kingers Posted June 9 Report Share Posted June 9 Cpmai™ Tutoring Masterclass: 1St Round Published 5/2025 MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz Language: English | Size: 2.70 GB | Duration: 1h 6mMaster the Cognitive Project Management for AI What you'll learn The fundamentals and structure of the CPMAI methodology The six phases of CPMAI and how they map to CRISP-DM and agile practices How to initiate, plan, execute, and monitor AI projects using CPMAI Practices for managing data, models, ethics, and business outcomes How to avoid common AI project pitfalls and ensure alignment with stakeholder expectations Knowledge Checkpoints to pass the CPMAI certification exam Requirements Take CPMAI Training at PMI Description This tutoring course is designed based on the below guideline on how to learn and prepare for the CPMAI certification.1. Understand What CPMAI IsCPMAI is not a technical AI certification - it's about managing AI and cognitive technology projects.It combines traditional project management (like PMI/PMBOK) with CRISP-DM and best practices for AI projects.You need to show you understand:How AI projects are different from normal IT projects.How to apply CPMAI methodology stages to an AI project.2. Study the CPMAI MethodologyThere are 6 CPMAI stages (based on CRISP-DM but tailored for AI projects):Business UnderstandingData UnderstandingData PreparationModelingEvaluationDeploymentFor each stage, you must know:What happens at that stage.Key deliverables.Common challenges (especially in AI - like bias, data drift, explainability).3. Review CPMAI Key ThemesCPMAI emphasizes:Iterative cycles (not one-and-done).AI Ethics (bias, transparency, fairness).Explainability (XAI) - how to make AI models understandable.Risk management specific to AI projects (e.g., data risk, model risk).4. Use the CPMAI Study MaterialsIf you enrolled in an official course, they usually provide:CPMAI Handbook or methodology guide (core reading).Templates (for deliverables at each stage).Sample exam questions (hugely important).TIP: Make your own notes on each CPMAI stage. Summarize:InputsActivitiesOutputsKey risks or considerations5. Practice with ScenariosThe exam tends to give realistic project scenarios and ask you:"At which CPMAI stage are you?""What should you do next?""What is missing in the project?"TIP: Practice identifying stages and decisions based on given case studies.6. Know AI Basics (but not in technical depth)You should be comfortable with basic concepts like:What is supervised vs unsupervised learning?What is overfitting?What is a model drift?What is explainability vs transparency?TIP: You don't need to code or build models. You just need to manage AI projects intelligently. Overview Section 1: Introduction Lecture 1 Welcome Section 2: AI Fundamentals Lecture 2 Understanding AI Fundamentals and Evolution - AI Fundamentals Lecture 3 Evaluating AI Applications and Patterns - AI Fundamentals Lecture 4 Seven Patterns of AI - AI Fundamentals Lecture 5 Applying Machine Learning Fundamentals - AI Fundamentals Section 3: CPMAI Methodology Lecture 6 Differentiating AI Project Management Approaches Lecture 7 Executing the Business Understanding Phase (CPMAI Phase I) Lecture 8 Managing the Data Understanding Phase (CPMAI Phase II) Lecture 9 Coordinating the Data Preparation Activities (CPMAI Phase III) Lecture 10 Determining the Approaches for Model Development (CPMAI Phase IV) Lecture 11 Conducting Model Evaluation and Maintenance (CPMAI Phase V) Section 4: ML for AI Lecture 12 Applying Classification and Clustering Algorithms Lecture 13 Implementing Neural Networks and Deep Learning Lecture 14 Leveraging Generative AI and Large Language Models (LLMs) Lecture 15 Selecting Machine Learning Tools and Platforms Section 5: Data for AI Lecture 16 Managing Data Fundamentals and Big Data Concepts Lecture 17 Implementing Data Governance and Management Lecture 18 Engineering Data Pipelines for AI Lecture 19 Executing Data Preparation and Transformation Section 6: Managing AI Lecture 20 Evaluating Model Performance and Accuracy Lecture 21 Deploying AI Models for Production Section 7: Trustworthy AI Lecture 22 Ethical, Responsible, and Trustworthy AI Lecture 23 Implementing AI Privacy and Security Lecture 24 Ensuring AI Transparency and Explainability Lecture 25 Navigating AI Regulations and Frameworks Project managers working on or transitioning to AI/data initiatives,Data scientists and engineers seeking a project delivery framework,Business analysts and consultants in AI transformation,Technology leaders who need to align AI projects with strategic goals,Anyone preparing for CPMAI certificationDDownloadhttps://ddownload.com/st3hclr64799/yxusj.CPMAI%E2%84%A2.Tutoring.Masterclass.1st.round.part1.rarhttps://ddownload.com/mcp49aqa6ct8/yxusj.CPMAI%E2%84%A2.Tutoring.Masterclass.1st.round.part2.rarRapidGatorhttps://rapidgator.net/file/ee742346ac2a31958826c945a88bac21/yxusj.CPMAI™.Tutoring.Masterclass.1st.round.part1.rarhttps://rapidgator.net/file/8d5be9f5b7cc03db2c6c7833a9b3ac8d/yxusj.CPMAI™.Tutoring.Masterclass.1st.round.part2.rarNitroFlarehttps://nitroflare.com/view/5A7EB677F7980F1/yxusj.CPMAI%E2%84%A2.Tutoring.Masterclass.1st.round.part1.rarhttps://nitroflare.com/view/482A2DB82DF197D/yxusj.CPMAI%E2%84%A2.Tutoring.Masterclass.1st.round.part2.rar Link to comment Share on other sites More sharing options...
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