Certified Prompt Engineer for Product Management (CPE-PM)

Name: Certified Prompt Engineer for Product Management (CPE-PM)
Rating: 2.6 (26 reviews)

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

Created byYouAccel Training

Last updated 2/2025

English

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.

Course content

12 sections • 72 lectures • 7h 7m total length

Course Preparation0:55

Section Introduction2:03
Master prompt engineering fundamentals and large language model capabilities to responsibly implement AI in product management, experiment with ChatGPT, and drive data-informed product decisions.
What is Prompt Engineering? Fundamentals and Importance8:05
Explore the fundamentals and importance of prompt engineering as a bridge between human inquiry and AI, emphasizing precise, context-rich prompts for finance, fintech, and product management.
Understanding Large Language Models: Capabilities and Limitations7:47
Understand large language models and transformer architectures, and how prompt engineering drives creative content in entertainment and media while balancing capabilities, limitations, and ethical considerations.
The Role of AI in Modern Product Management8:45
Explore how AI reshapes modern product management through machine learning, natural language processing, and data analytics, enabling data-driven decisions and automated insights, with fintech as a case study.
Key Terminology and Concepts in AI-Powered Product Workflows8:07
Explore how AI powered product workflows transform decision making in automotive and mobility markets, highlighting prompt engineering, data quality, and tailored insights from customer feedback and market trends.
Setting Up and Experimenting with ChatGPT for Product Tasks7:56
Set up and experiment with ChatGPT for product tasks, refining prompts and prompt engineering to boost precision and align outputs with business goals in e-commerce and retail.
Section Summary1:48
Explore essential principles of prompt engineering, capabilities and limitations of large language models, and how AI powers decision making and product workflows, including ChatGPT experiments.

Section Introduction1:59
Master core principles of prompt effectiveness and the cognitive processes behind language and machine learning to craft clear, iterative prompts guided by system messages.
The Science Behind Prompt Effectiveness7:36
Explore the science of prompt effectiveness and engineering, revealing how clear, context-rich prompts guide language models to precise, relevant AI outputs in healthcare and medtech.
Structuring Prompts for Clarity and Precision7:10
Structure prompts for clarity and precision to guide AI models like ChatGPT in finance and fintech with specificity. Use role-based contextualization and multi-turn dialogue for insights.
Techniques for Refining and Iterating Prompts7:18
Refine and iterate prompts to maximize ai utility in product management for e-commerce and retail. Apply prompt engineering, context, and multi-turn dialogue to boost customer engagement and data-driven decisions.
Balancing Creativity and Constraints in Prompt Writing8:53
Balance creativity and constraints in prompt writing within entertainment and media, using Toy Story’s 1990s tech limits as a guide for AI-driven storytelling and ethics.
Using System Messages and Instructions for Control7:20
Master system messages and instructions for control to craft precise, contextually aware prompts; advance prompt engineering through iterative refinement, predictive analytics, and alignment with AI and automation goals.
Section Summary1:47

Section Introduction1:54
Use AI generated prompts to gather industry insights, identify trends, benchmark competitors, and understand customer needs, guiding ethical, unbiased strategic decisions at scale.
Gathering Industry Insights Using AI-Generated Prompts6:56
Explore how AI generated prompts and prompt engineering transform market research and competitive analysis in fintech, offering dynamic, context-rich insights beyond traditional surveys and trends.
Leveraging AI for Competitor Benchmarking7:57
Explore using AI for competitor benchmarking in cloud-based software, focusing on Salesforce and its rivals to analyze strategies, customer satisfaction, and market trends.
Identifying Customer Pain Points Through AI Conversations6:18
Synthesizing and Analyzing Market Trends with AI7:02
Explore how AI-driven market trend synthesis expands anticipatory insights for e-commerce and retail. Learn how prompt engineering steers AI models to analyze seasonal, regional, and economic signals for strategic decisions.
Avoiding Bias and Ensuring Accuracy in AI-Generated Research7:41
Explore avoiding bias and ensuring accuracy in AI generated automotive research, guided by prompt engineering for analyzing electric vehicle adoption across urban and rural North America using diverse data sources.
Section Summary1:47
Leverage ai generated prompts to gather industry insights and trends for informed strategic decisions, benchmark competitors, identify customer pain points through ai driven conversations, and avoid bias in ai insights.

