Course Taxonomy: Generative AI

AI for Executives

Posted on November 6, 2024 by -

Part 1: Introduction to Generative AI

  • What is Generative AI?
  • Current and emerging technologies
  • Overview of Impacts
  • Industry use cases and success stories

 

Part 2: Strategic Planning with AI

  • Aligning AI with business goals and strategies
  • Identifying AI opportunities within your business processes
  • Understanding the most immediately accessible value and initiatives
  • Workshopping Alignment: Mapping potential AI applications to business units

 

Part 3: Leadership in AI Implementation

  • Leading change and fostering an AI-ready culture
  • Understanding and leading the necessary technology stakeholders
  • Building in-house AI capabilities vs. partnering
  • Case Study Analysis: Real-world examples of successful executive leadership on AI projects

 

Part 4: Risk Management, Ethics, and Legal Liability Concerns

  • Navigating the ethical implications of AI
  • Managing data privacy and security risks
  • Developing a compliance framework for AI applications

 

Part 5: ROI and Metrics

  • How to think about AI-driven value
  • Setting up success metrics for AI projects
  • Tools for tracking and analyzing AI project performance
  • ROI expectations and reality checks

 

Part 6: Q&A and Wrap-Up

  • Open discussion to address specific concerns and scenarios from participants
  • Summary of key takeaways
  • Next steps and resources for further learning

Introduction to AI & Machine Learning eLearning

Posted on June 18, 2024 by -

Part 1: Introduction to AI

  • Overview: What is AI and its significance?
  • History: Brief evolution of AI and its modern applications.
  • Ethics: Considerations on AI ethics, bias, privacy, and societal impacts.

Part 2: AI Concepts

  • AGI, ANI, ASI: Explanation of different AI levels and their implications.

Part 3: Machine Learning Basics

  • Goals: Objectives of ML-like prediction and pattern recognition.
  • Types:
    • Supervised Learning: Using labeled data for tasks like classification.
    • Unsupervised Learning: Identifying patterns in unlabeled data.
    • Semi-supervised Learning: Leveraging both labeled and unlabeled data.
  • Reinforcement Learning: Learning from interactions with an environment.

Part 4: Assessment

AI for Business Analysis

Posted on May 9, 2024 by -

Part 1: Understanding AI’s Role in Business Analysis

Part 2: Using AI to Jumpstart a Project

  • Applying prompt engineering techniques to plan and refine a product

Part 3: Organizing AI-Created Content

  • Transforming AI outputs and transforming them into coherent, valuable resources

Part 4: Crafting User Stories with AI

Part 5: AI and Stakeholder Interviews

  • Training simulated interviews by taking on
  • personas and responding to questions

Part 6: Potential Pitfalls and Social Risks

  • Detecting “hallucinations” and critically evaluating and validating AI results

Part 7: Requirements Analysis and Solution Design

  • Using AI to create many valuable BA artifacts such as process models and ERDs

Part 8: AI-Assisted UI Design

  • Transforming AI outputs into visual representations to produce UI prototypes

Part 9: Writing Tests with AI

  • Creating test scenarios and evaluating results to catch errors or gaps in coverage

Part 10: AI for Complete, Consistent, & Coherent Analysis

  • Strategies for responsible creation of AI-created artifacts under human supervision

Part 11: Creative Applications of Generative AI

  • Using generative AI for writing, education, and presentation design.

Part 12: Implementing AI-Driven Business Analysis

  • Responsibly leveraging AI's potential business analysis under human supervision

AI for Software Testing

Posted on May 9, 2024 by -

Part 1: Introducing Generative AI for Software Testing

Part 2: Let’s Test with AI

  • Use AI agents to generate and run tests

Part 3: Modelling for Testing

  • Apply different ways to structure a problem and organize the testing process

Part 4: Test Planning with AI

  • Use AI to help create an overall test strategy, using a Test Strategy Canvas and, Testing Quadrants

Part 5: Testing Single Functions

  • Learn how AI can assist with equivalence partitioning, boundary value analysis, state and preconditions when defining tests

Part 6: Evaluate Tests

  • Identifying missing and redundant tests as well as the level of test coverage

Part 7: Activities and Processes

  • Use AI to generate use cases in several forms (traditional, Given-When-Then, and graphical) and generate detailed test cases

Part 8: Planning the End Game

  • Create AI-generated test plans for UAT, alpha, beta, and usability testing

Part 9: Stories and Scenarios

  • Use AI to present a user story in terms of a set of scenarios that need to pass

