Gen AI Readiness, Implementation and Transformation

KNOWING HOW GEN AI TRANSFORMS ORGANIZATIONSGen AI is disrupting many (if not all!) organizations. We need to know what it is, and how to work with it.But there is a lot to know. What can these models do? How do we change work and workflows to deal with them? How do we prompt? Deal with hallucinations? And a lot more.In this course, we will cover two key areas related to Gen AI:What is, what it can and can't do, realistic expectations for it, and more - the basic concepts of Gen AI;How to work with Gen AI in practice. Prompting, spotting errors, dealing with weird and uncanny effects, working with context, structuring reasoning and tasks, and more;LET ME TELL YOU... EVERYTHING.Some people - including me - love to know what they're getting in a package.And by this, I mean, EVERYTHING that is in the package.So, here is a list of everything that this course covers:You'll learn about where we are right now, in the world, with Gen AI. What it can do, the effects it has on people, how it's being adopted, and how it's revolutionizing various industries;You'll learn about what Gen AI can do. The three tiers of tasks (Tier 1: Very useful; Tier 2: somewhat useful; Tier 3: dangerous!), what are the characteristics of tasks that Gen AI is good/bad at, and also what is hype versus what is true capability;You'll learn about how Gen AI changes work, including big shifts such as most employees going from focusing on the work itself to focusing on the design of workflows (to break down tasks so some can be automated), and going from "executor" to automator (instead of actually "doing" work, focusing on the automation of tasks in the same style/format as you previously did work);You'll learn about various technical aspects of Gen AI models. What do characteristics such as the number of parameters or the size of the context window mean, what are models for text/image/audio/video, as well as models such as multimodals or MoEs (mixtures of experts), as well as what are processes such as tokenization and vectorization for creating embeddings, why hallucinations occur, as well as an overview of what is training, fine-tuning, the creation of LoRAs, and the usage of RAG;You'll learn about the most common pain points when adopting Gen AI in an organization, including elements such as unrealistic expectations, premature optimizations, having insufficient/unfit tools, having problems with output quality/trustability, misalignment between Gen AI and workflows, disorganization issues, various anxieties and stigmas by employees, or stochastic degration (small widespread mistakes due to hallucinations, bad Gen AI adoption, or others);You'll learn about the right frame for using Gen AI - as a powerful assistant that needs validation - versus other unrealistic frames, such as seeing it as an oracle, a replacement, or others;You'll learn about the basic components of prompt, prompt engineering, designing quality prompts, and optimizing them for specific results;You'll learn about the major modes of working with Gen AI - through an interface, a step in an application or an agent - and the major types of tasks it can do (generating and adapting content, distilling and structuring content, analyzing and supporting decisions, simulating and role-playing, and automating and executing);You'll learn about structuring reasoning, breaking big tasks down into sub-tasks which can be executed with humans or Gen AI, as well as where to validate outputs and with what frequency. You'll also learn about common structures such as chains, loops and validation loops;You'll learn about the major types of errors in outputs - hallucinations, insufficient outputs, unstable outputs and biases - as well as what causes each and how to avoid them;You'll learn about the uncanny and weird effects of using Gen AI - "editor syndrome", feeling "centrifuged", the "Gendela Effect", and many others, how they affect you psychologically, and how to stay resilient in the face of them;You'll learn about some key principles to actually adopt Gen AI in work, including being open-minded, experimenting, and navigating the psychological uncanniness while tolerating the inherent ambiguity and fuzziness of both the technology and workflows;You'll learn about "problems at the joints", where individual outputs are good but they don't mesh together, including fragmentation of facts, tone and style, context, and others, cross-section inconsistencies and duplicates, and/or gradual erosion of quality; MY INVITATION TO YOURemember that you always have a 30-day money-back guarantee, so there is no risk for you.Also, I suggest you make use of the free preview videos to make sure the course really is a fit. I don't want you to waste your money.If you think this course is a fit, and can take your knowledge of dealing with change to the next level... it would be a pleasure to have you as a student.See on the other side!