Today, corporates are moving toward the adoption of Design-Thinking techniques to develop products and services, putting their consumer as the heart of the development process. Tim Brown, president, and CEO of IDEO, defines design thinking as "A human-centered approach to innovation that draws from the designer's toolkit to integrate the needs of people, the possibilities of technology, and the requirements for business success". The application of design thinking has been witnessed to be the road to develop innovative applications, interactive systems, scientific software, healthcare application, and even to utilize Design Thinking to re-think business operation as the case of Airbnb. Recently, there has been a movement to apply design thinking to machine learning and artificial intelligence to ensure creating the "waw" affect to consumers. ACM Taskforce on Data Science program states that "Data Scientists should be able to implement and understand algorithms for data collection and analysis. They should understand the time and space considerations of algorithms. They should follow good design principles developing software, understanding the importance of those principles for testability and maintainability" However, this definition hides the user behind the machine who works on data preparation, algorithm selection and model interpretation. Thus, Data Science program to include design thinking to ensure meeting the user demands, generating more usable machine learning tools, and developing new ways of framing computational thinking In this poster, we describe the motivation behind injecting DT in Data Science programs, an example course, its learning objective and teaching modules.