extract_skills_from_resume.ipynb

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      "authorship_tag": "ABX9TyOI0lMtR5toicw/M4ASHQ3f",
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        "<a href=\"https://colab.research.google.com/github/Ironsoldier353/freelance-clone/blob/main/extract_skills_from_resume.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "code",
      "source": [
        "!pip install PyPDF2 spacy"
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      "cell_type": "code",
      "source": [
        "import PyPDF2\n",
        "import spacy\n",
        "import re\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.feature_extraction.text import TfidfVectorizer\n",
        "from sklearn.metrics.pairwise import cosine_similarity\n",
        "\n",
        "# Load spaCy's pre-trained English model\n",
        "nlp = spacy.load(\"en_core_web_sm\")\n",
        "\n",
        "# Predefined list of required skills\n",
        "required_skills = [\n",
        "    \"Python\", \"Java\", \"JavaScript\", \"C++\", \"SQL\", \"Django\", \"Flask\",\n",
        "    \"React\", \"Machine Learning\", \"Data Analysis\", \"R\", \"MATLAB\",\n",
        "    \"Sphinx\", \"LaTeX\", \"Mathematica\", \"Maple\", \"GIT\", \"CVS\", \"HTCondor\", \"Data Mining\"\n",
        "]\n",
        "\n",
        "# Example courses\n",
        "courses = {\n",
        "    \"Python\": \"Complete Python Bootcamp by Udemy\",\n",
        "    \"Java\": \"Java Programming and Software Engineering Fundamentals by Coursera\",\n",
        "    \"JavaScript\": \"JavaScript: Understanding the Weird Parts by Udemy\",\n",
        "    \"C++\": \"Beginning C++ Programming by Udemy\",\n",
        "    \"SQL\": \"The Complete SQL Bootcamp by Udemy\",\n",
        "    \"Django\": \"Django for Everybody by Coursera\",\n",
        "    \"Flask\": \"Flask: Full Stack Web Development by Udemy\",\n",
        "    \"React\": \"React - The Complete Guide by Udemy\",\n",
        "    \"Machine Learning\": \"Machine Learning by Stanford University on Coursera\",\n",
        "    \"Data Analysis\": \"Data Analysis with Python by Coursera\",\n",
        "    \"HTML\": \"HTML and CSS for Beginners by Udemy\",\n",
        "    \"CSS\": \"Advanced CSS and Sass by Udemy\",\n",
        "    \"Node.js\": \"The Complete Node.js Developer Course by Udemy\",\n",
        "    \"Angular\": \"Angular - The Complete Guide by Udemy\",\n",
        "    \"Ruby\": \"The Complete Ruby on Rails Developer Course by Udemy\",\n",
        "    \"Ruby on Rails\": \"Ruby on Rails Web Development by Codecademy\",\n",
        "    \"PHP\": \"PHP for Beginners - Become a PHP Master by Udemy\",\n",
        "    \"Laravel\": \"Laravel - The PHP Framework for Web Artisans by Udemy\",\n",
        "    \"Go\": \"Go Programming Language: Beginner to Advanced by Udemy\",\n",
        "    \"Swift\": \"iOS App Development with Swift by Udacity\",\n",
        "    \"Kotlin\": \"Kotlin for Android Developers by Udacity\",\n",
        "    \"Android Development\": \"The Complete Android App Developer Bootcamp by Udemy\",\n",
        "    \"iOS Development\": \"iOS App Development with Swift by Udacity\",\n",
        "    \"C#\": \"C# Basics for Beginners by Udemy\",\n",
        "    \"ASP.NET\": \"ASP.NET Core - Beginner to Advanced by Udemy\",\n",
        "    \"R\": \"R Programming A-Z by Udemy\",\n",
        "    \"Scala\": \"Functional Programming Principles in Scala by Coursera\",\n",
        "    \"Haskell\": \"Introduction to Functional Programming by Coursera\",\n",
        "    \"Perl\": \"Master Perl Programming by Udemy\",\n",
        "    \"Shell Scripting\": \"Linux Shell Scripting: A Project-Based Approach by Udemy\",\n",
        "    \"PowerShell\": \"Mastering Windows PowerShell by Udemy\",\n",
