daBongo LMS AI Training Courses

Students learn to apply ChatGPT to four high-value everyday task categories - organizing thoughts and priorities, summarizing long content, drafting everyday communications, and building personal systems - generating immediate time savings from their first session.

Students learn to create a ChatGPT account, send their first effective messages using the four-part opening message framework, follow up and iterate productively, use ChatGPT as a learning partner with the four-tier verification habit, and identify the five everyday task categories where ChatGPT delivers the most immediate value.

Students learn what information is safe and unsafe to share with ChatGPT, how OpenAI handles conversation data, what privacy controls they have, and how to maintain human oversight of AI-assisted decisions.

Students learn what ChatGPT actually is - and is not - how GPT language models process text, what the different model tiers mean for users, and how to apply the four-tier verification framework with a nuanced understanding of why verification is essential.

Students learn to use ChatGPT as a practical career support tool - tailoring resumes and cover letters with the three-input method, preparing for interviews using the STAR framework, researching career pivots with transferable skills analysis, and drafting professional communications.

Students learn to use ChatGPT as a systematic quality assurance partner - applying criteria-first review, logic and consistency checking, and custom review checklists to catch errors, gaps, and weaknesses before work reaches its audience.

Students learn to use ChatGPT as a rigorous thinking partner - surfacing hidden assumptions, running pre-mortem analysis, stress-testing plans, and using perspective-taking to understand decisions from others' viewpoints.

Students learn a professional writing workflow with ChatGPT - architecture-first planning, layered revision across content/structure/style, and audience calibration - producing documents that serve their readers effectively and sound authentically like the writer.

Students learn to use ChatGPT as a personalized tutor - designing targeted learning paths, applying active recall and the Feynman technique, and exploring new fields at calibrated depth - transforming passive information consumption into durable understanding.

Students learn the structural principles behind effective ChatGPT prompts - the five-component anatomy, context and constraints deep dives, structured output formats, and assumption-surfacing techniques - replacing guesswork with a systematic, repeatable approach.

Students learn ChatGPT's most powerful distinguishing capabilities - Custom GPTs for specialized AI personas, memory feature management, multimodal capabilities (vision, voice, and ChatGPT image generation), data analysis / file analysis tools for file and data work, web search / browsing for current web information, and 15 high-impact power-user workflows.

Students learn how to start their first Claude conversations confidently, follow up and iterate effectively, get explanations that actually help them learn, and use Claude for immediate everyday tasks.

Students learn what Claude is, how it processes language, what its limitations are, and how to build a realistic mental model before they begin prompting.

Students learn how to use Claude for practical everyday productivity - organizing tasks and decisions, summarizing content they don't have time to read in full, drafting personal and professional communications, and building simple systems that save time every week.

Students learn how to use Claude as a career partner - writing stronger application materials, preparing for interviews, researching career pivots, and building the professional communication skills that get results.

Students learn what information to protect when using Claude, how to handle sensitive topics responsibly, when to keep humans in charge of decisions, and how to choose the right Claude tier for their needs.

Students learn how to structure prompts with the right level of context, constraints, and format instructions to get precise, useful outputs from Claude.

Students learn how to use Claude as a personal learning system - breaking down complex subjects, building structured study plans, testing their own understanding, and accelerating skill development across any field.

Students learn how to use Claude's interface features - navigation, Custom Instructions, Projects, file uploads, and Artifacts - alongside the prompt command patterns that power users rely on to get faster, more precise results every time.

Students learn how to use Claude for goal definition, structured research, multi-step planning, and comparing approaches - moving from task executor to genuine thinking partner.

Students learn how to use Claude to draft professional documents, transform rough ideas into structured content, build reusable prompt templates, and iterate toward polished final outputs.

Students learn how to use Claude to check, verify, and improve their own work - including identifying logical gaps, catching errors, flagging assumptions, and knowing when human review is required.

Students learn what each of the three Claude desktop modes actually is - Chat, Code, and Cowork - what each one can do, and how to choose the right mode for any given task or workflow.

