Data Ethics, AI and Responsible Innovation
Become an ethical AI practitioner by developing the ability to identify and resolve ethical challenges in AI and data science initiatives.
Description for Data Ethics, AI and Responsible Innovation
Critical Issues in Data Lifecycle: Understand the critical, social, legal, political, and ethical issues that arise throughout the data lifecycle.
Key Ethical Concepts: Gain an understanding of the concepts of ethics, morality, responsibility, digital rights, data governance, and human-data interaction in the context of data practices.
Ethical Issues in Data Science: Apply critical judgment to identify and assess the current ethical challenges in the data science and industry.
Ethically Driven Solutions: Ensure responsible decision-making by developing and applying ethically driven solutions to moral problems in your professional practice.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On edX provided by EdinburghX
Duration: 3�4 hours per week approx 5 weeks
Schedule: Flexible
Pricing for Data Ethics, AI and Responsible Innovation
Use Cases for Data Ethics, AI and Responsible Innovation
FAQs for Data Ethics, AI and Responsible Innovation
Reviews for Data Ethics, AI and Responsible Innovation
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for Data Ethics, AI and Responsible Innovation
The AI tool empowers non-programmers to construct and deploy AI, featuring data transformation, insights generation, identification of critical drivers, and prediction and forecasting functionalities to enhance business decision-making and planning processes.
NovaceneAI streamlines the organization of unstructured text data with AI algorithms, offering dedicated cloud hosting, adaptability across sectors, and robust data privacy measures.
Posit offers a comprehensive platform with enterprise solutions, cloud applications, community resources, and deployment solutions to enhance productivity in data science teams.
Utilize generative AI to advance in the field of data science. Develop hands-on generative AI skills that are in high demand to accelerate your data science career in under one month.
Acquire the knowledge necessary to direct your AI voyage. In this program, a CEO will instruct you on how to become a hands-on, AI-powered leader who is prepared to unlock the transformative potential of GenAI for your organization.
Learn to leverage Generative AI for automation, software development, and optimizing outputs with Prompt Engineering.
Learn to use generative AI tools to improve data science workflows, enhance datasets, and refine machine learning models through practical projects.
Learn machine learning with Google Cloud. End-to-end machine learning experimentation in the real world
Utilize Generative AI to optimize marketing creativity. Explore the potential of Generative AI to revolutionize and influence your marketing organization.
Learn how to leverage GenAI's capabilities and manage its risks to enhance decision-making, productivity, and customer value in organizations.
Featured Tools
Gain foundational knowledge of Linear Algebra and Machine Learning models, explore the scalability of SparkML and Scikit-Learn, and gain practical experience by adjusting models and analyzing vibration sensor data in a real-world IoT example.
Gain practical experience in optimizing, deploying, and scaling machine learning models using Google Cloud Platform through a structured five-course specialization with hands-on labs and a focus on advanced topics and recommendation systems.
Gain expertise in deploying and managing LLMs on Azure, optimizing interactions with Semantic Kernel, and applying Retrieval Augmented Generation (RAG) techniques.
With an emphasis on fairness measurement methods, the course teaches students how to use the Aequitas Tool to identify bias in machine learning models.
Enhance your Product Manager career with Gen AI. Boost your Product Manager career in under two months by developing hands-on, in-demand generative AI skills. No prior experience is required to initiate the process.