What is the CPMAI Certification?

AI & Data Best Practices The Cognitive Project Management for AI (CPMAI) methodology is the most widely adopted, vendor-neutral approach to running AI projects. Individuals and organizations are not just learning this approach, but also getting certified to run their AI projects successfully. So, what is the CPMAI certification and how can you put it …

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Established Best Practices for AI & Data Project Management

AI & Data Best Practices With all the talent, resources, and effort being put into AI projects, the failure rate should not be so significantly high. Indeed, there’s substantial good technology and talent that knows how to put technology to use for AI applications. The problem stems from the lack of following best practices for …

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The Critical AI and Data Skills you need as a Project Manager

AI & Data Best Practices There is significant and growing demand for skilled AI project managers and implementers across the whole range of AI capabilities. If you’re looking to get into managing AI projects, machine learning implementations, or advanced data projects of any type, or enhance your current skills, what are the most critical AI …

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How to apply CRISP-DM to AI and big data projects

AI & Data Best Practices There is significant and growing demand for skilled AI project managers and implementers across the whole range of AI capabilities. If you’re looking to get into managing AI projects, machine learning implementations, or advanced data projects of any type, or enhance your current skills, what are the most critical AI …

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Why Can’t I use Agile or CRISP-DM to manage AI and Data Projects?

Join Thousands of Others Who are Certified in AI Best-Practices Get CPMAI Certified Today! Millions of people around the globe at organizations and vendors of all sizes certified on leading project management methodologies and approaches such as PMP, PRINCE2, Agile, ScaledAgile (SAFe), and CRISP-DM. Likewise, organizations are rushing to implement and adopt AI. Existing data-centric …

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The ROI of a CPMAI Certification

AI & Data Best Practices When evaluating if Cognilytica’s Cognitive Project Management for AI (CPMAI) certification is right for you it’s important to ask “What’s the return for me on this investment?” Afterall, you’re investing your time and money so you want to make sure that the return is worth it.  Fortunately, the ROI of …

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Top 10 Reasons Why AI Projects Fail

AI & Data Best Practices  After observing thousands of AI projects, Cognilytica has identified the top 10 reasons why AI projects fail and how you can learn from others to avoid becoming another AI failure statistic. Join Thousands of Others Who are Certified in AI Best-Practices Get CPMAI Certified Today! AI is everywhere it seems …

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How can I earn PDUs for PMP and other PMI Certifications with CPMAI?

AI & Data Best Practices In this article, learn how to earn PDUs for PMP and other PMI Certifications with CPMAI training and certification. Join Thousands of Others Who are Certified in AI Best-Practices Get CPMAI Certified Today! The Cognitive Project Management for AI (CPMAI) Training and Certification offers many benefits. One of the benefits …

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How does a CPMAI certification enhance my career?

AI & Data Best Practices There is tremendous opportunity for people looking to manage AI & ML projects and there is a significant and growing demand for skilled AI project managers and implementers across the whole range of AI capabilities. So, you might be asking “how does a CPMAI certification enhance my career?” Read more …

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Is the CPMAI Certification worth it?

AI & Data Best Practices Organizations are looking for people with the right skills and knowledge to manage these projects. So, is the CPMAI Certification worth it? Absolutely! Join Thousands of Others Who are Certified in AI Best-Practices Get CPMAI Certified Today! Organizations across the world are looking to Artificial Intelligence (AI), Machine Learning (ML) …

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Cognitive Project Management for AI – CPMAI At a Glance [Infographic]

AI & Data Best Practices The Cognitive Project Management for AI (CPMAI) methodology provides a step by step approach to AI project management that has seen significant success in enterprise, government, academic, consulting, and technology vendor implementations. This infographic provides an overview of CPMAI at a glance, but read below for more details.   What …

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The Steps for a Machine Learning Project

AI & Data Best Practices Following a step-by-step repeatable, documented, and iterative approach will ensure project success. These steps provide an AI project template that provides guidance on each phase in development and provides an agile, flexible approach that allows you to iterate your project as needs change or you develop experience with AI systems. …

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Infographic: The Steps for an AI Project

AI & Data Best Practices How do you plan an AI project? AI projects can be challenging, daunting, and scary, especially if you’ve never run an artificial intelligence or machine learning project before. Fortunately, there are proven, best practices approaches to running Artificial intelligence projects.   How many Steps are in the Stepwise Approach to …

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A Step-by-Step Approach to Running AI and Machine Learning Projects

AI & Data Best Practices Following a step-by-step repeatable, documented, and iterative approach will ensure project success. These steps provide an AI project template that provides guidance on each phase in development and provides an agile, flexible approach that allows you to iterate your project as needs change or you develop experience with AI systems. …

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What is the Cognitive Project Management for AI (CPMAI) Methodology?

AI & Data Best Practices The Cognitive Project Management for AI (CPMAI) methodology is a vendor-neutral, data-centric, AI-specific, Agile methodology for running and managing AI, ML, and cognitive technology projects. Learn how this methodology is changing and improving the way AI & ML projects are run. Join Thousands of Others Who are Certified in AI …

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Synthetic Data Generation Market: Research Snapshot Feb. 2022

Machine learning training data is not always readily available. In many cases, “ground truth” data is unavailable, can be difficult to collect, or is considered private, making its use difficult. Synthetic data is often used in scenarios where there isn’t sufficient training data available to be used in machine learning algorithms, especially in supervised machine …

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Data Labeling Market: Research Snapshot Dec. 2021

In order for machine learning systems to be able to create accurate generalizations, they must be trained on data. Advanced forms of machine learning, especially deep learning neural networks, require significant volumes of data to be able to create models with desired levels of accuracy. Customers often don’t have the resources to label large data …

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Cognilytica’s Comprehensive Ethical AI Framework

Many of the existing ethical AI frameworks currently released by government agencies, corporations, multi-stakeholder organizations and non-profit groups are lacking in different aspects of their ethical AI frameworks. As such, Cognilytica is releasing for general usage a template for ethical AI frameworks that can serve as a basis for individual organization AI implementations or as …

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Worldwide AI Country Strategies and Competitiveness 2021

The race for competitive advantage in artificial intelligence (AI) is not just the domain of companies and organizations. Countries vie with each other for dominance in the space of AI, seeking competitive advantages for their industrial ecosystem, military and defense, academic institutions, and areas of private and public sector enterprise. Countries that can take advantage …

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Machine Learning Platforms 2020

Document ID: CGR-MLP20 | Last Updated: Dec. 8, 2020 Machine learning systems are core to enabling each of the seven patterns of AI. Machine learning platforms facilitate and accelerate the development of machine learning models by providing functionality that combines many necessary activities for model development and deployment. In this report, Cognilytica evaluates five major categories …

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Digitization and Digitalization Report (June 2020)

Document ID: CGR-DIG20 | Last Updated: Jun. 23, 2020 Digitization focuses on the capturing and extraction of value from non-digital data by converting it to a usable digital state. Digitalization expands upon the idea of digitization by addressing human-bound processes and processes that have previously been dependent on non-digital information. Digitization and Digitalization are seen …

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