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Generative Ai Essentials: A Comprehensive Hands-On Journey
Published 12/2025
Created by Dr. Ray Islam
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 75 Lectures ( 3h 50m ) | Size: 6.2 GB [/center]
A hands-on introduction to modern Generative AI, its applications, and responsible use.
What you'll learn
Explain foundational concepts of Artificial Intelligence and Generative AI
Trace the historical evolution of AI to modern Generative AI
Differentiate major types of Generative AI systems
Describe the core mechanisms behind modern GenAI models
Analyze and compare common GenAI algorithms and architectures
Design and explain a Retrieval-Augmented Generation (RAG) pipeline
Identify and apply modern GenAI tools, frameworks, and platforms
Compare deep learning frameworks and GenAI platforms
Distinguish between fine-tuning strategies
Validate GenAI systems using appropriate metrics and testing approaches
Build and document a small but realistic GenAI system
Produce a professional portfolio artifact
Critically reflect on misuse scenarios and mitigations
Requirements
Basic technical familiarity is helpful but not required.
Description
"This course contains the use of artificial intelligence"Generative AI Essentials: A Comprehensive Hands-On Journey - provides a practical and accessible introduction to today's Generative AI technologies, helping learners understand how these systems operate, how they are applied in real-world scenarios, and how to use them responsibly.The course explains the fundamental ideas behind large language models, diffusion-based generation, multimodal AI, and retrieval-augmented generation (RAG) through clear explanations and applied examples. Learners explore the progression of AI from early foundations to the modern GenAI landscape, along with the tools, platforms, and workflows used to build, test, and deploy these systems.A strong focus is placed on understanding limitations, risks, ethical considerations, and cybersecurity challenges. You will learn where Generative AI can produce unreliable results, how bias and hallucinations arise, and how misuse and adversarial behavior can impact real-world systems.The course culminates in a portfolio-ready capstone project, where learners design and evaluate a small yet realistic Generative AI solution and reflect on responsible and secure deployment practices.This course is well-suited for learners seeking a structured, hands-on, and responsible introduction to Generative AI.Throughout the course, learners are encouraged to think critically about design trade-offs, validation strategies, governance concerns, and real-world decision-making, drawing practical insights from industry, government, and academic contexts to strengthen technical understanding and professional readiness for modern AI-driven systems globally.
Who this course is for
This course is designed for students and professionals who want a practical, hands-on introduction to Generative AI.
• Students and early-career professionals in computer science, data science, cybersecurity, or related fields
• Software engineers, data scientists, and ML practitioners seeking to understand how modern GenAI systems work
• Cybersecurity, risk, and compliance professionals interested in GenAI risks and responsible use
• Product managers, consultants, and technical leaders evaluating GenAI adoption
• Educators and lifelong learners building foundational GenAI knowledge
Generative Ai Essentials: A Comprehensive Hands-On Journey
Published 12/2025
Created by Dr. Ray Islam
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All | Genre: eLearning | Language: English | Duration: 75 Lectures ( 3h 50m ) | Size: 6.2 GB [/center]
A hands-on introduction to modern Generative AI, its applications, and responsible use.
What you'll learn
Explain foundational concepts of Artificial Intelligence and Generative AI
Trace the historical evolution of AI to modern Generative AI
Differentiate major types of Generative AI systems
Describe the core mechanisms behind modern GenAI models
Analyze and compare common GenAI algorithms and architectures
Design and explain a Retrieval-Augmented Generation (RAG) pipeline
Identify and apply modern GenAI tools, frameworks, and platforms
Compare deep learning frameworks and GenAI platforms
Distinguish between fine-tuning strategies
Validate GenAI systems using appropriate metrics and testing approaches
Build and document a small but realistic GenAI system
Produce a professional portfolio artifact
Critically reflect on misuse scenarios and mitigations
Requirements
Basic technical familiarity is helpful but not required.
Description
"This course contains the use of artificial intelligence"Generative AI Essentials: A Comprehensive Hands-On Journey - provides a practical and accessible introduction to today's Generative AI technologies, helping learners understand how these systems operate, how they are applied in real-world scenarios, and how to use them responsibly.The course explains the fundamental ideas behind large language models, diffusion-based generation, multimodal AI, and retrieval-augmented generation (RAG) through clear explanations and applied examples. Learners explore the progression of AI from early foundations to the modern GenAI landscape, along with the tools, platforms, and workflows used to build, test, and deploy these systems.A strong focus is placed on understanding limitations, risks, ethical considerations, and cybersecurity challenges. You will learn where Generative AI can produce unreliable results, how bias and hallucinations arise, and how misuse and adversarial behavior can impact real-world systems.The course culminates in a portfolio-ready capstone project, where learners design and evaluate a small yet realistic Generative AI solution and reflect on responsible and secure deployment practices.This course is well-suited for learners seeking a structured, hands-on, and responsible introduction to Generative AI.Throughout the course, learners are encouraged to think critically about design trade-offs, validation strategies, governance concerns, and real-world decision-making, drawing practical insights from industry, government, and academic contexts to strengthen technical understanding and professional readiness for modern AI-driven systems globally.
Who this course is for
This course is designed for students and professionals who want a practical, hands-on introduction to Generative AI.
• Students and early-career professionals in computer science, data science, cybersecurity, or related fields
• Software engineers, data scientists, and ML practitioners seeking to understand how modern GenAI systems work
• Cybersecurity, risk, and compliance professionals interested in GenAI risks and responsible use
• Product managers, consultants, and technical leaders evaluating GenAI adoption
• Educators and lifelong learners building foundational GenAI knowledge
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