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Aims | Target Audience | Objectives | Date, Fee & Registration | Last Class | Track Record
Offical Course Title: DesignThinkers Academy (2-Day) AI Design Thinking Fundamentals Training Course
Part 1: Course Objectives and Participant Outcomes
AI-Driven Design Thinking Method (DT3.0) leverages advanced technologies to redefine strategic innovation, offering unparalleled competitive advantages. This cutting-edge approach not only propels your business ahead but also revolutionizes the landscape of strategy and technology. Through DT3.0, experience three pivotal breakthroughs:
- Accelerating innovation with a remarkable speed boost of up to 94% [Details]
- Enhancing strategic decisions with a 90% accuracy rate in market demand analysis [Details]
- Integrating your business goals with vital ESG development strategies [Details]
This interactive course will provide you with the skills, tools, and technologies of design thinking to help drive rapid and accurate product and service innovation. You will participate in a highly interactive learning journey, engage in teamwork, and solve challenges under the guidance of experienced instructors using AI tools to enhance the management effectiveness of design thinking innovation.
The course is carefully designed so that even business leaders who are unfamiliar with design thinking and the use of artificial intelligence tools can learn smoothly.
Comparison of traditional Design Thinking (DT 1.0) and AI Design Thinking (DT 3.0) in terms of skills, tools, and technologies:
| Traditional Design Thinking (DT 1.0) | AI-Driven Design Thinking (DT 3.0) | |
| Stage 1 Discover Root-Cases | Focuses on in-person interactions and direct observations with users, relying heavily on human intuition and empathy to gather meaningful insights from observed behaviors. | Leverages Social Listening Technologies to collect vast and complex datasets, enabling the analysis of user preferences and behaviors to uncover actionable, deep insights. |
| Stage 2 Define Opportunities | Relies on shared understanding and collaborative interpretations to identify and articulate user needs effectively. | Harnesses DALL-E to create visual representations of deep user insights, enabling a more precise reflection of evolving market trends and user behavior. |
| Stage 3 Develop Ideas | Encourages the generation of innovative ideas through collaborative brainstorming sessions and interactive creative workshops. | Utilizes Stormz to facilitate idea generation, fostering innovation with Fresh-Eye perspectives and Fresh-Mind approaches. |
| Stage 4 Deliver Solutions | Involves creating physical prototypes and conducting user testing to guide product iterations, with adjustments driven by direct user feedback. | Employs AICG for rapid prototyping and testing, utilizing machine learning models to predict user responses and dynamically refine designs based on real-time feedback. |
Part 2: Target Audience:
- Business Managers and Owners: Individuals hoping to enhance performance through innovation in “products,” “services,” and “marketing.”
- Innovation Team Members: Responsible for participating in corporate transformation or business improvement plans.
- Traditional Design Thinkers: Individuals currently applying Design Thinking 1.0 methods and tools for innovation or problem-solving.
- Business Leaders: Leaders responsible for enhancing corporate innovation effectiveness or fostering an innovative culture.
Part 3: Major Learning Objectives
Upon completion of the new program, you will be able to
(1) Master Design Thinking Principles, Values and Execution Framework (Double Diamond Model) for advanced problem-solving tasks, product or service innovations, & business transformation
(2) Explore how to achieve the optimal balance between “AI-driven market data analysis” and “human-centric emotional connection with users” in user-oriented innovation projects.
(3) Investigate artificial intelligence applications that can directly enhance the effectiveness and efficiency of innovation projects, such as Social Listening Technologies, Sentiment Analysis, and AICG.
(4) Understand the “Design Thinking Five-Day Rapid Implementation Model—Design Sprint” to help launch innovative products and services to market in a shorter timeframe.
(5) Understand how to form an innovative team with individuals from different professions (or departments), encouraging “Embracing a Growth Mindset” and “High-Level Co-creation” to enhance the success rate of innovation projects.
Learning approach: Learning by Doing (Practices: 50% | Lecturing: 20% | Case study: 20% | Reflection: 10% )
Part 4: Date, Fee and Registration:
Pre-class Self-Study: 13-set of Self-Paced Learning Videos of “How AI & Data Enhance the Effectiveness of Design Thinking Execution“
Date & Time for the 2-Day class: 8 & 9 Aug 2025 | 0915 to 1300 and 1400 to 1800 (Total: 15.5 hours)
Teaching Mode: Face-to-face instruction. Includes up to 10 international and local cases from Hong Kong and China, incorporating 8 sets of business innovation techniques (integrating 7 sets of artificial intelligence tools). [The case studies will be adjusted based on the participants’ backgrounds and progress.]
Case Studies: Please click here for details
Language: Cantonese Presentation with English Materials
Mode: Face-to-Face Training Mode
Course Leaders and Facilitators:
Our trainers are seasoned and certified Design Thinking facilitators. They will share their extensive experience and effective strategies for implementing Design Thinking in innovation projects and organizational transformations. This practical approach enables you to integrate Design Thinking into your daily work environment immediately.
Tuition Fee:
For HK Classes: HK$6,500 (Early Bird, One Month Before Class Start) | HK$ 7,000 (Standard Price)
For Mainland China Classes: RMB 6,500 (Early Bird | 1-month before the first lesson) | RMB 7,000 (Standard Price)
Part 5: Snapshot of the Last Class (Please click the below picture for details)
Part 6: Track Record
The previous 27 public classes of the DTA Design Thinking Fundamentals course are listed below:
2025 (26th to 27th Cohort): 17 May | 22 Feb
2024 (22nd to 25th Cohort): 30 Nov | 3 Oct | 19 Jul | 17 May
2023 (19th to 21st Cohort): 21 Oct | 22 Jul | 14 Apr
2022 (15th to 18th Cohort): 20 Oct | 7 Jul | 26 Apr | 17 Mar
2021 (10th to 14th Cohort): 2 Dec | 12 Oct | 19 Aug | 11 Mar | 16 Jan
2020 (5th to 9th Cohort): 19 Nov | 19 Aug | 3 Jul | 13 May | 16 Jan
2019 (1st to 4th Cohort): 2 Nov | 28 Sep | 26 Sep | 15 Aug
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