Part 10: Automation

  • Use AI to generate automated test cases

Part 11: Quality Attributes & Non-functional Requirements

Part 12: Evaluating AI Readiness

  • Ethical considerations and emerging trends

AI for Project Management

Posted on May 9, 2024 by -

Part 1: Generative AI Enablement

  • AI Capabilities and Limitations
  • Best Practices for Interacting with LLMs
  • Identifying Automation Use Cases

Part 2: AI-Enhanced Project Management Environments

  • AI and Project Management Tooling
  • Implementing an Internal LLM

Part 3: Applying AI in daily PM work

  • Content generation and communication assistance
  • Dataset identification and capture
  • Sentiment Analysis for Stakeholder Feedback
  • Search and Information retrieval and extraction
  • Text Summarisation for Efficient Reporting

Part 4: Implementing AI within a Project Management Framework

  • Project Lifecycle and Governance
  • Risk, Stakeholder and Change Management

Part 5: Ethical Considerations in AI-assisted Projects

  • Data Privacy and Security
  • AI Bias
  • Legal and Compliance Considerations

Part 6: Developing your AI-enabled Project Management Approach

  • Current State Assessment
  • Creating an Adoption Roadmap

Part 7: Future Trends

AI & Machine Learning for the Enterprise Overview

Posted on May 1, 2024 by -

  1. Introduction to AI & Machine Learning
  2. Deeper Dive into Machine Learning
  3. Leveraging AI in Business & Decision Making
  4. Hot Trends for AI in Business: Large Language Models (LLM), Generative AI and GPT
  5. Basics of Neural Networks
  6. Natural Language Processing (NLP) & Sentiment Analysis
  7. Using AI for Image, Video, and Audio Processing
  8. AI for Business Technical Tools: Data Science, Deep Learning & The Cloud
  9. Practical Applications and the Future of AI in Business

AI Basics for Everyday Business Camp: Part 2

Posted on May 1, 2024 by -

Part 1: Expanding Your AI Vocabulary and Understanding GPT-Based Tools

  • Introducing and exploring GPT-based tools
  • Understanding how GPT-based tools leverage AI to provide value
  • Exploring use cases of GPT-based tools in various industries
  • Distinguishing between different AI models and algorithms
  • Understanding the evolution and future trends of AI

Part 2:Next-Level Engagement with AI: Enhancing Communication with GPT-Based AI Tools

  • Developing advanced skills to leverage GPT-based tools for improving customer communication
  • Building on previous communication skills with AI tools
  • Simulating customer service interactions with GPT-based tools like ChatGPT and InstructGPT
  • Deepening understanding of AI capabilities in customer service
  • Discussing AI-enabled customer segmentation and personalization
  • Exploring AI role in handling and resolving customer complaints
  • Lab: Simulating complex customer service interactions with GPT-based tools

Part 3: Streamlining Workflow with GPT-Based AI Tools

  • Learning how GPT-based tools can optimize workflows and automate tasks
  • Exploring tools like Trello AI, IFTTT
  • Understanding the AI integration in project management tools
  • Discussing the benefits of AI-driven task automation
  • Lab: Setting up an AI-integrated workflow using GPT-driven apps

Part 4: Enhancing Collaboration with GPT-Based AI Tools

  • Using GPT-based tools like ChatGPT to foster efficient teamwork
  • Exploring AI’s role in remote work and virtual collaboration
  • Understanding how AI can foster efficient teamwork
  • Using AI in tools like Microsoft Teams and Google Docs
  • Exploring AI’s role in remote work and virtual collaboration
  • Understanding how AI can improve documentation and sharing of knowledge
  • Lab: Collaborating on a project using GPT-driven suggestions and ideas

Part 5: Leveraging GPT-Based AI Tools for Smarter Decision Making

  • Using GPT-based tools to support data-driven decision-making and risk management
  • AI for business intelligence, beyond the basics
  • Understanding AI in risk assessment, resource allocation
  • Exploring the role of AI in strategic planning and decision making
  • Understanding how AI can analyze trends and forecast outcomes
  • Lab: Running a complex risk assessment scenario using GPT-based tools

Part 6: Boosting Personal and Team Productivity with GPT-Based AI Tools (2 hours)

