Certified Prompt Engineer For Program Management (Cpe-Pmg)

Posted By: ELK1nG

Certified Prompt Engineer For Program Management (Cpe-Pmg)
Published 2/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 4.49 GB | Duration: 7h 25m

Unlock AI's Potential in Program Management: Transform Strategies with Prompt Engineering Essentials

What you'll learn

Understand the fundamentals of prompt engineering in program management

Explore AI and NLP basics tailored for program managers

Learn effective prompting techniques for AI-driven decisions

Discover the intersection of AI and program management

Identify ethical considerations in AI-powered decision-making

Define program goals and understand lifecycle governance

Master prompt crafting for strategic program planning

Align AI prompting with program goals and milestones

Leverage AI for work breakdown structures and budget forecasting

Enhance stakeholder engagement using AI-powered communication

Develop AI strategies for risk identification and mitigation

Use prompts for performance monitoring and optimization

Explore AI-driven change management and adaptation strategies

Strengthen team collaboration with AI-enhanced productivity strategies

Conduct AI-augmented scenario planning and decision-making

Address ethical and legal aspects of AI in program management

Requirements

An interest in AI and program management – A curiosity about how artificial intelligence can enhance strategic decision-making.

A problem-solving mindset – The ability to analyze complex challenges and integrate AI-driven solutions.

Strong communication skills – The capability to leverage AI for stakeholder engagement and effective reporting.

A commitment to ethical responsibility – An understanding of AI fairness, data privacy, and responsible automation in management.

A willingness to learn – An openness to exploring AI-driven techniques and adapting to evolving program management practices.

Description

Delve into an innovative educational journey designed to transform the way program managers integrate cutting-edge technology into their strategic decision-making processes. This course offers a comprehensive exploration into the emerging discipline of prompt engineering, tailored specifically for program management professionals seeking to leverage artificial intelligence and natural language processing to enhance their managerial acumen. Students will embark on a theoretical exploration that underscores the profound impact of AI on program management, equipping them with the insights needed to redefine success in their field.At the heart of this curriculum lies a thorough introduction to the fundamentals of prompt engineering and its pivotal role in program management. Students will gain a deep understanding of effective prompting techniques, which form the cornerstone of AI-driven decision-making. By exploring the intersection of AI and program management, participants will appreciate how these technological advancements can revolutionize program planning, risk management, and stakeholder engagement, all while maintaining a firm grounding in ethical considerations and responsible AI use.The course further delves into the essential principles of program management, offering a solid foundation in defining program goals, understanding lifecycle governance, and managing risks, scope, and resources. By mastering the art of crafting effective prompts, students will learn to align strategic planning with program objectives and milestones, ensuring a seamless integration of AI-generated insights into traditional practices. The course emphasizes the importance of AI in generating work breakdown structures and optimizing budget forecasting, showcasing the transformative potential of prompt engineering in resource allocation and agile planning approaches.Enhancing stakeholder engagement through AI is another focal point of this course. Participants will explore strategies for identifying key stakeholders, developing AI-powered communication tactics, and leveraging prompts for stakeholder feedback and buy-in. This knowledge is crucial for addressing resistance and conflict resolution, thereby fostering a collaborative environment that is essential for successful program execution. The ability to create dynamic, AI-assisted reports and presentations will further empower students to communicate their strategies effectively.Risk management is a critical component of program management, and this course provides an in-depth exploration of leveraging prompt engineering to identify, assess, and mitigate risks. Through AI-powered prompts, students will learn to forecast potential challenges and develop robust risk mitigation strategies, ensuring program resilience and adaptability. The course also examines the role of AI in automating risk monitoring and response planning, while evaluating its contribution to decision support in risk management.Performance monitoring and optimization form a cornerstone of the curriculum, guiding students in defining key performance indicators and success metrics with AI assistance. By crafting prompts for performance analysis and reporting, participants will gain insights into program health and enhance decision-making through predictive analytics. The course also explores the use of prompts in automating performance reviews and adjustments, enabling a proactive approach to program management.Finally, the course addresses the ethical and responsible use of AI in program management, ensuring students are equipped to navigate the complex landscape of bias, fairness, data privacy, and legal considerations. By fostering human-AI collaboration and balancing automation with human oversight, this course prepares program managers to lead with integrity and foresight. Through this transformative learning experience, participants will emerge as visionary leaders, ready to harness the full potential of AI in shaping the future of program management.

