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Udemy – Generative AI The Future of AI-Powered Creativity Pro TM

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Free Download Udemy – Generative AI The Future of AI-Powered Creativity Pro TM

Published: 4/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 29m | Size: 2 GB
Understanding Generative AI How It Works, Applications, and Future Trends

What you'll learn

Students will learn what Generative AI is, its types, and how it's transforming industries.
Students will understand the complete workflow of AI systems from basic AI to advanced deep learning.
Students will explore how large language models generate human-like text for various real-world applications.
Students will identify the limitations of current GenAI models including bias, hallucination, and data constraints.
Students will discover how RAG enhances model accuracy by integrating external knowledge sources.
Students will master the architecture and real-world implementation of RAG with LLMs.
Students will learn how GenAI creates stunning images using tools like DALL·E and Stable Diffusion.
Students will understand how GenAI generates music and visual art through creative AI algorithms.
Students will explore how artists can collaborate with AI tools to enhance creativity and productivity.
Students will learn the role of transformer models and attention mechanisms in GenAI systems.
Students will explore techniques for handling long sequences and dependencies in generated content.
Students will learn how to adapt pre-trained models to specific tasks using various fine-tuning methods.
Students will gain skills to fine-tune GenAI models for industries like healthcare, finance, and legal.
Students will explore how GenAI models combine text, image, audio, and video for richer experiences.
Students will understand how to implement RAG in multimodal systems for intelligent information retrieval.
Students will examine the ethical implications of GenAI, including fairness, privacy, and misinformation.
Students will learn strategies for building responsible, transparent, and accountable AI models.
Students will build a fully functional AI chatbot using LangChain, OpenAI APIs, and retrieval techniques.

Requirements

This masterclass is designed for everyone—no prior experience is required, as the concepts are explained in a simple and accessible manner.

Description

Unlock the power of Generative AI, the most transformative technology of the 21st century. From text and image generation to multimodal learning and Retrieval-Augmented Generation (RAG), this course offers a step-by-step journey through the core components, real-world applications, and ethical considerations of Generative AI.Learn how Large Language Models (LLMs) like GPT, transformer architectures, and domain-specific fine-tuningare reshaping content creation, automation, and AI innovation across industries.Whether you're a developer, data scientist, AI enthusiast, or a digital creative, this course equips you with hands-on skills and strategic insights to build cutting-edge AI solutions — including chatbots using LangChain + OpenAI.1. Introduction to Generative AIWhat is Generative AI?Types: Text, Image, Audio, CodeUse cases across industries (marketing, healthcare, education)2. How Generative AI Works End-to-End | AI → ML → DL

Overview

of AI, Machine Learning, Deep LearningKey concepts in Neural NetworksTraining vs Inference vs Deployment3. Text Generation Using Generative AIUnderstanding LLMs (GPT, BERT, T5)Applications in text summarization, translation, storytelling4. Challenges and Limitations of Current Text Generation AIBias, hallucination, prompt limitationsComputational cost, token limits5. Retrieval-Augmented Generation (RAG) in AI – Enhancing Model KnowledgeWhat is RAG and why it mattersAugmenting LLMs with external knowledge6. How RAG Works with LLMs – Mastering Retrieval-Augmented GenerationArchitecture of RAGBuilding pipelines with vector databasesPractical examples (e.g., Question Answering Systems)7. Introduction to Image Generation Using Generative AITools: DALL·E, Midjourney, Stable DiffusionGenerating realistic, abstract, and branded visuals8. Music and Art Creation Using Generative AIAI for creative expression: from background scores to generative artTools and platforms used in the industry9. Enhancing Artists' Workflow with Iterative Gen AICo-creation with AIStyle transfers, iterative refinement, ideation acceleration10. Transformer Architecture in Generative AISelf-attention, encoder-decoder designEvolution of Transformers: BERT → GPT → PaLM11. Modeling Long-Range Dependencies in Text Generation AIChallenges with long documentsSolutions: attention masks, hierarchical models12. Fine-Tuning Pre-Trained Models for Generative AITransfer learning basicsLow-Rank Adaptation (LoRA), PEFT, and prompt tuning13. Techniques for Domain-Specific Fine-Tuning in Generative AIMedical, legal, finance — customizing GenAIDataset preparation, fine-tuning pipelines14. Multimodal Generative Models ExplainedCombining text, image, audio, and videoCLIP, Flamingo, and Gemini models15. Multimodal Retrieval-Augmented Generation (RAG)Bridging modalities using RAGVisual QA, document understanding with RAG + LLMs16. Ethical Considerations in Generative AIMisinformation, deepfakes, consentRegulatory frameworks: EU AI Act, Responsible AI17. Enforcing Accountability & Responsibility in AI Model DevelopmentAuditing AI systemsBias detection, mitigation strategies, transparency in model design18. Building a Chatbot with LangChain + OpenAIIntroduction to LangChainIntegrating OpenAI APIsEnd-to-end project: RAG-based Q&A Chatbot

Who this course is for

This course is ideal for anyone aspiring to learn future-ready skills and pursue careers such as Deep Learning Engineer, Data Scientist, Senior Data Scientist, AI Scientist, AI Engineer, AI Researcher, or AI Expert.
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