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Rishabh Jain, Madonna Thomas, and Fractal Analytics

Ready to revolutionize your design process? In today's fast-paced world, creating products and services that truly resonate with users is paramount.

This course dives deep into the power of human-centered design, exploring how Design Thinking and user research can transform your approach to creating impactful solutions. In this course, you'll learn how to harness the potential of generative AI to supercharge your design process, from gathering insights to generating innovative ideas.

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Ready to revolutionize your design process? In today's fast-paced world, creating products and services that truly resonate with users is paramount.

This course dives deep into the power of human-centered design, exploring how Design Thinking and user research can transform your approach to creating impactful solutions. In this course, you'll learn how to harness the potential of generative AI to supercharge your design process, from gathering insights to generating innovative ideas.

Discover how to seamlessly integrate AI tools into your workflow to master user research, extract meaningful data, and generate groundbreaking strategies. This course will equip you with the knowledge and skills to create truly user-centric experiences while understanding the ethical implications of AI. By the end of this course, you'll be able to confidently apply AI-powered design thinking to deliver exceptional products and services.

You will also master AI tools for user research, synthesize and interpret research data, and apply AI to generate strategic insights.

All you need is a curious mind and a will to learn. Experience as Design Thinking practitioner, or as Business Consultants would be an added advantage. This course does not need any programming skills.

Enroll now

What's inside

Syllabus

Preparation for Discovery
This module explores the transformative role of Artificial Intelligence in user research, offering a comprehensive understanding of how AI can enhance and streamline various research processes.
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Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Emphasizes the importance of user research, which is critical in the design industry
Leverages AI, which is a significant trend in modern design
Instructors have a strong reputation in the field of design
Covers the application of AI in the design process, including topics like generative AI and ethical considerations
Provides a comprehensive overview of the design thinking process

