1. How to post a question
Before you post a question here, please make sure the question you’re thinking of hasn’t been answered already. A quick search in the Search box should resolve this.
If your question has already been addressed, join the discussion – there’s so much to be said and new insight or personal experience to be shared on any data science topic.
If your question hasn’t been asked yet, go ahead and post it.
- Question titles should be descriptive and contain enough information to help the next person reading them know if this thread will be of use to them.
Bad title: I am confused!!!
Good title: What’s the difference between type 1 error and type 2 error in statistics?
- Include enough detail in the body of your question, so others can help you quickly and accurately.
- Coding questions should always include the code you’re concerned about in their descriptions. If you have tried something and it hasn’t worked, share your work.
- If you’re a 365 Data Science student and you have a question about a concept discussed in one of the lessons, please include a link to that lesson using the Lesson link box. This will help our instructor team provide better answers!
2. What are comments used for
Comments are a tool intended to expand on a question or address a minor aspect of it.
Use comments to ask for more information or clarify a question. Commenting under your own question is allowed; do so if this will add more context to your question.
If you can provide an answer to a question in the HUB, please do so using the answer field, rather than the comments.
3. How to use the tag system
Tags help keep the HUB organized. When you are asking a question, please provide tags in the tag field.
Tags can be used in two ways – for searching by tag from the HUB homepage, or to browse by tag from within a question.
- Searching by tag
Use a hash (#) and then type out the term you’re interested in. If other users have used this tag when they asked their questions, you will see those questions. For instance, if you are interested in Python related questions, simply type ‘#python’ in the Search bar;
- Navigating to a tag from within a question
If you’re inside a question and want to browse related questions, you can use the tags below the question to do so. Clicking on a tag will do the same as searching by tag in the search bar.
4. Who can post a question
Any registered user can ask a question.
Students in the 365 Data Science Program are automatically registered into the HUB.
Users who a new to the website, welcome to 365 Data Science! If you are not yet registered, you will be prompted to do so before you can interact with the HUB.
5. Who can answer a question
Any registered user can answer a question.
If you have the know-how to help somebody else, you are welcome to do so. Try to be friendly and helpful in your answers, this is a learner’s community.
If your answer is complete and accurate, the Original Poster or our Team will mark the question as closed.
6. What are Super Learners
Super Learners are students who are actively studying data science with the 365 Data Science Program.
To support our students best in their journey, Super Learners’ questions are resolved more quickly by our instructors.
- Will my question be answered if I am not a Super Learner?
Yes. We answer all questions with equal care. We hope to grow a community of data scientists where even if we are not fast enough to be the first who have answered a question, somebody else who knows will have done so. But, ultimately, no question will be left without an answer.
- Can I become a Super Learner?
You can. If data science is the direction in which you want to develop professionally but you’re lacking the skillset, you can start developing your expertise with the 365 Data Science program.
The program includes 17 topics (70+ hours of video lessons and 500+ exercises) and covers data science fundamentals like statistics and mathematics; programming for data science with Python, R, and SQL; and machine and deep learning. The training also provides advanced specialization courses into domains like credit risk modeling or time series analysis.
To learn more about the program, please visit this page: https://365datascience.com/complete-data-science-training/
7. Who are the 365 Team
The Team consists of the instructors who created all courses in the 365 Data Science Program. They answer the questions to their areas of expertise. You can expect Vik to answer statistics and time series-related questions. Martin addresses SQL queries, while Simona will jump in R. Iliya and Eli will help with Python and machine and deep learning questions… and so on.
To “meet” the instructor team, please visit the About Us section of the site.
8. Rudeness and hostility will not be tolerated
This is a community of learners and there is absolutely no need for rude conduct. Insulting members, homophobia and racism are not tolerated.
Remember, we are all here to develop one skill or another; a hostile environment will not help to facilitate this.
Enjoy the HUB