Joining Data Science Community

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Joining Data Science Community by Mind Map: Joining Data Science Community

1. Intro

1.1. Public work has 2X return on investment

1.2. Benefits

1.2.1. Gaining skills

1.2.2. Growing network

1.2.3. Gaining opportunities

1.2.4. Giving back

2. Growing your portfolio

2.1. More blog posts

2.2. More projects

2.2.1. Projects can be much harder than blog posts to keep up with

2.2.2. Still, good to do a side project occasionally

3. Attending conferences

3.1. Look for scholarships or discount codes

3.2. Giving a talk also lowers the expense

3.3. Networking opportunity

3.4. Axes to consider

3.4.1. Academic or industry oriented? Recommend latter

3.4.2. Size: recommend starting with a small to medium-size conference

3.4.3. Hiring companies

3.4.4. Level of talks

3.4.5. Diversity and inclusivity

3.4.6. Specialty

3.5. Look for reviews before you commit

3.6. How to pitch to your manager

3.6.1. Recruiting: you put your company's name out there

3.6.2. Knowledge: talks immediately applicable to solving your problems

3.7. Dealing with social anxiety

3.7.1. Try talking to people a few minutes before a talk If it's bad, it'll anyway end soon!

3.7.2. Look for people standing in a Pac-Man shape: a circle with an opening

3.7.3. Important: you shouldn't be made to feel like an impostor

3.7.4. Totally normal to take personal time during the conference

4. Giving talks

4.1. Actually a great strategy for an introvert

4.1.1. After talk, people will come up to pay compliments, ask follow-up questions, or just introduce themselves

4.2. Keys to a good talk

4.2.1. Entertain people

4.2.2. Motivate people

4.3. Look for conferences that have calls for proposals

4.4. A good abstract has a first sentence that's a hook: draws the reader in to learn more

4.5. You don't need to be an expert: people who've just learned something are often the best teachers

4.6. First speaking gigs are the hardest to get, then there's a snowball effect

5. Preparing for talks

5.1. Spend a lot of time preparing

5.2. Easy to underestimate prep time

5.3. Not preparing is bad

5.3.1. Disrespectful of your audience

5.3.2. Not showcasing you at your best

5.4. Practice giving talk to a live person

5.4.1. Not just reading the slides to yourself

5.5. Time yourself giving the talk

5.5.1. Add some extra slides

5.5.2. Worst outcome is that your talk is way too long You will get cut off, or disrupt next speaker

5.6. Highly recommend reusing talks

5.6.1. Because of all the prep that goes into any talk

5.7. The day of the talk, gather your supporters

6. Contributing to open source

6.1. Mental model: imagine OSS projects are like throwing a giant dinner party

6.2. You don't want to be responsible for the main course yet

6.3. But lots of jobs need to be done!

6.3.1. Set the table

6.3.2. Make sure everyone has water

6.3.3. Put the dishes away afterward

6.4. Don't jump right in and start rewriting things or submitting a new function

6.4.1. Watch the repo for a while to understand the flow

6.5. Start by making an issue sharing what you'd like to add or change

6.5.1. Get feedback from maintainers before you've done a lot of work

6.6. You'll learn a lot of best practices that you can apply to your own work

7. Recognizing and avoiding burnout

7.1. Symptoms

7.1.1. Feelings of energy depletion or exhaustion

7.1.2. Increased mental distance from one's job

7.1.3. Feelings of negativism or cynicism related to one's job

7.1.4. Reduced professional productivity

7.2. If you feel like you're burning out

7.2.1. Start by asking yourself whether there are ways to cut back

7.2.2. You can add a lot of stress by trying to keep up with people

7.2.3. Social media is someone else's highlight reel

8. Making your own package or library

8.1. Allows you to store functions in one place

8.2. Easy to share and enforce best practices

8.3. Make sure your underlying work has been read by someone you trust

8.3.1. Users won't look under the hood!

8.3.2. If you tell them it's a Ferrari, it shouldn't be a golf cart half the time