        "    \"MATLAB\": \"MATLAB for Engineers by Coursera\",\n",
        "    \"TensorFlow\": \"Deep Learning with TensorFlow by Coursera\",\n",
        "    \"Keras\": \"Deep Learning with Python and Keras by Udemy\",\n",
        "    \"PyTorch\": \"PyTorch for Deep Learning by Udemy\",\n",
        "    \"Artificial Intelligence\": \"AI For Everyone by Coursera\",\n",
        "    \"Deep Learning\": \"Deep Learning Specialization by Coursera\",\n",
        "    \"Natural Language Processing\": \"Natural Language Processing with Python by Udemy\",\n",
        "    \"Computer Vision\": \"Computer Vision A-Z by Udemy\",\n",
        "    \"Blockchain\": \"Blockchain and Cryptocurrency Explained by Udemy\",\n",
        "    \"Bitcoin\": \"Bitcoin and Cryptocurrency Technologies by Coursera\",\n",
        "    \"Ethereum\": \"Ethereum and Solidity: The Complete Developer's Guide by Udemy\",\n",
        "    \"Smart Contracts\": \"Smart Contracts - Ethereum Blockchain by Udemy\",\n",
        "    \"DevOps\": \"DevOps: The Complete Guide by Udemy\",\n",
        "    \"Docker\": \"Docker Mastery: The Complete Toolset by Udemy\",\n",
        "    \"Kubernetes\": \"Kubernetes for Developers by Coursera\",\n",
        "    \"AWS\": \"AWS Certified Solutions Architect - Associate by Udemy\",\n",
        "    \"Azure\": \"Microsoft Azure Fundamentals by Udemy\",\n",
        "    \"Google Cloud\": \"Google Cloud Platform for Beginners by Coursera\",\n",
        "    \"Linux\": \"Linux Administration Bootcamp by Udemy\",\n",
        "    \"Network Security\": \"The Complete Cyber Security Course by Udemy\",\n",
        "    \"Ethical Hacking\": \"The Complete Ethical Hacking Course by Udemy\",\n",
        "    \"Penetration Testing\": \"Learn Penetration Testing from Scratch by Udemy\",\n",
        "    \"Cryptography\": \"Cryptography I by Coursera\",\n",
        "    \"Information Security\": \"Introduction to Information Security by Coursera\",\n",
        "    \"Agile\": \"Agile Project Management by Udemy\",\n",
        "    \"Scrum\": \"Scrum Master Certification by Udemy\",\n",
        "    \"Project Management\": \"Project Management Essentials by Udemy\",\n",
        "    \"Git\": \"Git & GitHub Masterclass by Udemy\",\n",
        "    \"GitHub\": \"Version Control with Git by Coursera\",\n",
        "    \"Jenkins\": \"Jenkins, From Zero to Hero by Udemy\",\n",
        "    \"Terraform\": \"Terraform for Beginners by Udemy\",\n",
        "    \"Ansible\": \"Ansible for the Absolute Beginner by Udemy\",\n",
        "    \"Puppet\": \"Puppet for DevOps - Beginner to Expert by Udemy\",\n",
        "    \"Chef\": \"Chef for DevOps Engineers by Udemy\",\n",
        "    \"Cybersecurity\": \"Introduction to Cyber Security by Coursera\",\n",
        "    \"Data Science\": \"Data Science Specialization by Coursera\",\n",
        "    \"Big Data\": \"Big Data Specialization by Coursera\",\n",
        "    \"Hadoop\": \"The Ultimate Hands-On Hadoop - Tame your Big Data by Udemy\",\n",
        "    \"Spark\": \"Apache Spark with Scala - Hands On with Big Data by Udemy\",\n",
        "    \"Kafka\": \"Apache Kafka Series - Learn Apache Kafka for Beginners by Udemy\",\n",
        "    \"MongoDB\": \"MongoDB - The Complete Developer's Guide by Udemy\",\n",
        "    \"Redis\": \"Mastering Redis by Udemy\",\n",
        "    \"Elasticsearch\": \"Elasticsearch 7 and the Elastic Stack by Udemy\",\n",
        "    \"Cassandra\": \"Apache Cassandra: Hands-On Training by Udemy\",\n",
        "    \"NoSQL\": \"NoSQL Databases by Coursera\",\n",
        "    \"MySQL\": \"MySQL for Beginners by Udemy\",\n",
        "    \"PostgreSQL\": \"The Complete PostgreSQL Bootcamp by Udemy\",\n",
        "    \"Oracle\": \"Oracle SQL Performance Tuning Masterclass by Udemy\",\n",
