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Certified AI-Generated Content Specialist
1. Introduction to AI-Generated Content
1.1 History and Evolution of Generative AI (16:32)
1.2 Key Applications in Text, Image, and Multimedia (22:11)
1.3 Impact of Generative AI Across Industies (25:33)
1.4 Opportunities and Use Cases (24:14)
1.5 Challenges in Automated Content Creation (27:14)
2. Understanding AI Algorithms for Content Generations
2.1 Basics of Neural Networks and Deep Learning (18:18)
2.2 How Transformer Models Work (BERT vs. GPT) (19:14)
2.3 Exploring the GPT Series (GPT-2, GPT-3, GPT-4) (20:42)
2.4 GANs, Diffusion Models & Comparisons (21:47)
2.5 How Algorithms Affect Tone and Creativity (21:34)
3. Tools and Platforms for Text Generation
3.1 Overview of Leading Text Tools (ChatGPT, Jasper, Copy.ai) (18:59)
3.2 Prompt Engineering Principles for Writers (19:37)
3.3 Refining Outputs with Prompt Iteration (19:43)
3.4 Templates and Frameworks for Marketing & Blogs (21:27)
3.5 Case Studies in Journalism & Storytelling (22:27)
4. Tools and Platforms for Image and Multimedia Generation
4.1 Introduction to DALL·E, Midjourney, and Stable Diffusion (24:41)
4.2 Crafting Prompts for Effective Image Creation (26:06)
4.3 Creating Visual-Text Pairs for Cohesive Narratives (22:56)
4.4 Post-Processing Tools for Image Refinement (23:31)
4.5 Use Cases - Education, Ads, Design & More (23:56)
5. Best Practices for Content Quality and Ethical Standards
5.1 Ensuring Accuracy and Consistency in AI Outputs (19:59)
5.2 Avoiding Plagiarism and Maintaining Originality (19:40)
5.3 Detecting and Mitigating AI Biases (16:39)
5.4 Misinformation, Copyright, and Legal Considerations (18:28)
5.5 Ethics, Governance, and Industry Guidelines (18:30)
5.3 Detecting and Mitigating AI Biases
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