  • Exploring how GPT-based AI personal assistants and project management tools can enhance productivity
  • Understanding AI in time management and task prioritization
  • Discussing how AI can enhance personal productivity and well-being
  • Exploring the role of AI in managing team productivity
  • Lab: Setting up and using a GPT-based AI personal assistant

Part 7: Advanced Applications of GPT-Based AI Tools in Business

  • Understanding how GPT-based tools can enhance customer experiences, marketing, HR, and sales
  • Exploring advanced use cases of AI in marketing, HR, sales, and more
  • Introduction to AI sentiment analysis, AI in recruiting, AI in sales forecasting
  • Understanding the role of AI in enhancing customer experiences
  • Discussing AI-driven personalization and predictive analytics in marketing
  • Lab: Using a GPT-based tool for sentiment analysis of customer feedback

Part 8: Future-Proofing Your Business with GPT-Based AI Tools

  • Identifying potential opportunities for GPT-based tool integration in your business and formulating a strategic AI plan
  • Discussing the future potential of AI in business
  • Identifying areas in one's own business for AI integration
  • Exploring potential challenges and solutions in AI adoption
  • Discussing the importance of continuous learning and adaptation in the AI landscape
  • The Role of Humans in an AI-Driven World
  • Lab: Developing a future AI strategy for a mock business using GPT-based tools

Bonus Topics / Addendum (can be self-paced)

  • Understand essential security considerations and best practices for using AI tools at work safely and effectively.
  • Permissions and access controls with AI tools
  • Considerations when sharing sensitive work data with AI
  • Understanding your organization's AI policies
  • Safe habits when using AI tools
  • Proactive steps to ensure your AI tool usage remains secure
  • Ensuring data privacy when working with AI

Part 9: The Ethics and Responsibility of AI and GPT Based Tools

  • Understand the ethical considerations and responsibilities of using AI in business
  • Privacy and data security in AI
  • Identifying and avoiding biases in AI
  • Legal considerations when using AI
  • Promoting responsible use of AI 

 

 

AI Basics for Everyday Business Camp: Part 1

Posted on May 1, 2024 by -

Part 1: Exploring AI in Today’s Business World

  • Quick View: AI Explained & Types of AI
  • Exploring AI's Role in Business
  • AI in Action: Current Trends, Skills & Roles in AI
  • Benefits and Risks of AI

Part 2: Meet Your New AI Friends & GPT Tools

  • Get to know common user-friendly AI tools for business
  • Exploring GPTs in action
  • Comparing tools & Matching the right AI tool to your business needs

Part 3: The ABCs of Prompt Engineering: AI Conversations for Beginners

  • Gain a foundational understanding of prompt engineering to effectively communicate with AI.
  • Basics of conversational AI & The Art of Crafting Prompts
  • Different Types of AI Prompts
  • Quick Guide to Effective Prompt Engineering
  • Refining Prompts: Making AI Work Harder for You
  • Managing AI’s Strengths & Weaknesses
  • Avoiding Common Pitfalls in Prompting
  • Quick Tips: Guide to Writing Great Prompts

Part 4: Boosting Personal Productivity and Efficiency with AI

  • Making AI Work for You
  • Implementing Day to Day AI: Tools to Use
  • Quick Guide for Implementing AI Intro Your Daily Workflow

Part 5: Powering Your Business with AI

  • Ways AI can boost productivity and efficiency in business 
  • AI-Enhanced Customer Service
  • Set Up a Quick ChatBot or Virtual Assistant
  • Fostering Team Productivity and Collaboration
  • Project Management with AI
  • Integrating AI with Business Software

Part 6: Leveraging AI for Business Intelligence and Decision Making

  • AI in Business Decision-Making
  • Data and AI in Business
  • Business Intelligence through AI
  • Market Research with AI
  • Risk Assessment Powered by AI
  • AI for Resource Allocation

Part 7: Staying Safe and Smart with AI Tools

  • Introduction to Data Security and AI
  • Keeping Data & Privacy Safe in the AI World
  • Quick Look: GDPR and California CCPA
  • Sharing Data: Do’s and Don’ts
  • Understanding your Organization's AI Policies
  • Guide to Ensure your AI Tool Usage Remains Secure
  • Safe Habits when using AI Tools

Part 8: The Ethics and Responsibility of AI

  • Understand the ethical considerations and responsibilities of using AI in business
  • Exploring Ethical AI / Responsible AI
  • Quick User’s Guide to AI Ethics
  • Identifying, Avoiding and Overcoming Bias in AI Systems
  • Legal considerations when using AI
  • Top Ten Quick Tips for Promoting Responsible AI

Mastering GitHub Copilot

Posted on April 23, 2024 by -

Day 1: Understanding GitHub Copilot

Part 1: Introduction to GitHub Copilot

  • Overview of GitHub Copilot and its role in modern software development
  • Understanding the underlying AI technology and its capabilities
  • Exploring the benefits of using GitHub Copilot in various development scenarios 
  • Exercise: Participants will install and set up GitHub Copilot in their preferred code editor and explore its basic functionalities.