        "    \"SQL Server\": \"Microsoft SQL Server for Beginners by Udemy\",\n",
        "    \"Tableau\": \"Tableau 2020 A-Z by Udemy\",\n",
        "    \"Power BI\": \"Microsoft Power BI - A Complete Introduction by Udemy\",\n",
        "    \"Excel\": \"Excel Skills for Business by Coursera\",\n",
        "    \"Business Intelligence\": \"Business Intelligence Concepts, Tools, and Applications by Coursera\",\n",
        "    \"Data Visualization\": \"Data Visualization with Tableau by Udemy\",\n",
        "    \"Statistics\": \"Statistics for Data Science and Business Analysis by Udemy\",\n",
        "    \"Probability\": \"Introduction to Probability by Coursera\",\n",
        "    \"Linear Algebra\": \"Linear Algebra for Data Science in Python by Udemy\",\n",
        "    \"Calculus\": \"Mathematics for Machine Learning by Coursera\",\n",
        "    \"Algorithms\": \"Algorithms Specialization by Coursera\",\n",
        "    \"Data Structures\": \"Data Structures and Algorithms by Udemy\",\n",
        "    \"Operating Systems\": \"Operating Systems: Three Easy Pieces by Coursera\",\n",
        "    \"Computer Networks\": \"Computer Networking - Principles, Protocols and Practice by Coursera\",\n",
        "    \"Software Architecture\": \"Software Architecture for Developers by Udemy\",\n",
        "    \"System Design\": \"Grokking the System Design Interview by Educative\",\n",
        "    \"Distributed Systems\": \"Designing Data-Intensive Applications by Coursera\",\n",
        "    \"Microservices\": \"Microservices with Spring Boot and Spring Cloud by Udemy\",\n",
        "    \"Spring Boot\": \"Spring Boot Microservices with Spring Cloud by Udemy\",\n",
        "    \"Hibernate\": \"Hibernate and Spring Data JPA by Udemy\",\n",
        "    \"Web Development\": \"The Web Developer Bootcamp by Udemy\",\n",
        "    \"Frontend Development\": \"The Complete Front-End Web Developer Bootcamp by Udemy\",\n",
        "    \"Backend Development\": \"The Complete Back-End Web Developer Bootcamp by Udemy\",\n",
        "    \"Full Stack Development\": \"The Complete Full-Stack JavaScript Course by Udemy\",\n",
        "    \"UI/UX Design\": \"UI/UX Design Specialization by Coursera\",\n",
        "    \"Graphic Design\": \"Graphic Design Bootcamp by Udemy\",\n",
        "    \"Photoshop\": \"Adobe Photoshop CC - Essentials Training Course by Udemy\",\n",
        "    \"Illustrator\": \"Adobe Illustrator CC - Essentials Training Course by Udemy\",\n",
        "    \"3D Modeling\": \"3D Modeling in Blender by Udemy\",\n",
        "    \"Game Development\": \"Complete C# Unity Developer 2D by Udemy\",\n",
        "    \"Virtual Reality\": \"Virtual Reality Specialization by Coursera\",\n",
        "    \"Augmented Reality\": \"Augmented Reality and ARCore by Coursera\",\n",
        "    \"Mobile App Development\": \"The Complete Mobile App Developer Bootcamp by Udemy\",\n",
        "    \"Cross-Platform Development\": \"Flutter & Dart - The Complete Guide by Udemy\",\n",
        "    \"React Native\": \"React Native - The Practical Guide by Udemy\",\n",
        "    \"Xamarin\": \"Xamarin Forms: Build Native Cross-platform Apps with C# by Udemy\",\n",
        "    \"Unity\": \"Complete C# Unity Developer 3D by Udemy\",\n",
        "    \"Unreal Engine\": \"Unreal Engine C++ Developer by Udemy\",\n",
        "    \"VFX\": \"VFX for Beginners with After Effects by Udemy\",\n",
        "    \"Animation\": \"The Beginner's Guide to Animation in Blender by Udemy\",\n",
        "    \"Music Production\": \"Music Production in Logic Pro X - The Complete Guide by Udemy\",\n",
        "    \"Sound Design\": \"Ultimate Sound Design Complete: Mastering Sound Design by Udemy\",\n",
