Generative AI (basic to advanced)
Published 8/2025
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch Language: English | Duration: 46h 36m | Size: 21.2 GB

Learn how Generative AI models are revolutionizing content, code, innovation using prompt engineering & real-world tech.

What you'll learn
Understand what Generative AI is and how it works
Learn different types of generative models (GANs, VAEs, Transformers, etc.)
Explore how GenAI can generate text, images, audio, and video
Build and train basic generative models from scratch
Use pre-trained models like GPT and DALL·E for real-world tasks
Practice prompt engineering to get better results from AI models
Learn how to fine-tune models for specific use cases
Build GenAI applications like chatbots, content creators, and art generators
Understand the risks, ethics, and responsible use of GenAI

Requirements
Enthusiasm and determination to make your mark on the world!

Description
A warm welcome to the Generative AI (basic to advanced) course by Uplatz.Generative AI (Generative Artificial Intelligence) refers to a type of artificial intelligence that is capable of creating new content-such as text, images, audio, code, and more-rather than simply analyzing existing data. It mimics human creativity by learning from large datasets and generating outputs that resemble original, human-made content.What It DoesTraditional AI systems are good at recognizing patterns or making predictions based on existing data. Generative AI goes a step further by actually producing new data that didn't exist before. For example:Writing articles or storiesCreating images or artworkComposing musicWriting codeDesigning products or layoutsHow It WorksGenerative AI typically relies on advanced machine learning techniques, especially deep learning models such as:Transformers - used in models like GPT (text) or T5Diffusion models - used in image generation (like DALL·E or Stable Diffusion)GANs (Generative Adversarial Networks) - used for creating realistic mediaHere's a simplified breakdown of the process:TrainingThe model is trained on massive datasets (e.g., books, websites, images, code).It learns statistical patterns, styles, and relationships in the data.Learning ProbabilitiesInstead of memorizing, the model learns the probability of what should come next in a sequence (next word, next pixel, etc.).Generation (Inference)When you give it a prompt, it generates new content based on what it has learned.For instance, if you type a sentence, a text model will complete it or write a full article.If you input a concept, an image model can generate an image matching that description.Fine-TuningThe base model can be refined using reinforcement learning or task-specific data to make it more accurate, aligned, or safer.Common Applications of Generative AIText GenerationWriting articles, blogs, and essaysDrafting emails and messagesSummarizing long documentsTranslating languagesAnswering questions or tutoringImage GenerationCreating digital art and illustrationsGenerating product mockups and logosDesigning ads, posters, and visual contentStyle transfer and photo editingCode GenerationAuto-completing codeGenerating boilerplate scriptsFixing bugs and refactoring codeExplaining code snippetsAudio and MusicComposing original musicGenerating voiceovers or speechProducing sound effectsVoice cloning and enhancementVideo GenerationCreating short films and animationsGenerating explainer videosVideo summarizationScene-to-video synthesis3D Modeling and DesignGenerating 3D objects and environmentsDesigning virtual products or architectureGame asset creationGamingProcedural content and level generationNPC (non-player character) behavior scriptingDialogue generationFashion and Product DesignDesigning apparel and accessoriesCreating virtual try-onsGenerating custom product variantsEducationPersonalized tutoring and explanationsQuiz and flashcard generationAdaptive learning contentMarketing and AdvertisingWriting ad copy and taglinesCreating personalized campaignsDesigning social media postsLegal and ComplianceDrafting legal documentsReviewing and summarizing policiesIdentifying contract risksHealthcare and BiotechGenerating radiology and diagnostic reportsSimulating molecular structuresSummarizing patient recordsCustomer SupportChatbots for FAQs and ticket handlingEmail and chat summarizationResponse recommendationFinanceAutomating financial reportsAnalyzing and summarizing earnings callsDetecting unusual financial patternsBenefitsRapid content generationPersonalized or on-demand outputsAutomation of creative and technical tasksSupport for brainstorming and ideationTime and cost efficiency for businessesChallenges and RisksMay generate incorrect or misleading contentCan reflect biases from the training dataRisk of misuse for fake content or misinformationComputational and environmental costsRequires careful monitoring and human validation

Who this course is for
AI/ML Engineers - looking to build or fine-tune generative models
Software Developers - wanting to integrate GenAI into applications
Data Scientists - interested in advanced modeling and content generation
Tech Enthusiasts & Hobbyists - curious about AI tools like ChatGPT, Midjourney, DALL·E
Product Managers - aiming to understand capabilities and limitations of GenAI
Startup Founders & Innovators - exploring GenAI use cases and MVP development
Content Creators & Designers - who want to leverage AI for creative work
Researchers & Academics - studying generative models and their applications
Business Professionals - interested in using AI to improve workflows and automation
Students & Career Changers - who want to enter the AI field with hands-on GenAI skills

https://www.udemy.com/course/generative … -advanced/

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