Part 2: Setting Up GitHub Copilot

  • Installation and configuration of GitHub Copilot in different development environments
  • Integration with popular code editors and IDEs
  • Configuring preferences and customizing Copilot for personal coding style 
  • Exercise: Participants will configure and customize GitHub Copilot in their development environment according to their preferences.

Part 3: Leveraging GitHub Copilot for Code Generation

  • Exploring Copilot's code generation capabilities for different programming languages
  • Utilizing Copilot to automate repetitive code snippets and boilerplate code
  • Techniques for leveraging Copilot to speed up coding tasks and reduce manual effort 
  • Exercise: Participants will work on a coding exercise where they utilize GitHub Copilot to generate code for a specific task or functionality.

Part 4: Understanding Copilot's Contextual Assistance

  • Working with Copilot to get intelligent suggestions and context-aware code completions
  • Leveraging Copilot to improve code quality and adhere to best practices
  • Understanding how Copilot can help with debugging and error handling 
  • Exercise: Participants will work on a coding exercise where they leverage Copilot's contextual assistance to enhance code quality and address common coding issues.

Day 2: Advanced Techniques and Integration

Part 5: Advanced Code Generation with Copilot

  • Harnessing Copilot's advanced capabilities to generate complex code structures
  • Exploring techniques for code refactoring and optimization using Copilot
  • Generating code patterns for specific software design patterns and architectural styles 
  • Exercise: Participants will tackle a coding exercise that involves using Copilot to generate advanced code structures or refactor existing code for optimization.

Part 6: Collaboration and Version Control with Copilot

  • Using Copilot in a collaborative coding environment
  • Best practices for integrating Copilot with version control systems like Git
  • Leveraging Copilot for seamless code reviews and pull request workflows 
  • Exercise: Participants will work in pairs and collaborate on a coding exercise using Copilot, practicing code reviews and version control integration.

Part 7: Extending Copilot with Custom Models

  • Overview of custom model creation for GitHub Copilot
  • Building and training custom models to enhance Copilot's suggestions
  • Integrating custom models into Copilot and leveraging them for specific coding tasks 
  • Exercise: Participants will explore the process of creating and training custom models for Copilot, and then utilize them in a coding exercise to see the enhanced suggestions.

Part 8: Real-World Applications and Case Studies

  • Exploring real-world examples of how GitHub Copilot is transforming software development
  • Case studies showcasing the benefits and challenges of using Copilot in different scenarios
  • Best practices and recommendations for incorporating Copilot into existing development workflows 
  • Exercise: Participants will analyze real-world case studies and discuss the potential applications and challenges faced in each scenario. They will also brainstorm and present their ideas on how Copilot can be integrated into their own development workflows.

Exploring AI & Machine Learning for the Enterprise

Posted on April 23, 2024 by -

Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We’ll work with you to tune this course and level of coverage to target the skills you need most. Topics, agenda and labs are subject to change, and may adjust during live delivery based on audience skill level, interests and participation.

  1. Introduction to AI & Machine Learning
  2. Deeper Dive into Machine Learning
  3. Leveraging AI in Business & Decision Making
  4. Hot Trends for AI in Business: Large Language Models (LLM), Generative AI and GPT
  5. Basics of Neural Networks
  6. Natural Language Processing (NLP) & Sentiment Analysis
    1. Lab: Use an online sentiment analysis tool to analyze customer feedback from a popular business.
  7. Using AI for Image, Video, and Audio Processing
    1. Lab: Use AI in recognizing and analyzing images
  8. AI for Business Technical Tools: Data Science, Deep Learning & The Cloud
    1. Tools: Azure, Google, IBM, Amazon solutions
  9. Practical Applications and the Future of AI in Business

Next-Steps

  • Hands-on Practice
  • Resources
  • AI & ML Communities