
Contextualize the current state of GenAI by understanding foundation models, their uneven impact on work, and the cognitive, emotional, and organizational shifts they introduce.
Classify GenAI use cases by usefulness and risk, distinguishing tasks where it reliably augments work from those where it produces shallow reasoning, instability, or dangerous errors.
Evaluate how GenAI changes professional work by shifting effort from execution to automation, requiring structured reasoning, orchestration, and new validation responsibilities.
Understand the technical foundations of GenAI systems—including models, context, embeddings, and hallucinations—to better interpret outputs, limitations, and failure modes.
Identify common organizational and human pain points in GenAI adoption, including unrealistic expectations, workflow misalignment, trust erosion, and cognitive degradation.
Discover Microsoft Copilot, an AI assistant integrated across Microsoft 365 apps that helps you write, analyze, and create content more efficiently.
Learn how to access and use the core features of Microsoft Copilot to boost your analytics workflow.
Explore Gemini by Google, an advanced AI model designed for reasoning, coding, and multimodal capabilities.
This lesson provides a quick walkthrough of the Gemini interface, highlighting key features and areas you’ll use most often in project management tasks.
Learn the fundamentals of Claude AI, including its capabilities and real-world applications.
Explore how Claude Pro compares to other AI models in terms of features, strengths, and use cases.
A step-by-step guide to getting started with Claude Pro and efficiently using its interface.
Discover how to create complete project plans in Word with Copilot’s assistance.
Discover how to use Copilot to model project outcomes under different scenarios (e.g., delays, resource changes) and generate actionable insights.
Discover how to quickly turn project goals into actionable step-by-step checklists and task breakdowns using Copilot.
Learn how to prompt Copilot to generate concise and structured project briefs that capture objectives, scope, deliverables, and key success criteria.
Discover how Copilot summarizes meetings and generates follow-up action items directly in Outlook.
Explore how Copilot can draft clear, professional progress updates for your team or stakeholders in seconds, saving you time on repetitive reporting.
Discover how Copilot helps you track overdue tasks and send effective follow-ups to keep projects on track.
See how AI can streamline collaboration and improve communication across different teams.
Discover how Copilot helps you monitor project expenses and keep budgets on track in Excel.
Use Copilot to instantly create structured, professional project status reports in Word.
Discover how to use Copilot to automate advanced data preparation tasks like pivoting tables, parsing text, and generating calculated fields.
Discover how Copilot enhances data storytelling through automatically generated, insightful, and interactive visuals.
This lesson shows how Gemini helps articulate clear project goals and measurable success criteria based on business context.
This lesson demonstrates how to use Gemini to identify key stakeholders, assess their influence and interests, and plan effective engagement strategies.
This lesson explains how to use Gemini in Google Docs to draft, refine, and manage project documentation.
This lesson demonstrates how Gemini can extract tasks from a project brief and organize them into a clear task list.
This lesson shows how Gemini can gather and summarize real-time information to support project planning decisions.
This lesson shows how Gemini helps draft and organize essential project documents.
Learn how to generate AI-powered images using Claude’s creative tools.
Understand how Claude can assist in writing and refining code, including HTML markup.
Explore how Claude AI can create compelling ad copy, email campaigns, and social media posts.
Learn how to streamline social media management by using Claude Pro for content engagement.
Unlock new creative possibilities by using Claude AI to generate innovative and engaging content.
Learn how to use Claude AI to identify high-impact keywords and optimize content for better search rankings.
Discover how to craft compelling, high-converting PPC ad copy with the help of Claude AI.
Explore how Claude Pro can streamline and improve the performance of your paid advertising campaigns.
Learn how to leverage Claude AI for data-driven insights that maximize ad effectiveness and return on investment.
Reframe managerial decision-making to account for Gen AI’s speed, instability, and evolving human-machine dynamics.
Structure workflows that combine human judgment and Gen AI execution to control risk while increasing efficiency.
Redefine hiring criteria and performance evaluation to reflect AI augmentation, validation skills, and oversight responsibilities.
Evaluate whether to hire, augment, or automate tasks by calculating risk-adjusted ROI and operationalizing the right mix of Gen AI and human talent.
Learn how to write effective prompts that guide Copilot in cleaning, formatting, and standardizing your datasets for accurate analysis.
Explore how Copilot can assist you in performing hypothesis tests and interpreting results to support data-driven decisions.
Learn how to prompt Copilot to quickly summarize your data using key descriptive statistics like mean, median, mode, and standard deviation.
See how Copilot can help you track performance indicators, spot bottlenecks, and provide clear summaries of project health.
Diagnose current Gen AI maturity across strategic, technical, data, talent, and governance dimensions to identify capability gaps.
Align Gen AI initiatives with clear business objectives, defined value hypotheses, and explicit risk boundaries.
Evaluate whether infrastructure, security, integration layers, and scalability can reliably support Gen AI workloads.
Assess data quality, accessibility, governance, and structure to ensure models are trained and deployed on reliable foundations.
Develop the skills, incentives, and cultural mindset required to experiment with, adopt, and responsibly scale Gen AI.
Strengthen organizational error-correction speed to continuously monitor, adjust, and stabilize Gen AI systems in dynamic environments.
Select high-leverage pilot use cases that balance feasibility, risk, and measurable business value.
Empower internal AI champions to drive adoption, enable teams, and sustain momentum across the organization.
Redesign tasks and workflows to integrate Gen AI intentionally, not accidentally.
Embed structured, risk-based human oversight into Gen AI workflows to prevent silent error propagation.
Map recurring Gen AI tasks into reusable workflow archetypes that define clear stages, roles, and handoffs.
Institutionalize Gen AI knowledge through shared patterns, repositories, and feedback loops that prevent capability silos.
Generalize stable prompt patterns into parameterized metaprompts that enable scalable, consistent, and controlled output variation.
KNOWING HOW GEN AI TRANSFORMS ORGANIZATIONS
Gen 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 YOU
Remember 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!