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Self-paced e-learning materials

Understanding Algorithms

Understanding Algorithms
Audience Growth & Community Building 4 skill levels

Algorithms decide who sees your content, but they respond to people's behaviour. Understand the signals platforms use and how to create with them in mind.

Starting from 185 credits Choose your skill level
  • 4 skill levels
  • Category: Audience Growth & Community Building
  • Each level is unlocked separately with credits
  • Access information typically arrives within 24 hours of confirmed payment
  • If nothing has arrived after 72 hours, please contact us

Levels are unlocked with credits from your account balance. You can buy more credits whenever you need them.

About this e-learning material

Every major platform uses recommendation systems to decide what appears in feeds and discovery pages. These systems change often, but they are built on common signals such as watch time, interactions and relevance, which creators can learn to work with.

What this material covers
• How recommendation systems choose what to show
• What completion rates, saves, shares and replies tell a platform
• Differences between feeds, discovery pages and search
• Separating reliable guidance from rumours and myths
• Adapting when a platform changes how it ranks content

Who it is for
Creators who want to understand why some posts reach more people, and marketers planning content across platforms.

Compare the ideas with your own analytics to see which signals matter most for your audience.

Choose your skill level

Each level is unlocked separately with credits

  • Beginner

    185 credits

    • What you will learn

      You will learn the basic idea of recommendation systems, the difference between feeds, discovery pages and search, and common signals such as watch time, likes and comments. Simple examples link these signals to everyday posting choices.

    • Purpose of this level

      Written for creators who hear the word algorithm often but are not sure what it actually does. It explains in plain terms how platforms decide which posts to show and why reach can change from one post to the next.

    • Expected outcome

      By the end of this level, you should be able to explain in your own words how a recommendation system works and name the main signals it uses. You will also be able to read basic analytics with more understanding.

  • Intermediate

    350 credits

    • What you will learn

      You will study what completion rates, saves, shares and replies suggest to a platform, and how hooks, pacing and calls to action can influence them. You will also practise telling reliable guidance apart from rumours and myths.

    • Purpose of this level

      For creators who understand the basics and now want to use that knowledge in their content decisions. It focuses on connecting platform signals with the way individual posts are planned, opened and structured.

    • Expected outcome

      After this level, you should be able to adjust your content structure to support the signals that matter on your main platform. You will be better prepared to test changes and judge advice critically rather than following every rumour.

  • Advanced

    745 credits

    • What you will learn

      You will compare how major platforms rank content, run structured tests on formats and timing and interpret results over longer periods. The material also covers responding when a platform changes its ranking approach and reach suddenly drops.

    • Purpose of this level

      Intended for experienced creators and marketers working across several platforms where ranking systems behave differently. It covers the challenge of adapting one content plan to each system without losing consistency.

    • Expected outcome

      By the end of this level, you should be able to plan platform-specific versions of your content based on how each system works. You will be ready to design simple experiments and respond calmly to ranking changes.

  • Expert

    960 credits

    • What you will learn

      You will examine how to separate lasting audience value from short-term ranking tactics, build testing and reporting frameworks and brief others on platform changes. It also explores the trade-offs of relying heavily on one platform's recommendations.

    • Purpose of this level

      Created for strategists, agency leads and senior creators who make content decisions for accounts or teams. It looks at building strategies that remain sound even as recommendation systems keep changing.

    • Expected outcome

      After this level, you should be able to set an algorithm-aware content strategy that does not depend on chasing every update. You will be better prepared to guide teams and clients through ranking changes with clear, evidence-based reasoning.