Students discover the hidden features, lesser-known commands, keyboard shortcuts, and proven prompting techniques that separate casual Claude users from power users - across all three modes and applicable to real professional workflows.

Students learn every layer of Claude's memory system - what persists by default, what requires setup, and how to build a complete persistent AI brain that retains their working relationship, preferences, and project knowledge across every session.

Students build the core habits that make Claude genuinely useful for everyday professional work - moving beyond occasional curiosity to a deliberate practice of prompt quality, conversation management, and knowing when AI judgment applies and when it does not.

Students move beyond the theory of Claude Cowork into hands-on practice - learning the Cowork task loop, working with real files and research, using plugins and skills in context, and steering multi-step work responsibly so they can be productive in their first week.

Students develop the cognitive and practical skills that separate effective AI collaborators from passive AI users - learning how to evaluate AI output critically, choose the right AI relationship for each task, structure requests clearly, and maintain ethical work habits when AI is involved.

Students build an accurate, practical mental model of what AI systems can do, where they struggle, and why - equipping them to make better decisions about when and how to use AI in professional contexts.

Small business owners learn to move from AI awareness to strategic AI deployment - identifying where AI adds the most value in their business, building team AI habits, managing real risks, and building a sustainable AI practice that increases organizational impact without compromising mission and values.

Builders - developers, designers, product managers, and independent makers - learn to use AI effectively across the full arc of building: from problem scoping and research through design and prototyping, development and testing, to shipping responsibly with AI-integrated evaluation and ethical product ownership.

Learn to use Grok as a structured thinking partner by defining clear goals, providing useful context, requesting structured output, iterating effectively, and applying verification habits.

Learn advanced practical workflows for organizing research, running structured review loops, supporting decisions with trade-off analysis, and building personal AI-assisted productivity systems.

Students learn to access Grok through the X platform and at grok.com, the four-part opening message framework for effective conversations, and the four-tier verification system for calibrating trust in Grok output.

Students learn how Grok generates responses, what makes its real-time X access genuinely different from other AI tools, what DeepSearch actually does, and an honest map of Grok's capabilities and limitations.

Students learn to use Grok for everyday productivity - the brain dump technique, quick research with appropriate source awareness, using Grok's direct style to get decisive answers, and building a minimum viable Grok habit.

Students learn to use Grok for resume tailoring, interview preparation, industry research, professional communication drafting, and career planning - with Grok's X access for industry trend research and appropriate verification standards throughout.

Students learn the six categories of information never to share with any AI, Grok's specific privacy context within the X platform ecosystem, Grok's content approach and how to use it responsibly, and the five non-negotiable professional review categories.

Develop expert-level reasoning skills by mastering advanced prompting patterns, self-critique methods, multi-step problem decomposition, and structured decision frameworks.

Learn to design and maintain personal knowledge management systems, long-term review loops, and scalable workflows that combine reusable templates, verification habits, and clear human oversight.

Students learn the five-component prompt framework adapted for Grok's direct style, how to use Grok's X integration in prompts, DeepSearch activation and scoping, and advanced techniques for assumption surfacing and conversation shaping.

Students learn to use Grok as a personalized learning accelerator - with DeepSearch for skill demand research, the explain-it-three-ways technique, custom study plan building, and Grok's X access for professional currency.

Students learn to use Grok's direct style and research capabilities for structured decision-making, assumption testing, pre-mortem analysis, and project planning - turning Grok's directness into a tool for rigorous thinking rather than fast-but-sloppy decisions.

Students learn the structure-first writing workflow adapted for Grok's direct style, iterative improvement using Grok's honest feedback, tone and audience adaptation, and the personal voice review that keeps Grok-assisted writing from sounding algorithmic.

Students with zero prior AI experience learn how to start, guide, follow up on, and get real value from their very first conversations with Google Gemini - building confidence and practical skill from the first session.

