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Generative AI & LLMs From Zero to Practical AI Mastery
Published 9/2026
Created by Ashish Chugh
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 13 Lectures ( 3h 10m ) | Size: 1.2 GB
Understand How Large Language Models Work, Master Prompting, Explore Real-World Use Cases, and Apply AI Responsibly
What you'll learn
Explain how Generative AI and LLMs work, from language modeling and tokens to transformers, training, and inference. Create effective prompts using context, instructions, examples, constraints, task decomposition, and output controls. Apply LLMs to generation, summarization, Q&A, coding, translation, classification, and real-world business and L&D workflows. Evaluate LLM limitations, including hallucinations, bias, privacy, security, and misuse, and apply responsible AI practices.Requirements
No prior experience with Generative AI, LLMs, programming, or machine learning is required. The course is designed for beginners. Learners only need a computer with internet access and a willingness to learn.Description
This course contains the use of artificial intelligence.
Generative AI & LLMs: From Zero to Practical AI Mastery
Generative AI and Large Language Models are transforming how people learn, work, create, analyze information, and solve problems. But using tools like ChatGPT effectively requires more than knowing how to type a prompt.
This course takes you fromthe fundamentals of language models to practical, responsible use of Generative AI, without requiring you to become a machine-learning engineer.
You will learn what actually happens inside an LLM, why transformers changed language AI, how models learn, how prompting works, where LLMs are genuinely useful, and where their limitations create risk.
What will you learn?
You will begin by understandingwhy LLMs are such a significant development in AI and how we arrived at today's technology-from rule-based systems to machine learning, deep learning, transformers, and large language models.
You will then learn what alanguage model actually is. Instead of treating an LLM as a mysterious black box, you will understand the fundamental idea of predicting likely continuations from context and how this simple concept scales into surprisingly powerful capabilities.
Next, you will explore thecore building blocks of LLMs, including
Tokens and tokenization Embeddings and numerical representations Context and context windows Parameters and model size Pre-training Fine-tuning and instruction-tuning InferenceFrom there, the course goes inside theTransformer architecture. You will learn why transformers became so important, how self-attention works conceptually, what queries, keys, and values represent, why multi-head attention is useful, and how layers, residual connections, and other components work together.
You will also discoverhow LLMs learn. We will examine training data, the next-token prediction objective, model optimization, scaling, compute, fine-tuning, and the progression from base models to instruction-following and conversational models.
Learn how to prompt effectively
Understanding the model makes prompting much more intuitive.
You will learn how to construct effective prompts by combiningtask, context, audience, format, constraints, and desired outcomes. The course covers zero-shot and few-shot prompting, structured prompts, output control, task decomposition, iterative prompting, and techniques for improving weak prompts.
Rather than memorizing a collection of prompt tricks, you will learnwhy certain prompting approaches work and when to use them.
Discover what LLMs can actually do
The course then moves from theory into practical capabilities and business applications.
You will explore how LLMs can be used for
Content generation Summarization Information extraction Question answering Chatbots Code generation and debugging Translation Sentiment analysis Classification Domain-specific workflowsYou will also learn an important distinction:a model capability is not automatically a reliable business solution. Effective AI workflows depend on the quality of the context, the task design, supporting tools, evaluation, verification, and appropriate human oversight.
Apply Generative AI to Education & L&D
A dedicated module focuses onEducation and Learning & Development, showing how LLMs can support
Personalized learning Learning assistants Course and content authoring Assessment creation Feedback Skill development paths Content adaptation Conversational practice and role play Learning workflows Knowledge support for learners and employeesThis makes the course particularly relevant to educators, trainers, instructional designers, L&D professionals, and organizations looking to incorporate Generative AI into learning workflows.
Understand the risks-not just the possibilities
Powerful AI requires responsible use.
You will examine the major limitations and risks associated with LLMs, including
Hallucinations and factual errors Bias and fairness Safety and misuse Privacy concerns Security risks Prompt injection Context limitations Reliability and evaluation Human oversight Responsible AI practicesYou will learn whyfluent output should never be confused with guaranteed truth, and how to think about risk when deciding whether an LLM is appropriate for a particular task.
Build a practical learning path
The course concludes by bringing everything together and helping you determinewhere to go next.
Whether you want to become more AI-literate, use AI more effectively in your current role, build AI-enabled workflows, or specialize in AI for education and L&D, you will have a structured path for continuing your learning.
By the end of the course
You will be able to explainwhat an LLM is, how it represents and processes language, how transformers enable modern language models, how these models are trained, how prompting influences their behavior, what they can be used for, and what can go wrong.
Most importantly, you will develop a practical mental model for working with Generative AI intelligently:understand the technology, provide the right context, use the right approach, evaluate the output, and apply human judgment where it matters.
This course is not about simply learning to use an AI chatbot.
It is aboutunderstanding the technology well enough to use it effectively, critically, and responsibly.
Who this course is for
This course is designed for anyone who wants to understand and use Generative AI and Large Language Models more effectively. It is suitable for beginners, business professionals, managers, educators, trainers, instructional designers, L&D professionals, knowledge workers, and aspiring AI practitioners. It is especially valuable for learners who want to move beyond simply using ChatGPT or other AI tools and understand how LLMs work, how to prompt them effectively, where they can be applied, and how to use them responsibly.Homepage
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