Generative AI
A free, beginner-friendly path through Geeks Analytics' Generative AI course, covering how LLMs work, prompt authoring, AI agents, and industry use cases.
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Now playing: Generative AI Limitations | AI Hallucinations, Bias, Privacy & Copyright Explained
This path follows the Geeks Analytics Generative AI Course in order, starting with an introduction and the difference between AI, machine learning, deep learning, and generative AI. It then moves into how large language models actually work, including tokenization, embeddings, and next-word prediction, before covering prompt authoring and the tools people use day to day. Later lessons look at agentic AI and a practical agent demo, then walk through generative AI use cases in banking, media, manufacturing, and healthcare. The path closes with a look at limitations such as hallucinations and bias, plus a career story from a non-technical background. It is aimed at beginners, students, and professionals who want a structured overview rather than deep hands-on coding.
Beginners who want a structured free introduction before deeper practice.
Lesson 1: Generative AI Course Introduction | What Is Generative AI | How It Works, Uses, Jobs & Future
This is the course introduction. It outlines the learning roadmap and touches on what generative AI is, how it works, where it is used, job opportunities, limitations, and what the future may hold.
Open on YouTubeLesson 2: Generative AI Explained | Evolution, Training Data, Normal AI vs Gen AI & Real-World Uses
A short session on how AI evolved from traditional systems to generative AI. It also covers what happens during training and contrasts normal AI with generative AI using real-world examples.
Open on YouTubeLesson 3: AI vs Generative AI Explained | Machine Learning, Deep Learning & Key Differences
This lesson separates the terms AI, machine learning, deep learning, and generative AI. It explains how each layer relates to the others and how they differ in the way they analyze data and produce output.
Open on YouTubeLesson 4: Machine Learning Explained | How Regression, Classification & AI Training Actually Work
An introduction to machine learning using regression and classification examples. It also covers data labeling and what AI training involves in practice.
Open on YouTubeLesson 5: Generative AI Explained | How LLMs Work, Tokenization, Embeddings & Next-Word Prediction
A longer lesson on how large language models actually generate text. It breaks down tokenization, embeddings, next-word prediction, and how models learn from large datasets.
Open on YouTubeLesson 6: Generative AI Tools Explained | ChatGPT, Gemini, Midjourney, Runway, Canva & More
A tour of major generative AI tools including ChatGPT, Gemini, Midjourney, Runway, and Canva. It looks at how these tools are used for text, research, images, video, writing, design, and workflow automation.
Open on YouTubeLesson 7: Prompt Authoring Explained | How to Write Better AI Prompts, Use AI Effectively & Avoid Mistakes
This lesson covers prompt authoring: how to communicate with AI to get more relevant and accurate results. It also explains common prompting mistakes and how to avoid them.
Open on YouTubeLesson 8: How to Create a 6-Month Business Plan with ChatGPT | Prompt Engineering Tutorial
A practical prompt engineering walkthrough where ChatGPT is used to build a 6-month business plan. The example uses a cloud-related business scenario to show how a real prompt is structured.
Open on YouTubeLesson 9: Generative AI Use Cases | What Can AI Really Do? Text, Image, Video & Audio
An overview of generative AI use cases across text, images, video, audio, and multimodal AI. It shows tasks such as text classification and transcription, and explains what multimodal systems can do.
Open on YouTubeLesson 10: What is Agentic AI? AI Agents Explained | Generative AI, ML & Automation
This lesson explains agentic AI and how AI agents combine generative AI, machine learning, and workflow automation. It walks through a practical agent example to show how these systems handle complex tasks.
Open on YouTubeLesson 11: Agentic AI Demo | How AI Agents Think, Act & Solve Real-World Problems
A demo showing how an AI agent handles a customer request end to end. The agent analyzes plants through video, recommends products, updates a shopping cart, and offers additional services.
Open on YouTubeLesson 12: Generative AI in Banking & Finance Explained | Fraud Detection, Personalization & Compliance
This lesson looks at generative AI in banking and finance. It covers proactive fraud detection, personalization, and compliance use cases.
Open on YouTubeLesson 13: Generative AI in Media & Entertainment | Content Creation, Digital Humans & Recommendations
A look at generative AI in media and entertainment, including AI-powered content creation, digital humans, and personalized movie and TV recommendations.
Open on YouTubeLesson 14: Generative AI in Manufacturing | 3 Use Cases Transforming Product Design & Production
This lesson covers three generative AI use cases in manufacturing. It focuses on product design, prototyping, production optimization, and defect detection.
Open on YouTubeLesson 15: Generative AI in Healthcare Explained | Drug Discovery, Synthetic Data & Personalized Medicine
An overview of generative AI in healthcare and life sciences. It covers drug discovery, synthetic data generation, and personalized medicine.
Open on YouTubeLesson 16: Generative AI Limitations | AI Hallucinations, Bias, Privacy & Copyright Explained
This lesson covers the main limitations of generative AI: hallucinations, biased outputs, outdated information, data privacy risks, copyright issues, deepfakes, and computational costs.
Open on YouTubeLesson 17: How a Non-Technical Person Became a Data Scientist | 13+ Years Data Analytics Career Journey
A career story about a non-technical professional who moved into data science and analytics over 13+ years. It covers data analytics, machine learning, and data visualization work.
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