        "    \"Video Editing\": \"Video Editing with Adobe Premiere Pro for Beginners by Udemy\",\n",
        "    \"Filmmaking\": \"Complete Filmmaker Guide: Become an Incredible Video Creator by Udemy\",\n",
        "    \"Photography\": \"Photography Masterclass: A Complete Guide to Photography by Udemy\",\n",
        "    \"Digital Marketing\": \"The Complete Digital Marketing Guide - 12 Courses in 1 by Udemy\",\n",
        "    \"SEO\": \"SEO Training Masterclass 2023: Beginner to Advanced by Udemy\",\n",
        "    \"Content Marketing\": \"Content Marketing Masterclass by Udemy\",\n",
        "    \"Social Media Marketing\": \"Social Media Marketing MASTERY 2023 by Udemy\",\n",
        "    \"Email Marketing\": \"Email Marketing - The Complete Guide by Udemy\",\n",
        "    \"Copywriting\": \"Copywriting Secrets - How to Write Copy That Sells by Udemy\",\n",
        "    \"Sales\": \"Sales Training: Practical Sales Techniques by Udemy\",\n",
        "    \"Entrepreneurship\": \"Entrepreneurship 101: Who is Your Customer? by edX\",\n",
        "    \"Leadership\": \"Leadership: Theory and Practice by Coursera\",\n",
        "    \"Negotiation\": \"Successful Negotiation: Essential Strategies and Skills by Coursera\",\n",
        "    \"Finance\": \"Finance for Non-Finance Professionals by Coursera\",\n",
        "    \"Accounting\": \"Financial Accounting Fundamentals by Coursera\",\n",
        "    \"Economics\": \"Principles of Economics by Coursera\",\n",
        "    \"Investing\": \"The Complete Investing Course by Udemy\",\n",
        "    \"Real Estate\": \"Real Estate Investing for Beginners by Udemy\",\n",
        "    \"Personal Development\": \"Personal Development Masterclass by Udemy\",\n",
        "    \"Time Management\": \"Time Management Mastery: Do More, Stress Less by Udemy\",\n",
        "    \"Public Speaking\": \"Public Speaking Masterclass by Udemy\",\n",
        "    \"Communication Skills\": \"Communication Skills Mastery by Udemy\",\n",
        "    \"Mindfulness\": \"Mindfulness Meditation for Beginners by Udemy\",\n",
        "    \"Yoga\": \"Yoga for Complete Beginners by Udemy\",\n",
        "    \"Health and Fitness\": \"The Complete Fitness Guide by Udemy\",\n",
        "    \"Nutrition\": \"Nutrition Masterclass: Build Your Perfect Diet & Meal Plan by Udemy\",\n",
        "    \"Cooking\": \"Cooking Basics: Master the Fundamentals by Udemy\",\n",
        "    \"Languages\": \"Learn Spanish - Complete Spanish Course for Beginners by Udemy\",\n",
        "    \"English\": \"English for Career Development by Coursera\",\n",
        "    \"French\": \"Learn French for Beginners by Udemy\",\n",
        "    \"German\": \"German Language for Beginners by Udemy\",\n",
        "    \"Japanese\": \"Japanese for Beginners by Udemy\",\n",
        "    \"Chinese\": \"Chinese for Beginners by Coursera\",\n",
        "    \"Russian\": \"Russian for Beginners by Udemy\",\n",
        "    \"Arabic\": \"Arabic for Beginners by Udemy\",\n",
        "    \"Italian\": \"Learn Italian for Beginners by Udemy\",\n",
        "    \"Portuguese\": \"Learn Portuguese for Beginners by Udemy\",\n",
        "    \"Critical Thinking\": \"Critical Thinking for Better Judgment and Decision-Making by Udemy\",\n",
        "    \"Emotional Intelligence\": \"Emotional Intelligence: Master Anxiety, Fear, & Emotions by Udemy\",\n",
        "    \"Creativity\": \"Creativity: Mastering Creativity by Udemy\",\n",
        "    \"Art\": \"Art Fundamentals: Theory and Practice by Udemy\",\n",
        "    \"History\": \"A History of the World since 1300 by Coursera\",\n",
        "    \"Philosophy\": \"Introduction to Philosophy by Coursera\",\n",
        "    \"Psychology\": \"Introduction to Psychology by Coursera\",\n",
