Content Guidelines for Slides

Each live session should begin with a 10 to 15 minute presentation with slides introducing the topic, technologies and other relevant information and end with a 5 to 10 minute discussion with slides discussing key takeaways.

Style guidelines

To keep things consistent across all our live sessions and provide the best possible user experience, here are a few guidelines to adhere to when formulating your slides. Use the link below to access the provided slide template.

Fonts and colors:

  • Make sure to use the Lato font.
  • To simulate the DataCamp blue inline formatting - highlight your functions, methods, packages and other relevant objects with the custom hex color #ebf4f7 and set your text color to #595959
  • Slide titles should be sentence case (only the first letter of the sentence is capitalized)

Images and graphics:

  • A great source of vector images to use is thenounproject, here's a loom walking you through copying images without a subscription.
  • If you want to create custom graphics, try to adhere to this set of primary colors when creating graphics (examples are included in the template above):
  • Gradient Green
  • Dark Blue: #2f5496ff
  • DataCamp Blue: #33aaccff

Session Agenda

Introductory Presentation (10-15 mins)

This presentation is designed to introduce students to the topic being taught, as well as set expectations about the flow of the session. Ideally, an introductory presentation would go as follows:

  1. Instructor Introduction led by a DataCamp TA (1-2 minutes)
  2. A 5-7 minute introduction on today's topic. This is an excellent opportunity to capture our learners' attention and incentivize them to stick around for the entire session. Here's a video on writing killer presentation introductions.
  3. Introduction of the dataset and problem we'll be working on (1-2 minutes)
  4. Brief explanation of the packages and technologies used (1-2 minutes)
  5. Session outline and what to expect, this is a great time to remind students there will be Q&A sessions throughout the live training (1-2 minutes)

Here's an example of how this flows fit from a previous live training done internally on Data Visualization in Python (from 0:00 to 8:03):

  1. Instructor Introduction led by a DataCamp TA
  2. Introduction on today's topic:
  • Here's where data science provides value for organizations today
  • An example of this value, is creating dashboards
  • A key component of dashboards is data visualization and that's what we will be learning today!

3. Introduction to HR attrition dataset and the problem we'll be working on (creating report investigating churn)

4. Brief explanation of the packages and technologies used (including Google Colabs and its requirements)

5. Session outline and what to expect

6. Go to session 🎉

Live Training - Hands on Coding Activity (1.5-2 hours)

See this article for more information on how to set up your coding activity.

Closing Presentation (5-10 mins)

This presentation is designed to summarize the learning objectives of the session, impart some wisdom, and point students in the right direction to keep going in their learning journey. Ideally, it should go as follows:

  1. Ending notes recapping what we learned
  2. An expert insight that you'd like to impart students. This could be anything from something you wished you were taught about the topic when you first started out, or an expert tip on how to keep digging and reaching the next level in your data science work 💪
  3. A call to action pointing students in the right direction - this could be your DataCamp course, other relevant DataCamp material that could help (blog post, webinars, white papers etc...)
  4. Optional: A take-home exercise where you provide learners with a detailed problem description, as well as your and DataCamp's social media handles for them to reach out to you with their results and code, with the promise of entries getting retweets from you and DataCamp. This is a great way to build your brand and engage with students further after the session.

Here's an example of how this flows fit from a previous live training done internally on Data Visualization in Python (from 2:36:00 to end of session):

  1. Brief summary of the session
  2. Data visualization packages tend to be verbose and rote memorization won't work - let's aim to understand the basics of how plots work and we can always rely on research to customize our plots!
  3. Call to action on DataCamp's business offering
  4. Take home exercise

Use the template provided below to structure your Live Training Session Slidedeck

Make a copy to your own drive before editing. Remember to set sharing options to "anyone with the link can view".

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