The AI Revolution Mastering the Tools for Tomorrow #254037

Upon completion of this course, participants will be able to:

• Navigate the AI Tool Ecosystem: Identify and evaluate the key categories of AI tools and their specific applications for different business functions and creative tasks.

• Achieve Proficiency in Core AI Platforms: Gain hands-on experience with leading tools for content generation (e.g., ChatGPT, Claude), data analysis, image creation, and process automation.

• Master the Art of the Prompt: Learn and apply advanced prompt engineering techniques to reliably generate high-quality, relevant, and complex outputs from AI systems.

• Integrate AI into Existing Workflows: Develop strategies for embedding AI tools into daily tasks to automate routine work, enhance decision-making, and accelerate project completion.

• Apply Tools to Real-World Problems: Use a suite of AI tools to complete a multi-stage project, from research and ideation to creation and presentation.

• Critically Evaluate AI Outputs: Assess the quality, accuracy, and potential biases of AI-generated content to ensure ethical and effective use.

This course is designed for any professional who wants to leverage AI tools to enhance their efficiency and capabilities:

• Knowledge Workers & Individual Contributors across all departments

• Managers & Team Leaders seeking to improve team productivity

• Marketing & Content Creators (writers, designers, social media managers)

• Data Analysts & Consultants

• Software Developers & Engineers

• Project Managers & Coordinators

• Entrepreneurs & Small Business Owners

• Researchers & Academics

• Anyone eager to future-proof their skills and stay relevant in a rapidly changing workplace.

• Pre-assessment
• Live group instruction
• Use of real-world examples, case studies and exercises
• Interactive participation and discussion
• Power point presentation, LCD and flip chart
• Group activities and tests
• Each participant receives a binder containing a copy of the presentation
• slides and handouts
• Post-assessment

5-Day Course Outline

Day 1: The Foundation: Understanding the New Toolbox

• AM: Welcome to the Revolution

  • The State of Play: A tour of the current AI landscape.

  • Demystifying the Tech: How LLMs, Diffusion Models, and other key technologies work at a conceptual level.

  • Tool Categories: Mapping the ecosystem of generators, analyzers, automators, and assistants.

• PM: Your First AI Assistant: Mastering Text-Based Generators

  • Deep dive into platforms like ChatGPT and Claude.

  • Prompt Engineering 101: Principles of clarity, context, and iteration.

  • Hands-on Lab: Basic tasks like drafting emails, summarizing documents, and brainstorming ideas.

Day 2: The Creative Arsenal: AI for Content and Design

• AM: The Written Word

  • Advanced Prompt Engineering for long-form content: blogs, reports, scripts.

  • Tailoring tone, style, and format for different audiences.

  • Hands-on Lab: Using AI to research and draft a short article or marketing copy.

• PM: The Visual World

  • Introduction to image generation with tools like Midjourney and DALL-E.

  • Crafting effective visual prompts: style, composition, lighting.

  • Hands-on Lab: Generating a set of concept images for a specific brand or project.

Day 3: The Analyst’s Edge: AI for Data and Decision-Making

• AM: Conversational Data Analysis

  • Using tools like ChatGPT Advanced Data Analysis or Google Gemini to analyze datasets.

  • Uploading spreadsheets, asking questions in plain language, and generating insights, charts, and forecasts.

• PM: Automating Research and Synthesis

  • Using AI to scan, summarize, and synthesize information from large volumes of text or web sources.

  • Hands-on Lab: Analyzing a provided dataset to find trends and create a presentation of key findings.

Day 4: The Productivity Engine: Automation and Code

• AM: Task and Process Automation

  • Overview of automation tools that leverage AI.

  • Conceptualizing workflows for automating repetitive tasks.

• PM: AI-Powered Development

  • Introduction to code assistants like GitHub Copilot and Amazon CodeWhisperer.

  • How developers and non-developers can use AI to write, explain, and debug code snippets.

  • Hands-on Lab: Using a code assistant to build a simple webpage or automate a data task.

Day 5: Integration and Capstone Challenge

• AM: Building Your AI-Augmented Workflow

  • Strategies for combining multiple tools into a seamless workflow.

  • Critical thinking and ethics: Identifying hallucinations, bias, and ensuring quality control.

  • Establishing best practices for security and privacy when using AI tools.

• PM: Capstone Project: The AI Tool Sprint

  • Final Challenge: Teams are given a complex, multi-part challenge (e.g., “Launch a new product idea”).

  • They must use a suite of AI tools to: conduct market research, generate a brand name and logo, draft a press release, and create a data-backed launch plan.

  • Presentations and peer review of the process and outputs.

  • Course Wrap-Up: Curating your personal AI toolkit and action plan for continued learning.