{"id":1877,"date":"2025-08-13T10:56:28","date_gmt":"2025-08-13T10:56:28","guid":{"rendered":"https:\/\/itxperts.co.in\/blog\/?p=1877"},"modified":"2025-08-13T10:56:56","modified_gmt":"2025-08-13T10:56:56","slug":"cbse-class-10-ai-python-projects","status":"publish","type":"post","link":"https:\/\/itxperts.co.in\/blog\/cbse-class-10-ai-python-projects\/","title":{"rendered":"Python Programs for CBSE Class 10 AI Projects"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Introduction<\/h2>\n\n\n\n<p>Artificial Intelligence is an exciting field and CBSE Class 10 AI curriculum encourages students to build simple, meaningful projects using the AI Project Cycle. These projects help students understand problem solving, data collection, data processing, model building, and result evaluation.<\/p>\n\n\n\n<p>Below are <strong>six CBSE Class 10 AI project ideas in Python<\/strong> with complete code. All projects are simple enough for beginners and can be run in Google Colab, Jupyter Notebook, or any Python IDE.<\/p>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">1. Sentiment Analysis of Student Reviews<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Objective<\/h3>\n\n\n\n<p>Classify short student reviews as positive, negative, or neutral using Natural Language Processing.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Dataset<\/h3>\n\n\n\n<p>Create a CSV file with 50\u2013100 one-line reviews from classmates about school events, facilities, or movies.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Steps<\/h3>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Collect and label the data.<\/li>\n\n\n\n<li>Clean the text.<\/li>\n\n\n\n<li>Train a sentiment analysis model.<\/li>\n\n\n\n<li>Test it with new reviews.<\/li>\n<\/ol>\n\n\n\n<h3 class=\"wp-block-heading\">Python Code<\/h3>\n\n\n\n<pre class=\"wp-block-code\"><code>from textblob import TextBlob\n\n# Sample reviews\nreviews = &#91;\n    \"The sports day was amazing and full of fun\",\n    \"I did not enjoy the event at all\",\n    \"It was okay but could have been better\"\n]\n\nfor review in reviews:\n    blob = TextBlob(review)\n    sentiment = blob.sentiment.polarity\n    if sentiment &gt; 0:\n        mood = \"Positive\"\n    elif sentiment &lt; 0:\n        mood = \"Negative\"\n    else:\n        mood = \"Neutral\"\n    print(f\"Review: {review} - Sentiment: {mood}\")\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">Expected Output<\/h3>\n\n\n\n<p>Each review will be labeled as Positive, Negative, or Neutral.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Viva Questions<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>What is sentiment polarity?<\/li>\n\n\n\n<li>Why do we clean text before processing?<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">2. Handwritten Digit Recognition<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Objective<\/h3>\n\n\n\n<p>Recognize handwritten digits (0\u20139) using a simple machine learning model.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Dataset<\/h3>\n\n\n\n<p>Use the built-in <code>digits<\/code> dataset from scikit-learn.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Steps<\/h3>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Load the dataset.<\/li>\n\n\n\n<li>Train a logistic regression classifier.<\/li>\n\n\n\n<li>Test on unseen data.<\/li>\n<\/ol>\n\n\n\n<h3 class=\"wp-block-heading\">Python Code<\/h3>\n\n\n\n<pre class=\"wp-block-code\"><code>from sklearn import datasets, metrics\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.linear_model import LogisticRegression\n\n# Load dataset\ndigits = datasets.load_digits()\n\n# Split into train and test\nX_train, X_test, y_train, y_test = train_test_split(digits.data, digits.target, test_size=0.2)\n\n# Train model\nmodel = LogisticRegression(max_iter=10000)\nmodel.fit(X_train, y_train)\n\n# Predict\ny_pred = model.predict(X_test)\n\n# Accuracy\nprint(\"Accuracy:\", metrics.accuracy_score(y_test, y_pred))\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">Expected Output<\/h3>\n\n\n\n<p>An accuracy score between 0.90 and 0.95 depending on system and random split.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Viva Questions<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>What is a pixel?<\/li>\n\n\n\n<li>How does the model learn from image data?<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">3. School FAQ Chatbot<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Objective<\/h3>\n\n\n\n<p>Answer common school questions using a rule-based chatbot.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Dataset<\/h3>\n\n\n\n<p>Create a Python dictionary with common questions and answers.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Steps<\/h3>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Map keywords to responses.<\/li>\n\n\n\n<li>Take input from the user.<\/li>\n\n\n\n<li>Display matching responses.<\/li>\n<\/ol>\n\n\n\n<h3 class=\"wp-block-heading\">Python Code<\/h3>\n\n\n\n<pre class=\"wp-block-code\"><code>responses = {\n    \"hello\": \"Hello, how can I help you?\",\n    \"admission\": \"Admissions are open till 30th September.\",\n    \"fees\": \"The annual school fee is fifty thousand rupees.\",\n    \"timing\": \"School timing is 8 AM to 2 PM.