Data Science

Data Ethics, AI and Responsible Innovation

(0 reviews)
Share icon
eDX

Become an ethical AI practitioner by developing the ability to identify and resolve ethical challenges in AI and data science initiatives.

Key AI Functions:data science, big data, information privacy, machine learning, innovation, facial recognition, intelligent systems, data ethics

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

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

Learn to apply advanced machine learning and deep learning models to real-world challenges by immersing yourself in the cutting-edge world of AI-powered finance and insurance.

#bitcoin #financial services
Visit icon

Gain extensive knowledge in AI technologies relevant to digital marketing, involving precise data analysis, content creation, and tools for optimizing social media and consumer segmentation.

#social media #market research
Visit icon

Examine how to improve learning and preserve integrity by incorporating morally sound and useful AI tools into evaluation procedures.

#artificial intelligence #education
Visit icon

Acquire practical expertise in the integration of machine learning models into pipelines, optimizing performance, and efficiently managing versioning and artifacts.

#software versioning #operations
Visit icon

Study the ethical consequences of AI development and implementation, emphasizing generative AI, AI governance, and pragmatic ethical decision-making in practical contexts.

#artificial intelligence #machine learning
Visit icon

In this course, students gain the skills necessary to use Python for data science, machine learning, and foundational applications of artificial intelligence.

#scientific methods #data science
Visit icon

Gain an extensive understanding of TinyML applications, fundamental principles, and the ethical development of artificial intelligence.

#artificial neural networks #smartphone operation
Visit icon

A thorough grasp of artificial intelligence (AI) and machine learning, including its various forms, methods, and applications, is given in this course.

#artificial intelligence #data science
Visit icon

The material equips data engineers to incorporate machine learning models into pipelines while adhering to best practices in collaboration, version control, and artifact management.

#machine learning #data engineering
Visit icon

From fundamental concepts to advanced methods such as deep learning and ensemble techniques, this program provides a comprehensive examination of machine learning techniques.

#algorithms #unsupervised learning
Visit icon