Courses Descriptions
"Learn the basics of Generative AI and Large Language Models, how they work, and their impact on various industries in this beginner-friendly guide."
What is Generative AI? Definition and Real-World Applications
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Overview of Large Language Models (LLMs) – How They Work
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The Evolution of AI: From Rule-Based Systems to Deep Learning
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Key Terminologies: Neural Networks, Deep Learning, NLP, and More
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Popular Generative AI Models (GPT, BERT, DALL·E, etc.)
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Ethical Considerations and Responsible AI Use
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Understanding Machine Learning and Deep Learning Basics
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Training an AI Model: Data, Tokens, and Parameters
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How LLMs Generate Text: Predicting the Next Word
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Fine-tuning vs. Pre-training: Key Differences
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Challenges in AI: Bias, Misinformation, and Hallucinations
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Hands-on Exercise: Exploring a Live AI Model (ChatGPT, Bard, etc.)
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Text Generation: AI-Powered Writing Assistants
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AI in Content Creation: Blogging, Storytelling, and Marketing
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Chatbots and Virtual Assistants: How They Work
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AI in Programming: Code Generation and Debugging
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AI for Business Automation and Productivity
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Hands-on Activity: Generating Text with an AI Tool
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What is Prompt Engineering? Why is it Important?
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Types of Prompts: Direct vs. Indirect Prompts
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Best Practices for Writing Effective AI Prompts
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Optimizing AI Outputs: Controlling Style and Tone
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Advanced Techniques: Chain-of-Thought Prompting and Role-Playing
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Hands-on Exercise: Writing and Testing AI Prompts
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Trends in AI and LLM Development
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Ethics and Responsible AI Adoption
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AI in Different Industries: Healthcare, Finance, Education, etc.
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Career Paths in AI: Research, Development, and Applications
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How to Keep Learning: Resources, Communities, and Certifications
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Final Project: Build a Simple AI-Powered Content Generator
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