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[center]![[Obrazek: c0c1d7572247ed16500baa62a9549d16.jpg]](https://i126.fastpic.org/big/2026/0112/16/c0c1d7572247ed16500baa62a9549d16.jpg)
Foundation Of Ai, Ml, Nn And Genai + Capstone Project
Published 1/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 6h 19m | Size: 7.84 GB [/center]
Learn AI, ML, Neural Networks & Generative AI from scratch with real-world concepts and a capstone approach
What you'll learn
Understand how AI systems differ from traditional software
Identify different types of AI and real-world AI workloads
Clearly explain Machine Learning concepts, algorithms, and models
Understand how ML models are trained, evaluated, and used
Build and use a basic ML model using Python
Understand Artificial Neural Networks and Deep Learning
Learn key neural network architectures
Understand Generative AI concepts and use cases
Learn how Autoencoders, GANs, Diffusion models, and Transformers work
Understand LLMs, SLMs, fine-tuning, and AI agents
Requirements
No prior AI, ML, or GenAI experience required
Basic computer knowledge is enough
Basic Python knowledge is helpful but not mandatory
A willingness to learn concepts step-by-step
Curiosity about how intelligent systems are built
Description
Artificial Intelligence is no longer optional-it is becoming a core skill across industries. However, most learners struggle because AI courses are either too mathematical, too abstract, or jump straight into tools without building strong fundamentals.This course solves that problem.Foundation of AI, ML, NN & GenAI + Capstone Project is a carefully structured beginner-to-intermediate course that helps you understand how AI systems actually work, from classical Machine Learning to modern Generative AI and Large Language Models.You'll start by learning what AI truly is, how AI systems differ from traditional software, and where AI is used in real-world scenarios. From there, you'll build a solid foundation in Machine Learning-understanding algorithms, models, training workflows, evaluation methods, and career paths.Next, you'll move into Artificial Neural Networks and Deep Learning, creating the bridge to Generative AI. You'll then explore GenAI concepts, understand different GenAI models, and learn how technologies like Autoencoders, GANs, Diffusion Models, and Transformers power today's AI applications.The course also covers LLMs, fine-tuning, AI agents, major AI labs, and ethical AI principles, giving you industry-relevant awareness that most beginner courses miss.This course focuses on clarity, structure, and real-world understanding, not just buzzwords. Whether you want to enter AI, upgrade your skills, or confidently talk about GenAI in professional settings-this course gives you the foundation you need.
Who this course is for
Beginners with no prior AI/ML background
Students and fresh graduates exploring AI career paths
Software developers who want to transition into AI/ML or GenAI
Working professionals curious about how modern AI systems actually work
Non-technical professionals who want to understand AI concepts, GenAI, and LLMs clearly
Anyone planning to move into Data Science, ML Engineering, or GenAI roles
HomepageScreenshot
Foundation Of Ai, Ml, Nn And Genai + Capstone Project
Published 1/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 6h 19m | Size: 7.84 GB [/center]
Learn AI, ML, Neural Networks & Generative AI from scratch with real-world concepts and a capstone approach
What you'll learn
Understand how AI systems differ from traditional software
Identify different types of AI and real-world AI workloads
Clearly explain Machine Learning concepts, algorithms, and models
Understand how ML models are trained, evaluated, and used
Build and use a basic ML model using Python
Understand Artificial Neural Networks and Deep Learning
Learn key neural network architectures
Understand Generative AI concepts and use cases
Learn how Autoencoders, GANs, Diffusion models, and Transformers work
Understand LLMs, SLMs, fine-tuning, and AI agents
Requirements
No prior AI, ML, or GenAI experience required
Basic computer knowledge is enough
Basic Python knowledge is helpful but not mandatory
A willingness to learn concepts step-by-step
Curiosity about how intelligent systems are built
Description
Artificial Intelligence is no longer optional-it is becoming a core skill across industries. However, most learners struggle because AI courses are either too mathematical, too abstract, or jump straight into tools without building strong fundamentals.This course solves that problem.Foundation of AI, ML, NN & GenAI + Capstone Project is a carefully structured beginner-to-intermediate course that helps you understand how AI systems actually work, from classical Machine Learning to modern Generative AI and Large Language Models.You'll start by learning what AI truly is, how AI systems differ from traditional software, and where AI is used in real-world scenarios. From there, you'll build a solid foundation in Machine Learning-understanding algorithms, models, training workflows, evaluation methods, and career paths.Next, you'll move into Artificial Neural Networks and Deep Learning, creating the bridge to Generative AI. You'll then explore GenAI concepts, understand different GenAI models, and learn how technologies like Autoencoders, GANs, Diffusion Models, and Transformers power today's AI applications.The course also covers LLMs, fine-tuning, AI agents, major AI labs, and ethical AI principles, giving you industry-relevant awareness that most beginner courses miss.This course focuses on clarity, structure, and real-world understanding, not just buzzwords. Whether you want to enter AI, upgrade your skills, or confidently talk about GenAI in professional settings-this course gives you the foundation you need.
Who this course is for
Beginners with no prior AI/ML background
Students and fresh graduates exploring AI career paths
Software developers who want to transition into AI/ML or GenAI
Working professionals curious about how modern AI systems actually work
Non-technical professionals who want to understand AI concepts, GenAI, and LLMs clearly
Anyone planning to move into Data Science, ML Engineering, or GenAI roles
HomepageScreenshot
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