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Reviews summary

Generative ai for ux design & research

According to students, this course offers a highly relevant and timely introduction to integrating Generative AI into User Research and Design Thinking. Learners appreciate its focus on practical application, enabling them to master AI tools for user research and apply them to generate strategic insights. The course is particularly beneficial for professionals seeking to supercharge their design process without needing programming skills. It provides a solid understanding of human-centered design principles and thoughtfully addresses the ethical implications of AI. While generally well-received for its comprehensive overview, some advanced learners might seek deeper technical dives into specific AI models beyond introductory applications, suggesting a need for more advanced case studies.
Thoughtfully covers the ethical aspects of AI in design, promoting responsible practice.
"I really valued the discussions on the ethical implications of using AI in user research; it's so important in today's world."
"The course's focus on responsible AI usage gave me a much-needed perspective on applying these powerful tools ethically."
"It was crucial to learn about the ethical side of applying AI in design thinking to ensure fair and unbiased outcomes."
Strong emphasis on synthesizing research data using AI for strategic insights.
"The modules on synthesizing primary research data with AI-driven techniques were incredibly helpful."
"I learned practical techniques like AI-driven affinity mapping to extract key themes from user data."
"Generating user journeys using Chat GPT was a powerful takeaway for understanding user behavior and preferences."
Empowers non-technical professionals to leverage AI without prior coding experience.
"As a designer with no coding background, I found the course surprisingly accessible and empowering."
"It's great that I didn't need any programming skills to grasp the AI concepts and apply them practically."
"The instructors made complex AI concepts understandable for someone like me who isn't a coder."
Addresses cutting-edge trends, offering immediate practical application for design professionals.
"I found the content incredibly timely and directly applicable to current industry demands in UX and design."
"This course genuinely helped me understand how to integrate AI tools into my daily design workflow effectively."
"I appreciate how it focused on practical strategies to use generative AI for user research, not just theory."
May offer less advanced technical detail for those already familiar with core AI concepts.
"I was hoping for a bit more in-depth exploration of various generative AI models beyond just introductory ChatGPT applications."
"For someone with prior AI knowledge, some sections felt a little basic; an intermediate or advanced track would be great."
"Could use more complex real-world case studies to challenge experienced design professionals applying these tools."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Generative AI in User Research and Design Thinking with these activities:
Read 'Design Thinking for Innovation' by Thomas Lockwood
Expand your understanding of Design Thinking principles and their application in various industries
Show steps
  • Read the book thoroughly, taking notes on key concepts and examples
  • Identify how the principles discussed in the book relate to the course content
Brush up on Design Thinking concepts
Review the fundamentals of Design Thinking to strengthen your understanding and prepare for the course
Browse courses on Design Thinking
Show steps
  • Review key principles of Design Thinking, such as empathy, iteration, and user-centricity
  • Explore examples of successful Design Thinking applications
Explore Generative AI Tools for Insights
Familiarize yourself with generative AI tools to enhance your research and ideation processes.
Browse courses on Generative AI
Show steps
  • Identify generative AI tools for user research and insights.
  • Explore tutorials and resources to understand their capabilities.
  • Experiment with using generative AI to generate ideas and gather insights.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Conduct User Interviews
Practice conducting user interviews to enhance your understanding of user needs and preferences.
Browse courses on User Research
Show steps
  • Identify research objectives and target user profiles.
  • Prepare interview questions and schedule sessions.
  • Conduct interviews and document key insights.
Attend a Design Thinking workshop or conference
Immerse yourself in the principles and practices of Design Thinking through hands-on activities and expert insights
Browse courses on Design Thinking
Show steps
  • Research and identify relevant Design Thinking workshops or conferences
  • Register and attend the event
  • Actively participate in the activities and discussions
Design User Personas
Develop user personas to create realistic representations of your target audience, aiding in decision-making.
Browse courses on User Personas
Show steps
  • Gather data from user interviews and research.
  • Identify common patterns and characteristics.
  • Create user persona profiles, including demographics, behaviors, and motivations.
Learn to use a generative AI tool for user research
Become familiar with an AI tool that can assist in gathering insights from user data
Browse courses on Generative AI
Show steps
  • Choose a generative AI tool and sign up for an account
  • Follow step-by-step tutorials to learn the basics of the tool
  • Practice using the tool to generate ideas and insights based on sample user data
Conduct mock user interviews
Gain practical experience in interviewing users to gather valuable insights
Browse courses on User Interviews
Show steps
  • Identify potential interview participants and schedule sessions
  • Prepare interview questions that align with the course modules
  • Practice conducting interviews in a structured and empathic manner
Engage in peer review and feedback sessions
Share your work with peers and receive constructive feedback to enhance your designs
Browse courses on Peer Review
Show steps
  • Organize review sessions with fellow students
  • Present your design concepts and gather feedback
  • Incorporate feedback into your design iterations
Build an AI-Powered User Journey Map
Create an AI-powered user journey map to visualize and optimize user experiences throughout their interactions.
Browse courses on User Journey Mapping
Show steps
  • Define user journey stages and touchpoints.
  • Use generative AI to identify pain points and opportunities.
  • Develop AI-informed strategies to improve the user journey.
Develop a UX persona based on research findings
Synthesize research data into a comprehensive persona that represents your target user
Browse courses on User Research
Show steps
  • Analyze interview data and identify common patterns and themes
  • Create a detailed profile of a representative user, including demographics, motivations, and pain points
  • Use the persona to guide your design decisions throughout the course
Contribute to an open-source design project
Apply your skills and knowledge by contributing to a real-world design project
Browse courses on Open Source
Show steps
  • Find an open-source design project that aligns with your interests
  • Review the project documentation and identify areas where you can contribute
  • Make contributions to the project, such as code improvements or design enhancements