        "    \"Sociology\": \"Sociology: Understanding and Changing the Social World by Udemy\",\n",
        "    \"Political Science\": \"Introduction to Political Science by Coursera\",\n",
        "    \"Law\": \"An Introduction to American Law by Coursera\",\n",
        "    \"Ethics\": \"Introduction to Ethics by Coursera\",\n",
        "    \"Literature\": \"The Modern and the Postmodern (Part 1) by Coursera\",\n",
        "    \"Writing\": \"Creative Writing Specialization by Coursera\",\n",
        "    \"Journalism\": \"Journalism for Social Change by Coursera\",\n",
        "    \"Environmental Science\": \"Introduction to Environmental Science by Coursera\",\n",
        "    \"Biology\": \"Introduction to Biology by Coursera\",\n",
        "    \"Chemistry\": \"Introduction to Chemistry by Coursera\",\n",
        "    \"Physics\": \"How Things Work: An Introduction to Physics by Coursera\",\n",
        "    \"Astronomy\": \"Astronomy: Exploring Time and Space by Coursera\",\n",
        "    \"Geology\": \"Geology: Earth Science for Everyone by Udemy\",\n",
        "    \"Anthropology\": \"Introduction to Anthropology by Coursera\",\n",
        "    \"Archaeology\": \"Introduction to Archaeology by Coursera\",\n",
        "    \"Astronomy\": \"Astronomy: Exploring Time and Space by Coursera\",\n",
        "    \"Linguistics\": \"Introduction to Linguistics by Coursera\",\n",
        "    \"Mathematics\": \"Mathematics for Computer Science by Coursera\",\n",
        "    \"Physics\": \"How Things Work: An Introduction to Physics by Coursera\"\n",
        "}\n",
        "def extract_text_from_pdf(pdf_file):\n",
        "    \"\"\"Extract text from a PDF file.\"\"\"\n",
        "    pdf_reader = PyPDF2.PdfReader(pdf_file)\n",
        "    text = \"\"\n",
        "    for page in pdf_reader.pages:\n",
        "        text += page.extract_text()\n",
        "    return text\n",
        "\n",
        "def preprocess_text(text):\n",
        "    \"\"\"Preprocess text by lowering the case and removing non-alphanumeric characters.\"\"\"\n",
        "    text = text.lower()\n",
        "    text = re.sub(r'[^a-z0-9\\s]', '', text)\n",
        "    return text\n",
        "\n",
        "def extract_skills(text, skills):\n",
        "    \"\"\"Extract and match skills from the text using contextual analysis and pattern matching.\"\"\"\n",
        "    matched_skills = []\n",
        "    text = preprocess_text(text)\n",
        "\n",
        "    for skill in skills:\n",
        "        skill_lower = skill.lower()\n",
        "        if re.search(r'\\b' + re.escape(skill_lower) + r'\\b', text):\n",
        "            matched_skills.append(skill)\n",
        "\n",
        "    return matched_skills\n",
        "\n",
        "def calculate_match_score(matched_skills, total_skills):\n",
        "    \"\"\"Calculate the match score based on matched skills.\"\"\"\n",
        "    match_percentage = (len(matched_skills) / total_skills) * 100\n",
        "    return match_percentage\n",
        "\n",
        "def create_pie_chart(match_percentage):\n",
        "    \"\"\"Create a pie chart to represent the match score.\"\"\"\n",
        "    labels = ['Matched Skills', 'Remaining Skills']\n",
        "    sizes = [match_percentage, 100 - match_percentage]\n",
        "    colors = ['#4CAF50', '#FF7043']\n",
        "    explode = (0.1, 0)\n",
        "\n",
        "    plt.figure(figsize=(7, 7))\n",
        "    plt.pie(sizes, explode=explode, labels=labels, colors=colors, autopct='%1.1f%%', shadow=True, startangle=140)\n",
        "    plt.axis('equal')\n",
        "    plt.title('Skill Match Score')\n",
        "    plt.show()\n",
        "\n",
        "def suggest_courses(missing_skills):\n",
        "    \"\"\"Suggest courses for missing skills or notify if not available.\"\"\"\n",
