인프런 커뮤니티 질문&답변

Inflearn has emerged as a powerhouse for self-paced tech education in South Korea, offering thousands of courses in programming, design, data science, and more. But while the platform is robust and content-rich, advanced learners often want a more personalized view of their progress—something beyond a static course history or completion badge. That’s where building a custom learning dashboard comes in.

Creating your own dashboard not only gives you the ability to track your course progress and visualize goals, but also pushes your skills in backend logic, API consumption, data visualization, and automation. In this post, we’ll explore how to design and implement a learning dashboard that integrates with Inflearn’s platform and adapts to your personal study habits.

Why a Custom Learning Dashboard Matters

Traditional learning platforms offer a generalized view of your progress. They tell you what percentage of a course you’ve completed, show a checklist of modules, and send you reminders. But they rarely adapt to your unique goals or learning style.

Let’s say you’re someone preparing for a transition into data science. You may be enrolled in 6–8 courses across Python, machine learning, SQL, and career prep. While Inflearn’s native UI does provide basic tracking, it doesn’t allow you to visualize how your time is distributed across subjects or how many hours you’ve logged toward a goal like “50 hours of coding per month.”

A custom dashboard gives you complete control. You can pull your data into a personal dashboard app—built using frameworks like Flask, Node.js, or even Google Sheets and App Script—and start tracking:

• Hours watched per course
  
  

• Weekly progress toward learning goals
  
  

• Course completion rate across categories
  
  

• Skills gained per quarter
  
  

• Trends in what topics you’re focusing on over time
  
  

You’re no longer bound by what the platform shows you. Instead, your data becomes a dynamic asset for reflection, improvement, and even resume building.

Getting Started: What You Need and How to Integrate

Before jumping into code, you need a few foundational elements in place. While Inflearn doesn’t currently offer a public REST API like some platforms, you can still collect data using web scraping techniques or, where permitted, internal API calls triggered during regular course access.

Start by identifying what information matters to you. For most learners, this includes:

• List of enrolled courses
  
  

• Completion percentage
  
  

• Date of last activity
  
  

• Time spent watching videos
  
  

You can use tools like Python’s requests and BeautifulSoup, or browser-based inspection tools to understand how Inflearn loads this data. Many modern learning platforms load user data using JSON endpoints, even if they don’t expose them publicly. You’ll typically find these calls in your browser’s Network tab.

Once you locate the data source, you can automate fetching it every day or week and feed it into a storage system—whether that's a simple CSV, a PostgreSQL database, or even a Google Sheet.

Now comes the part that feels like leveling up your gameplay in Dota 2 live odds—you start seeing patterns, making predictions, and customizing your interface to react to your moves. The dashboard evolves from a passive display into an intelligent guide.

Building the Dashboard: Frontend and Backend Workflow

After collecting the data, the next step is visualizing it. A good dashboard should not only report facts but also offer clarity. This means using charts, progress bars, and even calendar heatmaps to show learning activities.

On the backend, a Flask or Node.js server can process your data daily. It can parse new watch time logs, calculate rolling averages, and flag gaps or inconsistencies in your study pattern.

On the front end, tools like React or Vue.js allow you to build a responsive interface. If you prefer a faster prototype, consider using Google Data Studio or Tableau Public to connect your dataset and design charts quickly.

Important modules to build in your dashboard include:

• Today’s Progress: How many minutes/hours studied today
  
  

• Streak Tracker: Days of continuous study
  
  

• Category Completion: Percent of courses completed by domain (Frontend, AI, Design, etc.)
  
  

• Weekly Trends: Hours studied each day of the week
  
  

• Course Watch Breakdown: A pie chart showing time spent per course
  
  

This type of layout helps you identify patterns—are you spending too much time revisiting one subject? Are you losing momentum mid-week? Are you completing entire sections or hopping around randomly?

Adding Intelligence: Predicting and Recommending

Once your dashboard is live and tracking your progress, the next step is adding intelligence. Imagine you’ve logged 100 hours of coursework in 3 months. Using basic ML models or rule-based logic, your dashboard could estimate:

• Which courses you’re likely to finish next
  
  

• Your projected finish dates for enrolled courses
  
  

• Time needed to reach your next skill milestone
  
  

• Gaps in your learning that aren’t being addressed by current enrollments
  
  

You can also use simple keyword tagging to organize your course library. For instance, if you’re enrolled in “Intro to Python” and “Data Analysis with Pandas,” both could fall under a broader “Data Science” tag. Your dashboard could then show your mastery curve per tag or suggest content to reinforce weak areas.

By bringing structure and foresight to your learning, the dashboard becomes more than just a digital mirror—it becomes a learning assistant.

Expanding Use Cases Beyond Personal Learning

While this blog focuses on individuals, the concept of a custom Inflearn dashboard can scale to teams and classrooms. Teachers or boot camp instructors can monitor class engagement by syncing multiple students’ dashboards. Employers can also encourage professional development by offering access to dashboards where employees track how many hours they’ve spent upskilling through Inflearn each quarter.

Similarly, a public leaderboard or badge system can be layered into the UI if you want to gamify progress with friends or colleagues.

Beyond tech, this kind of tracking model can apply to any continuous learning initiative. Whether it’s language learning, UX design, or marketing analytics, being able to audit your own growth in a data-driven way changes how seriously you approach improvement.

Conclusion

Building a custom Inflearn learning dashboard is more than a cool side project—it’s a meaningful way to take charge of your personal growth. It turns passive consumption into active planning. You learn to treat your own learning data the way a company would handle KPIs—monitoring, analyzing, and iterating.

With the right tools, you don’t need to wait for the platform to tell you how you’re doing. You can build your own story of progress—visually, intelligently, and creatively. And in doing so, you move from being just a student to becoming the architect of your learning journey.