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Free Download Generative AI for Beginners - Explained Visually
Published 5/2026
Created by Jitendra Suryavanshi
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English + subtitle | Duration: 35 Lectures ( 1h 30m ) | Size: 1.84 GB
Master Generative AI: Explore LLMs, Diffusion Models, Prompt Engineering, and AI Ethics in this slide-based journey.
What you'll learn
Requirements
Description
This course contains the use of artificial intelligence.
Unlock the Future of Innovation: Master the Core Frameworks, Strategic Mechanics, and Real-World Logistics of Generative AI.
Welcome toGenerative AI for Beginners. We are living through a historic technological revolution. Artificial Intelligence is no longer a hidden tool reserved exclusively for data scientists and specialized programmers-it belongs to everyone. If you want to move past the surface-level hype and build a concrete, high-level mastery of the modern AI landscape, this conceptual, slide-based journey is engineered exactly for you.
Instructed by Jitendra, this course offers a complete 360-degree strategic roadmap across 6 structured sections and 35 deep-dive lectures. Whether you are an aspiring consultant, an enterprise leader, or a creative professional looking to supercharge your personal productivity, you will transition from a complete novice to a confident, strategically grounded authority in synthetic media.
What Makes This Course Unique?
Comprehensive Curriculum Breakdown
1. Foundations and Text Processing
We begin your journey by tracing the evolution of Artificial Intelligence, breaking down the massive historical shift from 1950s rigid Symbolic AI to modern predictive powerhouses. You will establish a definitive framework separating Predictive AI (the pattern finder) from Generative AI (the creative engine).
2. Under the Hood of Large Language Models (LLMs)
Demystify the actual mechanics driving tools like ChatGPT. Discover how theTransformer Architecture utilizes self-attention and positional encoding to process sentences simultaneously. Master the exact lifecycle of an LLM, detailing tokenization, subword slicing, vector embeddings, context window constraints, and the crucial balance between massivePre-training and specialized, cost-effectiveFine-tuning.
3. Generative Vision and Multi-Modal Logic
Explore how machines learn to see, draw, and compose. We deconstruct the math behindDiffusion Models, analyzing both the forward noise-injection process and the reverse denoising process driven by U-Net engines. Learn how text and pixels bridge seamlessly throughCLIP and text-to-image cross-attention layers, alongside an foundational look into Generative Adversarial Networks (GANs), temporal video consistency, and audio spectrogram maps.
4. Advanced Strategic Prompt Engineering
Move beyond basic questions and learn to architect your outputs with absolute precision. Master structural zero-shot and few-shot frameworks, trigger advanced cognitive capabilities usingChain-of-Thought (CoT) reasoning strings ("let's think step-by-step"), assign robust contextual professional personas, and implement iterative refinement loops to systematically eliminate mistakes.
5. Ethics, Safety, and Global Governance
Deploying technology responsibly is a non-negotiable professional mandate. We directly address the core challenges of algorithmic, representational, and sampling bias in training datasets. Navigate the murky legal waters of intellectual property ownership, copyright logic, and mimicry risks. Understand technical safety guardrails (pre- and post-processing filters), model alignment via Reinforcement Learning from Human Feedback (RLHF), deepfake tracking, global compliance risks (like the EU AI Act), and the heavy environmental carbon and water footprints of massive data centers.
6. Enterprise Workflows and Autonomous Agents
Conclude your training by looking at the horizon of business automation. Design highly secure multi-agent ecosystems where specialized AI workers collaborate autonomously. Learn to ground corporate AI instances with internal company records usingRetrieval-Augmented Generation (RAG) pipelines, explore how synthetic data accelerates scientific discoveries like drug matching, and evaluate the technical and economic roadmaps leading toward Artificial General Intelligence (AGI).
What You Will Master
Who Is This Course For?
No prior programming or computer science experience is required. Bring an open mind, an analytical perspective, and a readiness to master the next great technological frontier.
Enroll today and secure your roadmap for the future of work.
Who this course is for
Homepage
Code:
https://www.udemy.com/course/generative-ai-for-beginners-explained-visually
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https://rg.to/file/66a2727a46fd3030775a55679b545243/fxjif.Generative.AI.for.Beginners..Explained.Visually.part1.rar.html
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