Introduction
Introduction to AI
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1. Introduction to AI
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The importance of AI in boosting productivity
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Brief history and evolution of AI
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2. Exploring the Foundations of AI
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Definition and scope of AI
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Types of AI
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Basics of machine learning, deep learning, and neural networks
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3. Current State of Affairs in AI
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Recent advancements and breakthroughs in AI technology
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Real-world applications of AI in different industries
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Key players and leading AI research institutions
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4. AI Text Generation
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Introduction to natural language processing (NLP)
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Text generation models: GPT, BERT
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Applications of content creation, summarization, and translation
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5. AI Image Generation
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Overview of computer vision and image processing
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Applications in design, art, and visual content creation
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6. A World of Copilots
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Enhancing productivity with AI-powered assistants and tools
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Integrating AI into tools you already use
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Microsoft 365 Copilot
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GitHub Copilot
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7. Prompt Engineering
Learning objectives
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Understanding the importance of prompts in AI models
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Crafting effective prompts to achieve desired outputs
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Prompt engineering for specific tasks
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8. Tips and Tricks Using AI
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Productivity hacks leveraging AI tools and techniques
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Automating repetitive tasks with AI
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Integrating AI into existing workflows
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9. AI Risks and Opportunities
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Potential risks and ethical considerations of AI
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Opportunities for innovation and growth
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Strategies for mitigating risks
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10. Responsible AI
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Principles of responsible AI
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Bias detection and mitigation
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Ensuring AI applications are transparent, fair, and accountable
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11. Unlocking Productivity across Roles and Industries
Learning objectives
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Finance professional
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Marketing specialist
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Customer service rep
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Sales representative
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Business analyst
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Project manager
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Product manager
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Team lead
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12. The Future of AI
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Recap what you've learned
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Reflecting on the impact of AI
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Further learning and staying updated on AI
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