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    Certified Prompt Engineer For Product Management (Cpe-Pm)

    Posted By: ELK1nG
    Certified Prompt Engineer For Product Management (Cpe-Pm)

    Certified Prompt Engineer For Product Management (Cpe-Pm)
    Published 2/2025
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 4.32 GB | Duration: 7h 6m

    Unlock AI's Potential in Product Management: A Foundation in Prompt Engineering

    What you'll learn

    Understand the role of AI in modern product management.

    Learn the fundamentals of prompt engineering for AI.

    Explore the capabilities and limitations of language models.

    Master effective techniques for designing AI prompts.

    Balance creativity and constraints in prompt writing.

    Use AI for market research and competitive analysis.

    Conduct AI-generated customer pain point identification.

    Leverage AI for ideation and product innovation.

    Translate customer feedback into AI-driven features.

    Create AI-generated product roadmaps and address risks.

    Craft persuasive marketing copy using AI tools.

    Utilize AI in customer segmentation and targeting.

    Automate data analysis and KPI reporting with AI.

    Explore ethical and legal issues in AI product workflows.

    Integrate AI into agile and lean product development.

    Requirements

    An interest in AI and product management – A curiosity about how artificial intelligence is shaping product development and strategy.

    A creative and strategic mindset – The ability to generate and refine ideas while considering business objectives.

    An analytical approach – The capability to assess AI-generated insights and market trends with precision.

    A commitment to ethical responsibility – An awareness of AI bias, fairness, and data privacy in product decisions.

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

    Description

    The convergence of artificial intelligence and product management is reshaping how products are envisioned, designed, and brought to market. This course offers a comprehensive exploration into the domain of prompt engineering, a crucial skill for harnessing AI's potential in product management. Students will embark on a journey to understand the fundamentals and significance of prompt engineering, which serves as a foundation for leveraging AI's capabilities effectively. The course begins by introducing the pivotal role of AI in modern product management, providing insights into large language models, their capabilities, and inherent limitations. This understanding is essential for navigating the complexities of AI-driven product workflows.As students delve deeper, they will gain an appreciation for the nuanced art and science of prompt design. They will explore the principles that govern the effectiveness of prompts, focusing on achieving clarity and precision. The course emphasizes the delicate balance between creativity and constraints, a critical skill for crafting prompts that guide AI systems to generate valuable insights. The curriculum also introduces system messages and control instructions, which are vital for steering AI outputs in alignment with product objectives. Through theoretical exploration, students will learn to refine and iterate prompts to maximize their impact.Product management thrives on market insights and strategic analysis. This course equips students with the knowledge to conduct market research and competitive analysis using AI-generated prompts. Participants will learn how AI can be leveraged to gather industry insights, benchmark competitors, and identify customer pain points. The ability to synthesize and analyze market trends with AI assistance is highlighted, alongside methodologies to ensure accuracy and avoid bias in AI-generated research.Innovation is the lifeblood of successful product management, and this course delves into AI-driven ideation and product innovation. Students will explore how AI can augment brainstorming sessions and assist in evaluating and prioritizing product ideas. The course examines the dynamics of divergent and convergent thinking, encouraging students to expand their creative horizons while overcoming common challenges in AI-generated innovation. This theoretical framework prepares students for the future of product ideation.In the realm of requirements gathering and road-mapping, AI offers transformative possibilities. Students will learn how to translate customer feedback into actionable features and automate the development of user stories. The course provides insights into creating AI-generated product roadmaps while addressing risks and dependencies using AI-driven insights. Additionally, the collaborative intersection of AI and user experience design is explored, with a focus on persona development, journey mapping, and other UX enhancements.The course also covers AI-augmented product marketing strategies, guiding students through the intricacies of crafting persuasive copy and messaging with AI assistance. They will explore AI's role in customer segmentation, content strategy, and campaign ideation. Furthermore, the curriculum addresses the use of AI for social media and SEO optimization, as well as automating A/B testing and performance analysis.Finally, students will engage with ethical and legal considerations in AI adoption, examining issues of bias, fairness, and data privacy. The future of AI ethics and governance in product management is contemplated, empowering students to anticipate and navigate the evolving landscape. This course provides a robust theoretical foundation for those seeking to integrate AI into their product management practice, positioning them at the forefront of innovation and strategic decision-making.

