English | MP4 | AVC 1280×720 | AAC 44KHz 2ch | 50 lectures (3h 0m) | 2.45 GB
Master AI Ethics from Data Collection to Deployment: A Complete Guide to Ethical AI
The AI Ethics Course: Preparing You for the Real-World Challenges of AI—Today and Tomorrow
Do you want to gain critical AI skills while ensuring ethical and responsible use in your organization?
If so, you’re in the right place!
As AI grows more powerful and integrated into everyday life, building and using it responsibly has never been more important. This AI Ethics course offers an in-depth understanding of artificial intelligence’s ethical challenges.
Unlike other AI ethics courses, this one teaches you to identify and manage ethical risks throughout the entire AI lifecycle—from data collection and model development to deployment. Whether building language models, deploying generative AI, or using tools like ChatGPT, our resources ensure your work upholds key ethical principles: privacy, fairness, transparency, and accountability.
Why Take This Course?
Comprehensive Curriculum: Follow a structured journey—from AI basics to advanced ethical topics like regulatory compliance and digital equity.
Practical + Philosophical: This isn’t just theory. You’ll explore real-life examples, apply ethical thinking to hands-on AI scenarios, and walk away with actionable strategies.
Current and Global: Stay updated with the most recent developments in AI and data governance, including the EU AI Act, GDPR, HIPAA, and the future of global frameworks.
ChatGPT Case Studies: Learn to apply ethical thinking to large language models use cases (LLMs). Explore such issues as data privacy, misinformation, inconsistency, and more.
This AI Ethics course simplifies complex ethical issues from user, business, and developer perspectives. You’ll learn to distinguish proprietary, public, and web-scraped data and understand their unique challenges. Key topics—including data bias, supervised fine-tuning, AI hallucinations, deepfakes, plagiarism, and risk management—are explored thoroughly. A key course component is the ChatGPT section—one of today’s leading AI tools—highlighting real-world issues and engaging conversational examples.
Are you ready to stand out as a professional who understands the latest AI trends and the ethical responsibilities that come with them?
Today, nearly everyone interacts with AI. It’s essential to prepare your organization for responsible engagement. Don’t fear emerging technology—lead by understanding, questioning, and using it ethically.
The demand for AI ethics specialists is skyrocketing. Isn’t it time for you to become one?
What you’ll learn
- Understand the ethical challenges surrounding AI
- Examine ethical principles like transparency, fairness, privacy, and accountability
- Explore the intersection of AI ethics and laws, including GDPR and the EU AI Act
- Analyze real-world ethical dilemmas in AI applications
- Review responsible AI development strategies
- Discover the risks of AI deployment, such as misinformation, hallucinations, and intellectual property concerns
- Learn about ChatGPT’s ethical implications
Table of Contents
Welcome to the Course
1 What does the course cover
2 Intro to AI
3 AI vs Data science vs Machine learning
4 The AI Lifecycle From data collection to model application
Introduction to AI and Data Ethics
5 The rise of generative AI and its ethical challenges
6 Why AI Ethics matter more than ever
7 Ethics vs laws
The Core Principles of AI Ethics
8 Privacy
9 Transparency
10 Accountability
11 Fairness
Ethical Data Collection
12 Ethical sourcing and types of data
13 Proprietary data
14 Public data
15 Web-scraped data
16 Dealing with sensitive and protected information
17 Data bias and fair representation
Ethical AI Development
18 Ethical challenges in working with labeled data
19 Ethical considerations for unlabeled data
20 Ethical challenges in unsupervised training
21 Ethical considerations for supervised Fine-tuning
22 RLHF and ethical AI behavior
23 Inclusive and fair AI development practices
Ethical AI Deployment
24 Intellectual property and user consent in AI interactions
25 Ethical responsibilities of foundation model developers
26 Common issues in foundation models Open-source data
27 Inconsistency
28 Hallucination
29 Ongoing monitoring and risk mitigation for deployed AI
Ethical AI for End-Users Businesses
30 Access to AI technology for businesses of all sizes
31 Transparency in AI decision-making processes
32 Ethical use of AI outputs in business
33 Responsible AI adoption and risk management for businesses
Ethical AI for End-Users Individuals
34 Equity in access to AI technology
35 Ethical considerations in human-AI collaboration
36 Responsible use of AI-generated outputs
ChatGPT Ethics
37 Understanding ChatGPT
38 Privacy concerns with ChatGPT
39 OpenAI’s privacy policies and data handling
40 Misinformation and AI-generated content
41 ChatGPT plagiarism
42 Responsible use of ChatGPT What you can and can’t do
43 ChatGPT and the environment
Data and AI Regulatory Frameworks
44 Global AI and data regulations
45 European Union GDPR and the EU Artificial Intelligence Act
46 United States AI regulation across states
47 Asia-Pacific region Strong government control
48 Africa’s push for AI governance
49 International frameworks and standards
50 The future of AI Ethics What should we worry about
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