Aladia Discovery Scraper

The Aladia Discovery Scraper is a powerful Apify Actor designed to extract detailed course information from the Aladia platform. It enables users to search for courses by keywords and retrieve comprehensive data on titles, descriptions, instructors, categories, and more. This tool is ideal for educators, researchers, and businesses seeking to analyze educational content trends and opportunities.

Features

• Comprehensive Data Extraction: Scrapes rich course details including metadata, categories, skills, requirements, and performance metrics.
• Flexible Search: Supports keyword-based queries to find relevant courses efficiently.
• Customizable Limits: Allows setting maximum items to scrape, with options for unlimited extraction.
• High Reliability: Built on Apify's robust infrastructure for consistent and error-free scraping.
• Structured Output: Delivers clean JSON data ready for integration into databases, analytics tools, or reports.
• Fast Performance: Optimized for speed, handling large volumes of data without compromising quality.
• Ethical Scraping: Respects website terms and avoids overloading servers, ensuring sustainable use.

Input Parameters

Parameter	Type	Required	Description	Example
searchQuery	string	Yes	Keyword to search for courses by title (e.g., 'ai', 'machine learning', 'python').	"machine learning"
maxItems	integer	No	Maximum number of courses to scrape. Set to 0 for unlimited.	50

Example Usage

Input JSON

{
  "searchQuery": "ai",
  "maxItems": 100
}

Output JSON

[
  {
    "id": "6847f668e3793dcbae597791",
    "title": "Exploring Fairness in Machine Learning",
    "description": "This course introduces students to the ethical dimensions of machine learning (ML), with a particular focus on applications in international development.\nAttribution: This course is adapted from Exploring Fairness in Machine Learning for International Development, originally developed by Dr. Richard Fletcher, Prof. Daniel Frey, Dr. Mike Teodorescu, Amit Gandhi, and Audace Nakeshimana, and published by MIT OpenCourseWare under a Creative Commons BY-NC-SA 4.0 License.",
    "type": "on-demand",
    "status": "published",
    "visibility": "public",
    "color": "#6F1D1B",
    "language": "en",
    "spaceId": "6847162b0af49caf63a61ccc",
    "productId": "684928a5e3793dcbae5c6f9c",
    "createdAt": "Tue Jun 10 2025 09:10:00 GMT+0000 (Coordinated Universal Time)",
    "updatedAt": "Wed Feb 25 2026 06:52:02 GMT+0000 (Coordinated Universal Time)",
    "publishedDate": "2025-06-11T06:57:19.310Z",
    "owner": {
      "id": "6847155b0af49caf63a61b0d",
      "name": "Rambod Rahmani",
      "email": "rambodrahmani@aladia.io",
      "followers": 400,
      "bio": "Senior Software, AI & Data Engineer 🚀🎓"
    },
    "categories": [
      {
        "id": "67163a6d7e90861c1982cd54",
        "name": "Artificial Intelligence"
      }
    ],
    "subCategories": [
      {
        "id": "67165ae77e90861c19847251",
        "name": "AI Ethics"
      },
      {
        "id": "67165ae77e90861c1984724a",
        "name": "Machine Learning"
      },
      {
        "id": "67165ae77e90861c1984724b",
        "name": "Natural Language Processing"
      }
    ],
    "skills": [
      "Computer Programming",
      "Python Programming",
      "Algorithms",
      "Machine Learning Algorithms",
      "Applied Machine Learning"
    ],
    "chapterCount": 5,
    "chaptersDuration": 7271,
    "lectureCount": 14,
    "requirements": [
      "Basic knowledge of machine learning principles, including familiarity with algorithms, training data, and supervised learning.",
      "A strong interest in ethical and social issues, particularly in the context of technology and development.",
      "Access to a computer with internet connectivity to watch video lectures and download resources.",
      "English reading and listening proficiency, as course materials are presented in English.",
      "A willingness to engage in reflective analysis, including participation in case-based and scenario-based learning activities."
    ],
    "objectives": [
      "Explain the ethical implications of deploying machine learning systems, especially in low-resource or development-focused contexts.",
      "Identify common sources of bias in machine learning algorithms and datasets.",
      "Analyze real-world case studies to assess how fairness, equity, and accountability are addressed — or overlooked — in ML deployments.",
      "Apply a structured pedagogical framework to critically evaluate and teach fairness concepts in ML.",
      "Formulate strategies to mitigate ethical risks, such as bias and misuse, when planning or implementing ML-based interventions.",
      "These goals are derived from and adapted based on course materials from MIT OpenCourseWare, RES.EC-001, Spring 2020, under the CC BY-NC-SA 4.0 license."
    ],
    "purchases": 355,
    "attendees": 356,
    "attendancePercent": 100,
    "globalRating": 5,
    "totalReviews": 2,
    "paymentModel": "free",
    "price": 0,
    "thumbnailFileId": "68484351e3793dcbae5bd1cc",
    "trailerFileId": "684846dbe3793dcbae5be2cd",
    "trailerDuration": 111
  }
]

Use Cases

• Market Research: Analyze trending courses in AI and tech to identify market gaps.
• Competitive Intelligence: Monitor competitors' course offerings and pricing strategies.
• Content Aggregation: Build databases of educational resources for platforms or apps.
• Academic Research: Study course structures, skills taught, and instructor profiles.
• Business Automation: Automate data collection for reports on e-learning trends.
• Personal Learning: Discover courses matching specific interests like "python" or "machine learning".

Installation and Usage

1. Search for "Aladia Discovery Scraper" in the Apify Store.
2. Click "Try for free" or "Run".
3. Configure input parameters.
4. Click "Start" to begin extraction.
5. Monitor progress in the log.
6. Export results in your preferred format (JSON, CSV, Excel).

Output Format

The Actor outputs a JSON array of course objects. Each object includes fields like id, title, description, owner (with instructor details), categories, skills, requirements, objectives, purchases, globalRating, and more. This structured data allows easy parsing for analysis, with timestamps in UTC and ratings on a 5-point scale.

Support

For custom/simplified outputs or bug reports, please contact:

• Email: support@getdataforme.com
• Subject line: "custom support"
• Contact form: https://getdataforme.com/contact/

We're here to help you get the most out of this Actor!

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Unlock comprehensive course data from Aladia with our scraper! Extract titles, descriptions, instructors, categories, skills, and metrics effortlessly. Perfect for market research, competitive analysis, and content aggregation. Start scraping today—try it free on Apify! (148 characters)