46 courses across 12 tracks
AcademAI is a public catalog of practical AI courses organized by use case, provider, and learning goal.
Begin with foundations, then move into provider-specific mastery when the goal is clear.
Scan ChatGPT, Microsoft Copilot, Perplexity, Grok, Ollama, Claude, APIs, MCP, and AI fluency tracks.
Use public overviews and the free AI Fluency foundation course before unlocking the paid mastery layer.
AcademAI's course catalog is a public map of practical AI training across provider-specific and goal-specific tracks.
Use it to compare ChatGPT workflows, Microsoft Copilot productivity, Perplexity research, Grok and xAI workflows, Ollama local AI labs, Claude and Claude Code, AI API development, Model Context Protocol, and AI fluency for work, education, students, and nonprofits.
Who the course is for, from first-time AI learners to workplace teams and technical builders.
What practical work the learner should be able to complete after the course.
Which beginner, workplace, or technical background helps the learner choose confidently.
How AcademAI uses public provider sources while writing original lessons and exercises.
Course summaries stay open for visitors comparing the catalog, and the AI Fluency foundation course is free before checkout.
Membership unlocks full lessons, scenario tests, progress tracking, AI syllabi, and certificates.
Each public overview explains who the course is best for, from new AI learners to builders and workplace teams.
Course summaries focus on practical work learners should be able to complete, not vague tool familiarity.
Prerequisite notes help visitors choose a beginner-friendly entry point or a more technical provider track.
AcademAI uses public provider documentation as source context, then writes original lessons, exercises, and review gates.
Topic hubs help visitors move from a broad AI training question to a focused course sequence. Each hub explains who it is for, what learners should be able to do, which courses fit, and what prerequisites matter.
Start with AcademAI's free AI Fluency foundation course before choosing a paid mastery path.
Learn how to use Claude for everyday work tasks, understand core features, and explore resources for more advanced learning.
Integrate Claude Code into your development workflow with hands-on exercises and real-world scenarios.
Learn to work alongside Claude on your real files and projects. Hands-on coverage of the Cowork task loop, plugins, and workflows.
Learn how to build, configure, and share Skills in Claude Code — reusable markdown instructions that Claude automatically applies.
Learn how to use and create sub-agents in Claude Code to manage context, delegate tasks, and build specialized workflows.
Comprehensive course covering the full spectrum of working with Anthropic models using the Claude API.
First-of-its-kind training for integrating Claude models with AWS services through Amazon Bedrock.
Full spectrum of working with Anthropic models through Google Cloud's Vertex AI platform.
Learn to build MCP servers and clients from scratch using Python. Master MCP's three core primitives: tools, resources, and prompts.
Discover advanced MCP implementation patterns including sampling, notifications, file system access, and production transport mechanisms.
Empowers faculty, instructional designers, and educational leaders to apply AI Fluency into teaching practice.
Empowers students to develop AI Fluency skills that enhance learning, career planning, and academic success.
Empowers academic faculty, instructional designers, and others to teach and assess AI Fluency in instructor-led settings.
Empowers nonprofit professionals to develop AI fluency to increase organizational impact while staying true to mission and values.
Build a practical map of modern OpenAI tools, responsible use habits, verification loops, and tool-selection judgment for everyday AI work.
Move from casual prompting to repeatable ChatGPT workflows using context, files, search, projects, custom GPTs, skills, and review discipline.
Design practical ChatGPT workflows for writing, marketing, education, small business, and nonprofit work with review, privacy, and quality gates.
Use Codex to plan coding tasks, navigate repositories, run edit-review-test loops, and hand off work safely through Git-aware builder workflows.
Build practical OpenAI API foundations with Responses API patterns, structured outputs, tool use, multimodal inputs, streaming, evals, and production safety.
Build a practical map of Grok, xAI account surfaces, everyday prompting, source checks, privacy choices, and responsible workflow habits.
Use Grok in team settings with workspace setup, license activation, sharing norms, privacy boundaries, adoption playbooks, and review gates.
Connect Grok to email, calendars, cloud files, collaboration stores, and external data with clear permissions, source boundaries, and review loops.
Build practical xAI API foundations with accounts, keys, models, pricing awareness, request design, tools, structured outputs, and production guardrails.
Use Grok Build for agentic development workflows with repository inspection, AGENTS.md instructions, skills, plugins, hooks, Git, tests, and handoff review.
Design Grok creative workflows across image, video, voice, and multimodal inputs with prompt craft, cost checks, safety boundaries, and final review.
Build a practical Perplexity foundation for answer-engine research, source trails, Learn Mode, privacy choices, and verification habits.
Design deeper Perplexity research workflows that compare sources, expose disagreement, check evidence quality, and produce decision-ready briefs.
Use Perplexity Spaces for shared research, files, connectors, instructions, collaboration, and controlled team knowledge workflows.
Plan browser and Computer-assisted Perplexity workflows with task scoping, source context, approvals, prompt-injection awareness, and handoff review.
Build with Perplexity API surfaces including Sonar, Search API, Agent API, citations, filters, structured results, streaming, cost, and production guardrails.
Design advanced Perplexity research-agent systems with MCP, embeddings, retrieval, source-aware agents, evaluation sets, and production security.
Build a practical Microsoft Copilot foundation for product surfaces, web and work grounding, account context, responsible AI, and verification before action.
Turn Microsoft 365 Copilot Chat into a disciplined work assistant for drafting, summarizing, researching, comparing, planning, and safe daily use.
Design practical Word, Excel, PowerPoint, Outlook, Teams, OneDrive, and SharePoint workflows with source-aware review and reusable job patterns.
Move beyond prompt tips into reusable Copilot prompt systems, source packages, critique passes, team prompt cards, and quality rubrics.
Plan Copilot adoption with readiness checks, champion networks, risk tiers, department workflow playbooks, feedback loops, and value measurement.
Design business agents with use-case fit checks, knowledge boundaries, instructions, actions, connectors, testing, analytics, and governance.
Use GitHub Copilot across developer surfaces with repository context, tests, PR workflows, agent mode, MCP, responsible AI, privacy, and secure coding habits.
Build an AcademAI Local AI Lab foundation for installing Ollama, running first models, choosing local or cloud fit, and verifying privacy boundaries.
Operate Ollama models through the CLI with pull, run, list, ps, stop, tags, context habits, troubleshooting, and repeatable lab checks.
Shape model behavior with an Ollama Modelfile using FROM, PARAMETER, SYSTEM, TEMPLATE, adapters, imports, licensing review, and behavior tests.
Build Ollama-powered applications with local and cloud base URLs, generate, chat, embeddings, official libraries, streaming, and server-side boundaries.
Create source-aware Ollama workflows with tool calling, web search and fetch, embeddings, simple RAG, MCP integration, and hallucination controls.
Use ollama launch, Codex-style tooling, Claude Code, OpenCode, and OpenClaw workflows with model fit, permissions, context, and review discipline.
Build a complete local-AI lab playbook for logs, hardware constraints, cloud fallback, evals, privacy, security, model fit, and capstone governance.