Section Introduction1:53
Harness artificial intelligence to fuel innovation and boost creativity by generating and evaluating product ideas, scoring and filtering with AI, and balancing divergent and convergent thinking.
Generating and Evaluating Product Ideas with AI7:17
Learn how AI analyzes data to generate and evaluate product ideas, guiding sustainable packaging and green tech innovations through prompt engineering and ethical governance.
Enhancing Brainstorming Sessions Using AI-Powered Prompts7:31
Leverage ai powered prompts to invigorate brainstorming, guiding structured ideation and diverse, critical analysis in e-commerce and retail.
Prioritizing Ideas: AI-Assisted Scoring and Filtering7:00
Expanding Creativity: Divergent vs. Convergent Thinking with AI6:54
Explore how AI-powered ideation blends divergent thinking with convergent thinking to optimize logistics and supply chain decisions, using prompt engineering to guide strategic, multi-turn interactions.
Overcoming Common Challenges in AI-Generated Innovation7:41
Leverage OpenAI's GPT three to explore AI generated innovation in the SaaS sector, showing how refined prompt engineering and multi-turn dialogue unlock meaningful, targeted product ideas.
Section Summary2:06

Section Introduction2:09
Extracting and Structuring Product Requirements with AI8:30
Extract and structure product requirements with AI across customer feedback, market trends, and competitor analysis. Use prompt engineering to deliver targeted insights for agile logistics and supply chain decisions.
Translating Customer Feedback into Actionable Features7:29
Translate customer feedback into actionable features by crafting precise prompts that identify themes and propose improvements for the logistics tracking feature. Integrate with existing systems and predictive analytics.
Automating User Story and Feature Development with AI6:44
Leverage ai and prompt engineering to automate user story and feature development while embracing human–ai collaboration, data integrity, and agile product management for innovative, efficient outcomes.
Creating AI-Generated Product Roadmaps7:05
Leverage AI generated product roadmaps to weave data-driven decisions, predictive analytics, and continuous optimization into strategic product planning, with a focus on e-commerce applications and prompt engineering.
Addressing Risks and Dependencies Using AI-Driven Insights7:11
Section Summary1:27
Leverage AI technologies to extract and structure product requirements, translating feedback into actionable features. Automate user stories and roadmaps to streamline development, mitigate risks and dependencies, and accelerate value delivery.

Section Introduction2:02
Discover how AI enhances persona development, journey mapping, wireframing, and prototyping, enabling real-time personalization, data-driven UX testing, and ethical handling of privacy, bias, and transparency.
AI in Persona Development and User Journey Mapping8:03
Leverage AI to develop dynamic personas and map user journeys in SaaS, using real-time data, predictive analytics, and prompt engineering to enhance personalization and reduce friction.
Enhancing Wireframing and Prototyping with AI Assistance7:41
Explore how AI assistants enhance wireframing and prototyping through prompt engineering, enabling rapid iteration and interactive prototypes for engaging entertainment and media interfaces.
Optimizing UX Research and Testing via AI-Generated Prompts7:50
Explore how AI generated prompts enhance user experience research and testing by blending human centered design with machine learning, enabling faster, more precise insights in healthcare and medtech.
Personalization and Adaptive UI Design with AI7:29
Ethical Considerations in AI-Driven UX Design6:53
Section Summary1:55

Section Introduction2:03
Explore AI ethics and governance for product management by identifying bias, protecting intellectual property in AI-generated content, ensuring fairness, and applying responsible prompt engineering, while safeguarding privacy, compliance, and transparency.
AI Bias, Fairness, and Responsible Prompt Engineering7:34
Data Privacy and Compliance in AI-Driven Product Workflows8:09
Intellectual Property Considerations in AI-Generated Content8:49
Managing AI Transparency and User Trust in Product Decisions8:22
Explore AI transparency and user trust in product decisions within logistics and supply chain, highlighting explainable AI, prompt engineering, and ethical data practices.
The Future of AI Ethics and Governance in Product Management7:25
Section Summary1:55
Mitigate AI bias and promote inclusivity through responsible prompt engineering. Navigate data privacy, intellectual property, transparency, and governance to build trustworthy AI in product management.

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.

Who this course is for:

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

Certified Prompt Engineer for Product Management (CPE-PM)

What you'll learn

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Course content

Course Preparation1 lecture • 1min

Introduction to Prompt Engineering and AI in Product Management7 lectures • 45min

Foundations of Effective Prompt Design7 lectures • 42min

Market Research and Competitive Analysis7 lectures • 40min

AI-Driven Ideation and Product Innovation7 lectures • 40min

Requirements Gathering and AI-Assisted Road-mapping7 lectures • 41min

User Experience (UX) Design and AI Collaboration7 lectures • 42min

AI-Augmented Product Marketing Strategies7 lectures • 42min

AI in Data Analytics and Decision Making7 lectures • 43min

Ethical and Legal Considerations in AI Adoption7 lectures • 44min

Requirements

Description

Who this course is for: