> For the complete documentation index, see [llms.txt](https://opencampus.gitbook.io/opencampus-machine-learning-program/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://opencampus.gitbook.io/opencampus-machine-learning-program/courses/archive/intermediate-machine-learning-legacy/hello-and-welcome.md). # Hello and welcome😊 Great that you want to dive into the deep water in Machine Learning. These are exciting times with major advancements on a quarterly basis like ChatGPT, Whisper, StableDiffusion and so many more. Nevertheless all these exciting models were developed with solid ML knowledge which is what we want to acquire in this course. This is a course which brings you from beginner to intermediate or even advanced. It is formally called Intermediate Machine Learning but following HuggingFace🤗 terms which we will use heavily in the course I like to call the course SmilingFace😊. This is meant ironically, because you will never laugh in the course😊. Okay joking aside the use of smileys during learning and practioning ML helps us to remember to have fun, laugh about our mistakes and take ourself not seriously as it was proposed by the HuggingFace🤗 community. Therefore we will use our 😊 heavily in this course. On the next pages you can see what the content of each course week will be starting with what will happen during each of our course sessions. Then again the SmilingFace😊 will lead you to what else to do in the week. I have divided the course into three levels of course work: 😊 The part after one 😊 is mandatory for each course participant for a for successful participation 😊😊 The part after two 😊😊 is voluntary but recommended 😊😊😊 The part after three 😊😊😊 is completely voluntarily for the ones who really want to know Remember the course instructor(me) is also fallible so please question me if you see something that does not kind of seem right for you. Also always ask questions especially if you don't fully understand something. This is really why we give this course so that you understand everything😊 Own contributions or suggestions for improving the course as well as feedback are always welcome😊 Let's dive right in! --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://opencampus.gitbook.io/opencampus-machine-learning-program/courses/archive/intermediate-machine-learning-legacy/hello-and-welcome.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.