Students build the foundational mental model needed to use Gemini intelligently - understanding what it is, how it processes information, what its real-time web access means in practice, and how to verify its outputs responsibly.

Students learn to apply Gemini to four high-value everyday task categories - organizing thoughts and decisions, summarizing long content, drafting communications, and building simple personal systems - generating immediate time savings from their first session.

Students learn to use Gemini as a practical career support tool - tailoring resumes and cover letters, preparing for interviews, researching career pivots, and developing professional communication skills - with honest guidance about what Gemini can and cannot do for a job search.

Students learn what information is safe and unsafe to share with Gemini, how Google handles Gemini conversation data and what privacy controls they have, and how to ensure human judgment remains in charge of consequential decisions.

Students learn the structural principles behind effective Gemini prompts - the five-component anatomy, context and constraints, structured output formats, and assumption-surfacing techniques - building the skill that underpins every advanced AI workflow.

Students learn to use Gemini as a personalized learning partner - designing structured learning paths for new skills, using active recall and the Feynman technique to deepen retention, exploring new fields at calibrated depth, and accelerating professional development.

Students learn to use Gemini as a structured thinking partner - challenging assumptions, stress-testing plans, exploring problems from multiple angles, and surfacing blind spots before they become costly mistakes.

Students learn advanced drafting workflows with Gemini - building structured outlines before drafting, using layered revision techniques to improve any draft, adapting writing style and voice across audiences, and producing long-form content efficiently without losing quality.

Students learn to use Gemini as a systematic quality assurance partner - reviewing documents and outputs for logic, completeness, consistency, and accuracy gaps - while maintaining appropriate human accountability for final decisions.

Students learn Gemini's advanced feature set - connecting Google services through Extensions, creating custom AI personas with Gems, working with multimodal inputs (images, documents, audio), and applying 15 power-user workflows that go beyond standard conversations.

Students learn to have their first productive conversations with Microsoft Copilot - using the four-part opening message framework, iteration techniques, learning strategies, and everyday task applications - building confidence from the very first session.

Students learn what Microsoft Copilot actually is, how large language models work at a conceptual level, what makes Copilot's Microsoft ecosystem integration unique, the difference between Copilot and Bing search, and how to use the four-tier verification framework to interact with Copilot responsibly.

Students learn to apply Copilot to four high-value everyday task categories - organizing thoughts and priorities, summarizing long documents and email threads, drafting communications, and building personal systems - generating immediate time savings from their first session.

Students learn to use Copilot as a practical career support tool - tailoring resumes and cover letters, preparing for interviews using the STAR framework, researching career pivots with transferable skills analysis, and drafting professional communications - with honest guidance about what Copilot can and cannot do for a job search.

Students learn what information is safe and unsafe to share with Copilot, how Microsoft handles Copilot conversation data, what privacy controls they have, and how to maintain human oversight of AI-assisted decisions.

Students learn the structural principles behind effective Copilot prompts - the five-component anatomy, context and constraints, structured output formats, and assumption-surfacing techniques - building the skill that underpins every advanced Copilot workflow.

Students learn to use Copilot as a personal learning partner - designing learning paths, applying active recall and the Feynman technique, and exploring new fields at calibrated depth - transforming Copilot into a tutor that adapts to how they specifically learn.

Students learn to use Copilot as a rigorous thinking partner - surfacing hidden assumptions, running pre-mortem analysis, and stress-testing plans from multiple perspectives - developing a more honest, disciplined approach to complex decisions.

Students learn a professional writing workflow with Copilot - architecture-first planning, layered revision across content/structure/style, and audience calibration - producing drafts that sound like themselves and serve their readers effectively.

Students learn to use Copilot as a systematic quality assurance partner - applying criteria-first review, logic and consistency checking, and custom review checklists - catching errors, gaps, and weaknesses before work reaches its audience.

Students learn Copilot's most powerful differentiating capabilities - Microsoft 365 deep integration across Outlook, Teams, Word, Excel, and PowerPoint; Copilot Pages for collaborative AI work; advanced plug-in and web access features; and the 15 highest-impact power-user workflows for professional settings.