Career center

Learners who complete Generative AI in User Research and Design Thinking will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Generative AI in User Research and Design Thinking.
The definitive benchmark textbook of modern artificial intelligence, rigorously unifying search algorithms, probabilistic reasoning, knowledge representation, and machine learning into an elegant, coherent agent-based framework.
Wharton professor Ethan Mollick delivers the essential human-AI collaboration playbook for ChatGPT users. Explains the jagged frontier of model capabilities, four core principles for co-intelligence, and practical workflows for writing, brainstorming, research, and strategic decision-making.
A monumental foundational text establishing the mathematical, algorithmic, and statistical principles of modern deep neural networks, from linear algebra and optimization to convolutional and sequence modeling architectures.
Offers a comprehensive look at the mindset and practices of effective UX researchers. It covers planning, conducting, analyzing, and communicating research findings to influence design and business strategy. It valuable resource for aspiring and practicing UX researchers seeking to develop a strategic approach to their work. The second edition incorporates recent changes in the field, including remote methods and bias.
Is an excellent starting point for anyone new to UX research. It demystifies the research process and provides practical guidance on when and how to conduct research without getting bogged down in overly academic methods. It emphasizes integrating research throughout the design process, making it valuable for students and professionals alike. This book serves as a foundational text for understanding the core principles of user research.
Provides a foundational understanding of Design Thinking from the CEO of IDEO, a leading design firm. It explains the principles and process of Design Thinking and how it can be applied to drive innovation in various organizations and aspects of life. It's an excellent starting point for gaining a broad understanding of the topic. An updated edition was published in 2019.
Provides an exceptionally practical, code-first curriculum that guides engineers from end-to-end data preprocessing and traditional regression pipelines to production deep learning models and generative neural networks.
Systematic O'Reilly framework that moves ChatGPT practitioners beyond brittle prompt hacks into repeatable engineering. Covers direction setting, few-shot exemplars, structured output formatting, chain-of-thought reasoning, and automated evaluation across text and multimodal workflows.
Delivers an authoritative mathematical foundation in Bayesian inference, graphical models, and statistical learning algorithms, bridging foundational probability theory with rigorous predictive computational modeling.
Authoritative systems blueprint for turning ChatGPT-class foundation models into dependable production software. Guides builders through prompt engineering, retrieval-augmented generation, fine-tuning trade-offs, latency optimization, and rigorous evaluation pipelines.
Deep dive into the fundamental qualitative research method of interviewing. It provides detailed techniques and practical advice for conducting effective user interviews to gain valuable insights into user needs and behaviors. It crucial resource for anyone planning to conduct user interviews, a common practice in UX research. The second edition includes updated information on remote research and analysis.
Guides engineers step-by-step through implementing, training, and fine-tuning complete generative transformer architectures in pure PyTorch, providing crystal-clear low-level insight into modern foundation models.
Visual, intuitive tour of the transformer architecture, tokenization, and embedding spaces powering ChatGPT. Equips learners with clear mental models and runnable Python examples for semantic search, text generation, RAG, and parameter-efficient fine-tuning.
Crafted by early GitHub Copilot architects, exploring how to design prompts programmatically as first-class software interfaces. Teaches context window budgeting, dynamic snippet assembly, grounding strategies, and deterministic output parsing for GPT-style models.
Presents the foundational treatise on Markov decision processes, temporal-difference learning, and policy gradient methods that underpin autonomous decision-making and modern post-training alignment workflows.
Considered a benchmark in usability testing, this handbook provides detailed guidance on every aspect of planning, designing, moderating, and reporting usability tests. It's an essential reference for anyone conducting usability studies.
Examines holistic architectural patterns for designing resilient machine learning infrastructure, addressing data pipelines, real-time feature stores, continual learning loops, and production deployment reliability.
Provides a comprehensive overview of user research methods, including observation.
Classic in the field of design and provides insights into the principles of human-centered design.
Demystifies practical transformer model implementation through the Hugging Face ecosystem, demonstrating how to fine-tune, optimize, and deploy attention architectures across diverse natural language processing and understanding tasks.
Provides a practical guide to using generative AI, covering the different techniques and tools available. It is written by two leading experts in the field, Josh Patterson and Adam Gibson.
Seminal treatise by UC Berkeley AI pioneer Stuart Russell examining why maximizing fixed objectives fails and how machines must learn human preferences instead. Provides the conceptual bedrock behind reinforcement learning from human feedback (RLHF) that makes ChatGPT safe and helpful.
