Each DataCamp course has an associated GitHub repository (repo) that houses all course content. Central to this repository is the README file, which serves as the course spec—a blueprint used during the course design phase and as a reference throughout development. Each section of the spec sets clear expectations for the steps involved in creating the course. Please note that video scripts are capped at a 500-word limit.
Step 1: Brainstorming
The brainstorming phase allows you to explore all potential directions for your course without committing to every idea. It’s a creative process to align your vision with DataCamp’s curriculum goals.
Define the key learning objectives for your course. This ensures your vision aligns with DataCamp’s goals and maps to relevant certifications or skills when applicable.
Identify any technical terms or jargon that require explanation to make the content accessible and learner-friendly.
Consider creative ways to simplify complex ideas using analogies or heuristics that resonate with your audience.
Anticipate common mistakes or misconceptions learners might have about the topic and plan strategies to address them.
E. What datasets or resources will you use?
If your course involves data or resources, outline them here:
Use one dataset per chapter or a single engaging dataset for the entire course.
Avoid datasets previously used in other Cloud courses.
Ensure datasets are under 10MB to optimize virtual machine performance.
Refer to this guide for tips on finding datasets.
Step 2: Define the Target Audience
A. Describe the target audience.
Who will benefit from this course? Consider:
Professional backgrounds (e.g., data scientists, developers).
Relevant industries or sectors.
Learners’ goals or motivations.
B. What level of expertise is required?
Specify the level of experience learners should have before starting, such as:
Beginner, intermediate, or advanced skills.
Prerequisite knowledge or technical abilities.
Step 3: Create the Course Outline
Define each lesson in your course, including:
Learning Outcomes: What will the video teach?
Exercise Plan: What are the three associated exercises?
Assessment Strategy: How will understanding be tested?
Exercise Types: Which types (e.g., multiple choice, cloud exercises) will you use?
For certification-aligned courses (e.g., AWS or Azure), map content to certification objectives for relevance and coverage.
Step 4: Create a Conceptual Video
In this step, you’ll work in the Teach editor to create your first conceptual video. This step allows you to:
Understand DataCamp’s video creation process.
Showcase your approach to teaching relevant concepts.
Receive feedback from your Curriculum Manager (CM) to refine your content and presentation style.
The conceptual video provides a foundation for creating engaging and effective videos in subsequent lessons.
Step 5: Build an Interactive Cloud Exercise
In this step, you’ll work in the Teach editor to create your first interactive cloud exercise. This step allows you to:
Familiarize yourself with building multi-step exercises in the Teach editor.
Apply best practices for designing cloud exercises.
Receive feedback from your Curriculum Manager (CM) to refine the exercise content and structure.
Your first cloud exercise sets the tone for developing hands-on, practical exercises that engage learners effectively.
Step 6: Revisit the Course Outline
After completing a video and an exercise, revisit your outline to refine the scope and flow of the course. This ensures it aligns with the course’s objectives and your growing understanding of the process.
Step 7: List Course Pre-Requisites
Based on your course outline, identify prerequisite knowledge and reference relevant DataCamp courses that learners should complete beforehand.