Master text, image, and video generation as practical work skills — with a tutor that teaches the concepts and critiques your actual outputs.
The best way to learn generative AI is to work across the main modalities — text, image, and video — building real outputs and understanding why each tool behaves the way it does, rather than collecting scattered tips. LearnAI structures this into a hands-on curriculum and teaches it through conversation, adapting to whether you're a creator, marketer, or curious professional. Start free, no account needed.
Generative AI is a broad label covering very different tools: chatbots that draft and summarize, image models that render from text descriptions, video generators, voice synthesis, music tools. Most people learn one tool shallowly and stop. The professionals getting real value understand the layer underneath — how generative models work, what each modality is good for, and how to chain tools into workflows — so every new release makes them faster instead of starting them over.
LearnAI teaches that layer. You'll build a working understanding of how generative models produce text and images, then apply it: writing and editing workflows, image prompting and iteration, video generation basics, and combining tools into pipelines for the work you actually do. Your tutor explains concepts, sets exercises, and critiques your prompting technique as you go.
6 weeks at 3 hours per week · built by LearnAI, adjusted to your level and goals
This is an example of the course plan LearnAI generates — yours will be personalized from your first message.
Build the mental model behind all of it — how models learn from data and generate new text and images, explained without math.
The highest-ROI modality first — drafting, rewriting, summarizing, and repurposing content with prompts that produce consistent quality.
Learn to direct image models like Midjourney, DALL-E, and Stable Diffusion — composition, style, and the iteration loop that gets you from rough to usable.
Survey the newest frontier hands-on — short-form video generation, voice synthesis, and where these tools are production-ready versus experimental.
Chain modalities into pipelines — brief to copy to visuals to video — and design repeatable processes instead of one-off generations.
The professional layer — evaluating output quality, understanding copyright and disclosure questions, and using generative tools defensibly at work.
Generative AI proficiency shows up near the top of in-demand skills in 2026 hiring data across marketing, design, content, operations, and product roles. The expectation has shifted from 'has heard of ChatGPT' to 'can reliably produce useful output with it' — and the gap between those two is exactly what a structured course closes.
The multi-modal shift also raises the ceiling. Text generation alone was useful; text plus image plus video generation means one person can produce campaign drafts, visual concepts, and short video content that previously required a small team. Understanding the whole toolkit — including its quality limits and rights questions — is what makes that leverage real rather than theoretical.
The tutor explains how a technique works, you produce something with it, and it critiques the result — your image prompts get specific feedback on composition language, your drafts on voice and structure.
A designer exploring image models gets a different course than a marketer building content pipelines. Tell LearnAI your role and it weights the modalities and exercises accordingly.
Instead of a tour of 40 tools, you go deep on workflows: real briefs, real iteration, real quality judgment. You finish with pipelines you can run at work, not a list of bookmarks.
Work through the modules and pass the reviews, and Pro members get a LearnAI completion certificate — shareable proof of applied generative AI skills, not just course attendance.
No. Every tool in this course — ChatGPT, Claude, Midjourney, video generators — is operated in plain language. The course teaches you how the models work conceptually so you can direct them better, but there's no coding, no APIs, and no math. Technical learners who want to build with these models should look at the LLM App Development track instead.
The course teaches transferable technique using the major tools as examples: ChatGPT and Claude for text, Midjourney, DALL-E, and Stable Diffusion for images, and current text-to-video and voice tools for the newer modalities. Because tool rankings shift constantly, the emphasis is on skills that transfer — a well-constructed image prompt works across models.
Competence in text generation comes fast — most learners level up within the first week. Image generation takes longer because the iteration loop is a genuine craft; expect a few weeks of practice to produce consistently usable results. The full course runs about six weeks at three hours per week, and you're producing real output from day one.
Pro members earn a LearnAI completion certificate after passing the module reviews. To be straightforward: it's not an accredited or university-backed credential, and neither are most platform certificates — their value everywhere is signaling that you did the work. LearnAI's difference is what the work is: hands-on production and critique rather than videos and multiple-choice quizzes, so the certificate sits on top of a portfolio of things you actually made.
Yes — open the course and start without creating an account. Free covers a set number of AI tutor messages per course, which is enough to get well into the material; Pro makes messages unlimited and adds the completion certificate.
It depends on the tool's license, your jurisdiction, and how the output is used — some tools grant broad commercial rights on paid plans, and the legal landscape is still settling. The course's final module covers the practical questions to ask: what your tool's terms actually grant, when disclosure is expected, and how companies are handling this internally. It gives you the framework, not legal advice.
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