    Overview

    Section 1: Course Preparation

    Lecture 1 Course Preparation

    Section 2: Introduction to Prompt Engineering and AI in Product Management

    Lecture 2 Section Introduction

    Lecture 3 What is Prompt Engineering? Fundamentals and Importance

    Lecture 4 Understanding Large Language Models: Capabilities and Limitations

    Lecture 5 The Role of AI in Modern Product Management

    Lecture 6 Key Terminology and Concepts in AI-Powered Product Workflows

    Lecture 7 Setting Up and Experimenting with ChatGPT for Product Tasks

    Lecture 8 Section Summary

    Section 3: Foundations of Effective Prompt Design

    Lecture 9 Section Introduction

    Lecture 10 The Science Behind Prompt Effectiveness

    Lecture 11 Structuring Prompts for Clarity and Precision

    Lecture 12 Techniques for Refining and Iterating Prompts

    Lecture 13 Balancing Creativity and Constraints in Prompt Writing

    Lecture 14 Using System Messages and Instructions for Control

    Lecture 15 Section Summary

    Section 4: Market Research and Competitive Analysis

    Lecture 16 Section Introduction

    Lecture 17 Gathering Industry Insights Using AI-Generated Prompts

    Lecture 18 Leveraging AI for Competitor Benchmarking

    Lecture 19 Identifying Customer Pain Points Through AI Conversations

    Lecture 20 Synthesizing and Analyzing Market Trends with AI

    Lecture 21 Avoiding Bias and Ensuring Accuracy in AI-Generated Research

    Lecture 22 Section Summary

    Section 5: AI-Driven Ideation and Product Innovation

    Lecture 23 Section Introduction

    Lecture 24 Generating and Evaluating Product Ideas with AI

    Lecture 25 Enhancing Brainstorming Sessions Using AI-Powered Prompts

    Lecture 26 Prioritizing Ideas: AI-Assisted Scoring and Filtering

    Lecture 27 Expanding Creativity: Divergent vs. Convergent Thinking with AI

    Lecture 28 Overcoming Common Challenges in AI-Generated Innovation

    Lecture 29 Section Summary

    Section 6: Requirements Gathering and AI-Assisted Road-mapping

    Lecture 30 Section Introduction

    Lecture 31 Extracting and Structuring Product Requirements with AI

    Lecture 32 Translating Customer Feedback into Actionable Features

    Lecture 33 Automating User Story and Feature Development with AI

    Lecture 34 Creating AI-Generated Product Roadmaps

    Lecture 35 Addressing Risks and Dependencies Using AI-Driven Insights

    Lecture 36 Section Summary

    Section 7: User Experience (UX) Design and AI Collaboration

    Lecture 37 Section Introduction

    Lecture 38 AI in Persona Development and User Journey Mapping

    Lecture 39 Enhancing Wireframing and Prototyping with AI Assistance

    Lecture 40 Optimizing UX Research and Testing via AI-Generated Prompts

    Lecture 41 Personalization and Adaptive UI Design with AI

    Lecture 42 Ethical Considerations in AI-Driven UX Design

    Lecture 43 Section Summary

    Section 8: AI-Augmented Product Marketing Strategies

    Lecture 44 Section Introduction

    Lecture 45 Crafting Persuasive Copy and Messaging with AI

    Lecture 46 AI in Customer Segmentation and Targeting

    Lecture 47 Enhancing Content Strategy and Campaign Ideation with AI

    Lecture 48 Leveraging AI for Social Media and SEO Optimization

    Lecture 49 Automating A/B Testing and Performance Analysis with AI

    Lecture 50 Section Summary

    Section 9: AI in Data Analytics and Decision Making

    Lecture 51 Section Introduction

    Lecture 52 Using AI to Extract Actionable Insights from Product Data

    Lecture 53 Automating Performance Reports and KPI Analysis with AI

    Lecture 54 Forecasting Trends and User Behavior with AI Models

    Lecture 55 AI in Decision-Making: Augmentation vs. Automation

    Lecture 56 Understanding AI-Generated Data Bias and Mitigation Strategies

    Lecture 57 Section Summary

    Section 10: Ethical and Legal Considerations in AI Adoption

    Lecture 58 Section Introduction

    Lecture 59 AI Bias, Fairness, and Responsible Prompt Engineering

    Lecture 60 Data Privacy and Compliance in AI-Driven Product Workflows

    Lecture 61 Intellectual Property Considerations in AI-Generated Content

    Lecture 62 Managing AI Transparency and User Trust in Product Decisions

    Lecture 63 The Future of AI Ethics and Governance in Product Management

    Lecture 64 Section Summary

    Section 11: Advanced Prompt Engineering and Future Trends

    Lecture 65 Section Introduction

    Lecture 66 Multi-Turn Prompting for Complex Product Workflows

    Lecture 67 Using Chain-of-Thought and Few-Shot Prompting Techniques

    Lecture 68 Integrating AI into Agile and Lean Product Development

    Lecture 69 The Evolving Role of AI in Product Management & Innovation

    Lecture 70 Beyond ChatGPT: Emerging AI Technologies and Their Impact

    Lecture 71 Section Summary

    Section 12: Course Summary

    Lecture 72 Conclusion

    Product managers eager to integrate AI into their workflow and enhance product innovation,Aspiring product managers seeking foundational skills in AI and prompt engineering,Professionals in tech looking to understand AI's role in modern product management,Entrepreneurs aiming to leverage AI for competitive market analysis and insights,Marketing strategists wanting to explore AI-driven content and campaign ideation,Business analysts focusing on AI's potential in data analytics and strategic decision making,Ethical and legal practitioners exploring AI governance in product management contexts