Students learn to access Perplexity AI, conduct their first effective searches, read and evaluate citations, and apply the three-question framework and four-tier verification standard that form the foundation of responsible AI use.

Students learn how Perplexity's search-to-AI synthesis pipeline works, what sources it draws from, why citation presence does not equal claim accuracy, and what the free vs. Pro feature comparison means for how they should use each.

Students learn to use Perplexity AI as a daily research and productivity tool - turning vague questions into answered action items, summarizing competing information, and building a minimum viable research system for recurring needs.

Students learn to use Perplexity AI's real-time search capability for company research, industry analysis, salary benchmarking with sourced verification, and professional communication preparation - giving job seekers a researched, credible edge.

Students learn the six categories of information never to enter into any AI research tool, Perplexity's specific data practices and privacy controls, how to evaluate source trust hierarchy, and the five categories requiring non-negotiable professional human review.

Students learn the five-component prompt anatomy adapted for Perplexity's search-first nature, context and constraint techniques that improve search precision, structured output requests, and Perplexity-specific prompting strategies for research tasks.

Students learn to use Perplexity AI's real-time research capability to design learning paths, explore unfamiliar fields with verified current information, and apply academic research habits to any learning goal.

Students learn to use Perplexity AI's research capability to test assumptions with real evidence, gather data for pre-mortem analysis, and research multiple stakeholder perspectives - making plans and decisions more evidence-grounded and rigorous.

Students learn to use Perplexity AI as a research partner for writing - integrating real-time sourced research into documents, synthesizing multiple perspectives, and verifying factual claims before publication.

Students learn to use Perplexity AI to verify claims in their own work, cross-reference information from multiple source types, conduct completeness research, and build systematic verification checklists for recurring review tasks.

Students learn Perplexity AI's most powerful distinguishing capabilities - Pro Search for deep multi-step research, Focus modes (Academic, Writing, Video, Reddit, Wolfram Alpha) for specialized source targeting, Spaces for collaborative research organization, and 15 power-user research workflows across professional use cases.

Students learn how to access and use Meta AI across WhatsApp, Instagram, Facebook, Messenger, and meta.ai - including the four-part opening message framework and the four-tier verification standard that is the foundation of responsible AI use.

Students learn what powers Meta AI (Llama), how AI language models generate responses, what the context window means for platform-embedded conversations, and what Meta AI can and cannot reliably do.

Students learn to use Meta AI across WhatsApp, Instagram, and meta.ai for everyday productivity - the brain dump technique, quick research and summarization, decision support, and building a minimum viable AI habit on platforms they already use.

Students learn to use Meta AI for resume tailoring, interview preparation, industry research, professional communication drafting, and career planning - with appropriate verification standards for each use case.

Students learn the six categories of information never to share with any AI tool, the unique privacy context of Meta AI within Meta's social media ecosystem, the consequential decision test, and five non-negotiable professional review categories.

Students learn the five-component prompt anatomy, deep application of context and constraints, structured output techniques, and Meta AI-specific prompting strategies for both mobile and desktop contexts.

Students learn to use Meta AI as a personalized learning accelerator - researching skill demand, breaking down unfamiliar fields, building custom study plans, and staying current in their professional domain.

Students learn to use Meta AI for structured decision-making, assumption testing, pre-mortem analysis, and multi-perspective thinking - moving beyond information retrieval to genuine cognitive partnership.

Students learn the full Meta AI writing workflow - from structure-first outlining through drafting, iterative improvement, tone and audience adaptation, and the essential personal voice review before any piece goes out.

Students learn to use Meta AI for criteria-based review, logic and consistency checking, completeness analysis, and building custom review checklists - turning Meta AI into a systematic quality assurance partner for any professional deliverable.

Students master Meta AI's distinctive features - the Imagine image generation tool, deep platform integration across WhatsApp/Instagram/Facebook/Messenger/meta.ai, and 15 practical power-user workflows.