While a broader design book, this is considered a foundational text for anyone in the field of user-centered design, including UX research. It introduces key principles of design based on human psychology and behavior. Understanding these principles is essential for conducting effective UX research.
Focused developer handbook for building Python applications atop OpenAI's ChatGPT and GPT-4 APIs. Demonstrates chat completions, function calling, structured JSON modes, embeddings, RAG architectures, and fine-tuning through clear, production-minded code examples.
Delivers battle-tested operational patterns for serving foundation models, addressing GPU cluster throughput, semantic caching, automated evaluation benchmarks, and continuous latency minimization.
Accessible, balanced primer explaining how ChatGPT and modern generative models work alongside their real-world risks and capabilities. Covers prompt design, hallucination mitigation, copyright, privacy, and organizational adoption without requiring deep math.
Argues for the importance of Design Thinking in business strategy and achieving a competitive advantage. It's particularly relevant for those in business programs or working professionals looking to understand the strategic implications of Design Thinking.
Delves into the crucial aspect of empathy in understanding users. It provides methods for conducting listening tours and analyzing the data to build a deep understanding of people's thinking and motivations. It is highly relevant for foundational and deepening understanding of qualitative research and user-centered design.
Details an applied architectural methodology for running high-performance open-weights models on local workstations, tackling quantization fidelity, memory bandwidth limits, and prompt assembly trade-offs.
Written by the founders of IDEO, this book focuses on unlocking creativity, a crucial element of Design Thinking. It provides insights and exercises to help individuals and teams build confidence in their creative abilities and apply them to problem-solving.
Standard Stanford computational linguistics textbook anchoring ChatGPT in decades of natural language processing theory. Rigorously covers language modeling, vector semantics, neural sequence models, transformers, attention mechanisms, and dialogue systems.
Practical everyday handbook for getting sharper, more reliable results from ChatGPT across writing, coding, analysis, and creative ideation. Introduces role framing, iterative refinement, chain-of-thought cues, and custom GPT workflows for non-specialists.
Offers a rigorous theoretical foundation for reasoning under uncertainty, combining graph theory and probability distributions to model complex high-dimensional dependencies across autonomous intelligent systems.
Modern 2025 Manning playbook tailored to systems engineers, analysts, and technical practitioners integrating ChatGPT into daily operations. Covers prompt automation, documentation drafting, scripting assistance, data governance, and enterprise security guardrails.
Introduces core computational linguistics concepts and practical tokenization, tagging, and syntactic parsing workflows through clear Python examples, establishing strong fundamentals for language analysis.
Introduces the concept of continuous discovery, emphasizing the importance of integrating research ongoingly throughout the product development lifecycle. It provides practical habits and techniques for teams to continuously learn about their users and opportunities. It's highly relevant for modern product development environments.
Foundational text covering a wide range of user research methods beyond just observation. It provides detailed guidance on planning and conducting various types of studies, analyzing data, and reporting findings. While an older edition exists, it remains a valuable reference for understanding established research practices.
Synthesizes the five foundational tribes of machine learning into a unified conceptual framework, illuminating how symbolists, connectionists, evolutionaries, Bayesians, and analogizers approach intelligence.
Explores how Design Thinking can be applied to address complex social problems and drive innovation in the social sector. It provides case studies and practical insights for those interested in using Design Thinking for social impact.
Forward-looking O'Reilly manual showing how conversational models like ChatGPT evolve into autonomous, tool-using AI agents. Details multi-agent orchestration, memory architectures, reflection loops, API tool integration, and agent evaluation strategies.
This playbook offers a comprehensive guide to applying Design Thinking for digital transformation. It's a relevant resource for understanding how Design Thinking intersects with contemporary digital challenges.
Focused guide on designing and conducting effective surveys, a common quantitative method in UX research. It provides practical advice on writing good survey questions, recruiting participants, and analyzing survey data. It's a valuable resource for anyone using surveys in their research.
Project-oriented Python guide to OpenAI's developer ecosystem beyond the ChatGPT web interface. Walks through the Assistants API, Whisper speech recognition, DALL-E image generation, custom embeddings, and deploying end-to-end conversational web services.
Gripping narrative connecting cognitive science, fairness research, and reinforcement learning to explain why aligning language models with human intent is so difficult. Essential context for understanding reward modeling, bias, and RLHF in ChatGPT.

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