        "    suggested_courses = {}\n",
        "    for skill in missing_skills:\n",
        "        if skill in courses:\n",
        "            suggested_courses[skill] = courses[skill]\n",
        "        else:\n",
        "            suggested_courses[skill] = \"No specific course available. Consider searching online resources or platforms like Coursera, Udemy, or edX.\"\n",
        "    return suggested_courses\n",
        "\n",
        "def parse_resume_and_generate_report(pdf_file):\n",
        "    \"\"\"Main function to parse the resume, calculate the match score, and generate the report.\"\"\"\n",
        "    extracted_text = extract_text_from_pdf(pdf_file)\n",
        "    matched_skills = extract_skills(extracted_text, required_skills)\n",
        "    missing_skills = list(set(required_skills) - set(matched_skills))\n",
        "    match_score = calculate_match_score(matched_skills, len(required_skills))\n",
        "\n",
        "    # Show extracted skills before generating the pie chart\n",
        "    print(\"Extracted Skills:\")\n",
        "    for skill in matched_skills:\n",
        "        print(f\"- {skill}\")\n",
        "\n",
        "    # Generate pie chart\n",
        "    create_pie_chart(match_score)\n",
        "\n",
        "    # Report missing skills and suggest courses\n",
        "    if missing_skills:\n",
        "        print(\"\\nSkills you are missing:\")\n",
        "        for skill in missing_skills:\n",
        "            print(f\"- {skill}\")\n",
        "\n",
        "        print(\"\\nRecommended Courses:\")\n",
        "        suggested_courses = suggest_courses(missing_skills)\n",
        "        for skill, course in suggested_courses.items():\n",
        "            print(f\"- {skill}: {course}\")\n",
        "    else:\n",
        "        print(\"Congratulations! You have all the required skills.\")\n",
        "\n",
        "# Example usage\n",
        "if __name__ == \"__main__\":\n",
        "    resume_file_path = \"/content/data-scientist-1559725114.pdf\"\n",
        "    with open(resume_file_path, \"rb\") as resume_file:\n",
        "        parse_resume_and_generate_report(resume_file)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "nH5QZ9KKdLp5",
        "outputId": "31dce9d4-5e87-4f0f-b919-a66764f8f0c8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Extracted Skills:\n",
            "- Python\n",
            "- Machine Learning\n",
            "- Data Analysis\n",
            "- R\n",
            "- MATLAB\n",
            "- Sphinx\n",
            "- Mathematica\n",
            "- Maple\n",
            "- GIT\n",
            "- CVS\n",
            "- HTCondor\n",
            "- Data Mining\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 700x700 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Skills you are missing:\n",
            "- JavaScript\n",
            "- SQL\n",
            "- C++\n",
            "- Flask\n",
            "- Java\n",
            "- Django\n",
            "- React\n",
            "- LaTeX\n",
            "\n",
            "Recommended Courses:\n",
            "- JavaScript: JavaScript: Understanding the Weird Parts by Udemy\n",
            "- SQL: The Complete SQL Bootcamp by Udemy\n",
            "- C++: Beginning C++ Programming by Udemy\n",
            "- Flask: Flask: Full Stack Web Development by Udemy\n",
            "- Java: Java Programming and Software Engineering Fundamentals by Coursera\n",
            "- Django: Django for Everybody by Coursera\n",
            "- React: React - The Complete Guide by Udemy\n",
            "- LaTeX: No specific course available. Consider searching online resources or platforms like Coursera, Udemy, or edX.\n"
          ]
        }
      ]
    }
  ]
}