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  1. Courses
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  3. GenAI for Product R&D Teams

GenAI for Product R&D Teams

This course, "GenAI for Product R&D Teams," introduces integrating GenAI in product research and development, highlighting its potential to accelerate innovation, enhance creativity, and optimize strategies for R&D professionals.

Reza Moradinezhad
Soheil Haddadi
Soheil HaddadiReza Moradinezhad
Data Science | core | 1 hour 30 minutes |   Published: Aug 2024
In partnership with:  Coursera

    Discussions

Overview

1KSTUDENTS*
98.9%RECOMMEND*

This course includes:

  • 1.5 hour of on-demand video  
  • Certificate of completion  
  • Direct access/chat with the instructor 
  • 100% self-paced online 

"GenAI for Product R&D Teams" offers an introductory exploration into the innovative integration of GenAI within product research and development processes. Tailored for R&D professionals, this course highlights the transformative potential of GenAI in accelerating product innovation, enhancing creative processes, and optimizing development strategies. Learners will be introduced to foundational GenAI concepts, tools, and methodologies that can be leveraged to drive efficiency, foster creativity, and navigate the competitive landscape of product development. 

Through practical examples, case studies, and industry insights, participants will understand how GenAI can be applied to various stages of product development, from ideation to prototyping to testing. This course aims to demystify GenAI technologies, illustrating their practical benefits and ethical considerations, to empower R&D teams in harnessing GenAI's full potential. Whether you're looking to streamline your R&D processes, enhance product innovation, or explore new development horizons, this course provides the necessary knowledge and skills to embark on your GenAI journey. 

Skills You Will Gain

Case Studies
Ethical Considerations
Foundational Concepts
Industry Insights
Practical Examples

Learning Outcomes (At the end of this program you will be able to)

  • Acquire a foundational understanding of GenAI tools and discover strategies to enhance team collaboration and operational efficiency. 
  • Develop essential skills in applying GenAI to streamline communication, manage projects, and bolster creative efforts within product R&D teams and across departments. 
  • Explore the integration of GenAI technologies into product R&D workflows to drive innovation, amplify creative results, and refine decision-making processes. 
  • Analyze the potential ethical implications of utilizing GenAI in product R&D, learn to address potential challenges, and ensure the ethical use of AI technologies within product R&D practices. 
  • Create a framework to continuously adapt to and leverage ongoing advancements in GenAI technology. 

Prerequisites

Learners should have a fundamental understanding of product R&D principles and strategies as well as an eagerness to learn and adapt to new technologies. 

Who Should Attend

This course is tailored for R&D Managers and Team Leads to enhance leadership and innovation skills, Product Developers to gain practical GenAI application skills, Design Engineers to integrate AI into workflows, and Training Specialists to create effective GenAI tool demonstrations for continuous learning.

 

 

Curriculum

Instructors

Frequently Asked Questions

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*Where courses have been offered multiple times, the “# Students” includes all students who have enrolled. The “%Recommended” shown is also based on this data.
1Module 1: GenAI for Product R&D Teams
Reza Moradinezhad

Reza Moradinezhad

Reza is a passionate advocate for fostering effective and trustworthy collaboration between humans and artificial intelligence, with a strong commitment to advancing the ethical use of Generative AI. Holding a PhD in Computer Science from Drexel University, his research focuses on enhancing human trust in Embodied Virtual Agents (EVAs). Through collaborations with prestigious institutions such as MIT Media Lab, CMU HCII, Harvard University, and UCSD, Reza has contributed impactful research published in leading journals like Springer Nature, ACM CHI, and ACM C&C. His work has gained recognition from the academic community, earning him accolades such as the Outstanding Reviewer award by ACM ICMI 2019 and ACM CHI 2021. His research has also been featured in media outlets including The Next Web, TechXplore, and CBS News.

As an Assistant Teaching Professor at Drexel University's College of Computing and Informatics, Reza has shaped the minds of both undergraduate and graduate students, guiding them through complex topics such as Artificial Intelligence, Software Engineering, and Computer Graphics. His dedication to education extends beyond teaching, mentoring research projects on topics ranging from mind-wandering in the human brain to the effectiveness of creativity support tools in fostering innovation.

In addition to his academic work, Reza served as an AI Scientist at TulipAI, where he focused on ensuring the ethical and responsible application of Generative AI in media creation. He is driven by the vision of making AI more trustworthy for humanity and believes in designing transparent, fair, and responsible interactions with AI systems. Through his work, Reza aims to harness the full potential of AI while adhering to ethical principles and promoting responsible innovation.

With a proven track record in academic research, collaborative projects, and a deep passion for ethical AI development, Reza is committed to making significant contributions to the evolving field of Human-AI interaction.

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Soheil Haddadi

Soheil Haddadi

Soheil is a Postdoctoral Researcher with a strong academic foundation in Control and Automation Systems Engineering, specializing in Artificial Intelligence. His expertise spans across Data Science, Machine Learning, LLMs, Deep Learning, Natural Language Processing (NLP), and Robotics. Soheil has successfully applied his skills in both industry and research environments, contributing to advancements in AI.

Currently, as a Postdoctoral Researcher, Soheil is dedicated to pushing the boundaries of AI. His technical proficiency in Python, SQL, TensorFlow, and Keras, combined with a deep understanding of AI methodologies, has enabled him to deliver innovative solutions and insights. His prior work includes leading diverse projects such as sales forecasting using time series and LSTM neural networks, autonomous indoor navigation for quadrotors using ORB-SLAM, and deep learning-based credit scoring in the banking sector.

Soheil’s experience in data analysis and visualization further enhances his comprehensive understanding of how AI can address complex problems and create tangible value. His contributions are a testament to his dedication to advancing AI research and its real-world applications.

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Segment 01 - Introduction to GenAI for Product R&D Teams

Segment 02 - Resources for GenAI for Product R&D Teams

Segment 03 - The GenAI Future-Ready Framework for Product R&D Teams

Segment 04 - Ethical Concerns and Remediating Risks

Segment 05 - Demo for Creating an App Using Various GenAI Tools

Segment 06 - Practice Project for Product R&D Teams

Segment 07 - Collaborative Strategies with GenAI

Segment 08 - GenAI in Project Management

Segment 09 - GenAI for Boosting Creativity & Communication

Segment 10 - Best Practices for Protecting Against Plagiarism

Segment 11 - Closing Thoughts: What’s Next