Overview

Section 1: Course Preparation

Lecture 1 Course Preparation

Section 2: Introduction to Prompt Engineering in Program Management

Lecture 2 Section Introduction

Lecture 3 Understanding the Role of Prompt Engineering in Program Management

Lecture 4 Fundamentals of Effective Prompting Techniques

Lecture 5 AI and NLP Basics for Program Managers

Lecture 6 The Intersection of AI and Program Management

Lecture 7 Ethical Considerations in AI-Powered Decision-Making

Lecture 8 Section Summary

Section 3: Foundations of Program Management

Lecture 9 Section Introduction

Lecture 10 Key Principles of Program Management

Lecture 11 Defining Program Goals and Objectives

Lecture 12 Program Lifecycle and Governance

Lecture 13 Stakeholder Roles and Responsibilities

Lecture 14 Introduction to Risk, Scope, and Resource Management

Lecture 15 Section Summary

Section 4: Crafting Effective Prompts for Program Planning

Lecture 16 Section Introduction

Lecture 17 Structuring Prompts for Strategic Planning

Lecture 18 Aligning Prompts with Program Goals and Milestones

Lecture 19 Generating AI-Assisted Work Breakdown Structures

Lecture 20 Utilizing Prompting for Budget Forecasting and Resource Allocation

Lecture 21 Refining Prompts for Agile and Traditional Planning Approaches

Lecture 22 Section Summary

Section 5: Enhancing Stakeholder Engagement with Prompt Engineering

Lecture 23 Section Introduction

Lecture 24 Identifying Key Stakeholders and Their Needs

Lecture 25 Developing AI-Powered Communication Strategies

Lecture 26 Crafting Prompts for Stakeholder Feedback and Buy-in

Lecture 27 Addressing Resistance and Conflict Resolution via AI-Powered Insights

Lecture 28 Creating Dynamic Reports and Presentations with AI Assistance

Lecture 29 Section Summary

Section 6: Leveraging Prompt Engineering for Risk Management

Lecture 30 Section Introduction

Lecture 31 Understanding Risk Identification and Assessment

Lecture 32 Using AI-Powered Prompts for Risk Forecasting

Lecture 33 Developing Risk Mitigation Strategies with AI

Lecture 34 Automating Risk Monitoring and Response Planning

Lecture 35 Evaluating AI’s Role in Decision Support for Risk Management

Lecture 36 Section Summary

Section 7: Performance Monitoring and Optimization Using Prompts

Lecture 37 Section Introduction

Lecture 38 Defining KPIs and Success Metrics with AI Assistance

Lecture 39 Crafting Prompts for Performance Analysis and Reporting

Lecture 40 AI-Powered Dashboards for Program Health Monitoring

Lecture 41 Enhancing Decision-Making Through Predictive Analytics

Lecture 42 Using Prompts to Automate Performance Reviews and Adjustments

Lecture 43 Section Summary

Section 8: Prompt Engineering for Change Management

Lecture 44 Section Introduction

Lecture 45 Principles of Change Management in Program Execution

Lecture 46 Identifying Change Drivers and Readiness Factors

Lecture 47 Using AI Prompts to Develop Change Strategies

Lecture 48 Communicating Change Effectively Through AI-Assisted Messaging

Lecture 49 AI-Driven Change Impact Assessments and Adaptation Strategies

Lecture 50 Section Summary

Section 9: Strengthening Team Collaboration Through AI-Powered Prompts

Lecture 51 Section Introduction

Lecture 52 Promoting Cross-Functional Collaboration with AI Assistance

Lecture 53 Generating AI-Enhanced Team Productivity Strategies

Lecture 54 Prompting for Effective Conflict Resolution in Teams

Lecture 55 AI-Powered Delegation and Task Prioritization

Lecture 56 Enhancing Virtual Team Engagement with AI

Lecture 57 Section Summary

Section 10: Advanced Prompt Engineering for Strategic Decision-Making

Lecture 58 Section Introduction

Lecture 59 AI-Augmented Scenario Planning and Decision Trees

Lecture 60 Crafting Prompts for Complex Decision-Making Processes

Lecture 61 Using AI for Data-Driven Strategic Forecasting

Lecture 62 AI-Enabled Market and Competitive Analysis

Lecture 63 Developing AI-Powered Reports for Executive Leadership

Lecture 64 Section Summary

Section 11: Ethical and Responsible AI Use in Program Management

Lecture 65 Section Introduction

Lecture 66 Addressing Bias and Fairness in AI-Generated Insights

Lecture 67 Ensuring Data Privacy and Security in AI-Assisted Workflows

Lecture 68 Human-AI Collaboration: Balancing Automation and Human Oversight

Lecture 69 Legal and Compliance Considerations in AI Use

Lecture 70 The Future of AI and Prompt Engineering in Program Management

Lecture 71 Section Summary

Section 12: Course Summary

Lecture 72 Conclusion

Program managers aiming to integrate AI into strategic decision-making,Professionals in program management seeking AI and NLP expertise,Managers wanting to enhance decision-making with AI insights,Program leads interested in advanced prompt engineering techniques,Leaders focused on aligning AI with program goals and objectives,Stakeholder managers aiming to improve engagement with AI tools,Risk managers seeking AI-driven strategies for risk mitigation,Change managers looking to leverage AI for seamless transition