AI: Ethics & Societal Challenges
A four-week course that explores the ethical and societal implications of artificial intelligence, addressing topics such as AI bias, surveillance, democracy, consciousness, responsibility, and control, and fostering reflection and discussion on these issues.
Description for AI: Ethics & Societal Challenges
Level: Beginner
Certification Degree: Yes
Languages the Course is Available: 21
Offered by: On Coursera provided by Lund University
Duration: 3 weeks at 4 hours a week
Schedule: Flexible
Pricing for AI: Ethics & Societal Challenges
Use Cases for AI: Ethics & Societal Challenges
FAQs for AI: Ethics & Societal Challenges
Reviews for AI: Ethics & Societal Challenges
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for AI: Ethics & Societal Challenges
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.
Learn to use generative AI tools to improve data science workflows, enhance datasets, and refine machine learning models through practical projects.
Gain a comprehensive understanding of AI's potential, ethical considerations, and applications in efficient programming and common coding tasks using various LLMs.
Master Python programming for software development and data science, including core logic, Jupyter Notebooks, libraries like NumPy and Pandas, and web data gathering with Beautiful Soup and APIs.
Understand AI, its applications, concepts, ethical concerns, and receive expert career guidance.
Gain a comprehensive understanding of AI terminology, applications, development, and strategy, while navigating ethical and societal considerations in a non-technical context.
Prepare for a vocation as a data scientist. Acquire hands-on experience and in-demand skills to become job-ready in as little as five months. No prior experience is necessary.
Learn to create and diversify portfolio strategies, apply machine learning to financial data, and utilize quantitative modeling and data analytics for investment decisions.
Featured Tools
Gain a comprehensive understanding of AI applications, concepts, technological progression, software architecture, and deployment considerations across various environments.
This course covers the development, impact, and future of Generative AI through lectures, critical AI technologies, and interactive assessments.
Train, assess, and deploy an enhanced decision tree model using Azure ML Studio for predictive and scoring experiments.
Learn about AI principles and platforms like IBM Watson and Hugging Face, integrate RAG technology for chatbot intelligence, create web apps using Python libraries, and develop interfaces with generative AI models and Python frameworks.
Explore the use of generative AI tools to enhance data preparation, querying, and machine learning model development in data science workflows through hands-on projects.