
Companies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists. Too often, these AI projects focus on technology at the expense of actionable or tangible business results, resulting in scattershot results and wasted investment. Managing Successful AI Projects sets out a blueprint for AI projects to ensure they are predictable, successful, and profitable. It’s filled with practical techniques for running data science programs that ensure they’re cost effective and focused on the right business goals.
Veljko Krunic is an independent data science consultant who has worked with companies that range from start-ups to Fortune 10 enterprises. He holds a PhD in Computer Science and an MS in Engineering Management, both from the University of Colorado at Boulder. He is also a Six Sigma Master Black Belt.
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