\",\n    \"goodbye\": \"Goodbye and have a nice day.\"\n}\n\nwhile True:\n    user_input = input(\"You: \").lower()\n    if user_input in responses:\n        print(\"Bot:\", responses&#91;user_input])\n        if user_input == \"goodbye\":\n            break\n    else:\n        print(\"Bot: Sorry, I do not have an answer for that.\")\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">Expected Output<\/h3>\n\n\n\n<p>The chatbot answers correctly for known questions and politely for unknown ones.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Viva Questions<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>How is a rule-based chatbot different from a machine learning chatbot?<\/li>\n\n\n\n<li>What happens when no matching response is found?<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">4. Color Detection in Images<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Objective<\/h3>\n\n\n\n<p>Detect the RGB values of a specific pixel in an image.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Dataset<\/h3>\n\n\n\n<p>Any school or personal image saved as <code>image.jpg<\/code>.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Steps<\/h3>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Load the image.<\/li>\n\n\n\n<li>Pick coordinates.<\/li>\n\n\n\n<li>Read RGB values.<\/li>\n<\/ol>\n\n\n\n<h3 class=\"wp-block-heading\">Python Code<\/h3>\n\n\n\n<pre class=\"wp-block-code\"><code>import cv2\n\n# Load image\nimage = cv2.imread('image.jpg')\n\n# Coordinates\nx, y = 50, 100\n(b, g, r) = image&#91;y, x]\nprint(f\"Pixel at ({x},{y}) - Red: {r}, Green: {g}, Blue: {b}\")\n\n# Show image\ncv2.imshow(\"Image\", image)\ncv2.waitKey(0)\ncv2.destroyAllWindows()\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">Expected Output<\/h3>\n\n\n\n<p>RGB values for the selected pixel.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Viva Questions<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>What is RGB?<\/li>\n\n\n\n<li>How does light affect color detection?<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">5. Marks Prediction from Study Hours<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Objective<\/h3>\n\n\n\n<p>Predict student marks based on daily study hours.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Dataset<\/h3>\n\n\n\n<p>Hours studied and marks obtained for 30\u201350 students.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Steps<\/h3>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Create dataset.<\/li>\n\n\n\n<li>Train a regression model.<\/li>\n\n\n\n<li>Predict marks for given hours.<\/li>\n<\/ol>\n\n\n\n<h3 class=\"wp-block-heading\">Python Code<\/h3>\n\n\n\n<pre class=\"wp-block-code\"><code>from sklearn.linear_model import LinearRegression\nimport numpy as np\n\n# Dataset\nX = np.array(&#91;1, 2, 3, 4, 5]).reshape(-1, 1)\ny = np.array(&#91;35, 50, 65, 75, 85])\n\n# Train model\nmodel = LinearRegression()\nmodel.fit(X, y)\n\n# Predict for 6 hours of study\npredicted = model.predict(&#91;&#91;6]])\nprint(f\"Predicted Marks: {predicted&#91;0]:.2f}\")\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">Expected Output<\/h3>\n\n\n\n<p>Predicted marks for 6 study hours, around 90 depending on dataset.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Viva Questions<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>What is regression?<\/li>\n\n\n\n<li>Why is it important to split data into train and test sets?<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">6. News Topic Classification<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">Objective<\/h3>\n\n\n\n<p>Classify short news headlines into categories like sports, politics, technology, and entertainment.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Dataset<\/h3>\n\n\n\n<p>Prepare a CSV file with at least 100 headlines.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Steps<\/h3>\n\n\n\n<ol class=\"wp-block-list\">\n<li>Clean text.<\/li>\n\n\n\n<li>Convert to features.<\/li>\n\n\n\n<li>Train a classifier.<\/li>\n\n\n\n<li>Test accuracy.<\/li>\n<\/ol>\n\n\n\n<h3 class=\"wp-block-heading\">Python Code<\/h3>\n\n\n\n<pre class=\"wp-block-code\"><code>from sklearn.feature_extraction.text import CountVectorizer\nfrom sklearn.model_selection import train_test_split\nfrom sklearn.naive_bayes import MultinomialNB\nfrom sklearn import metrics\n\n# Sample data\nheadlines = &#91;\n    \"India wins cricket match\",\n    \"New smartphone launched in market\",\n    \"Government passes new education bill\",\n    \"Actor announces new movie release\"\n]\nlabels = &#91;\"sports\", \"technology\", \"politics\", \"entertainment\"]\n\n# Vectorize text\nvectorizer = CountVectorizer()\nX = vectorizer.fit_transform(headlines)\n\n# Train-test split\nX_train, X_test, y_train, y_test = train_test_split(X, labels, test_size=0.25)\n\n# Train model\nmodel = MultinomialNB()\nmodel.fit(X_train, y_train)\n\n# Predict\ny_pred = model.predict(X_test)\nprint(\"Accuracy:\", metrics.accuracy_score(y_test, y_pred))\n<\/code><\/pre>\n\n\n\n<h3 class=\"wp-block-heading\">Expected Output<\/h3>\n\n\n\n<p>Accuracy score based on given dataset.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Viva Questions<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>What is Bag of Words?<\/li>\n\n\n\n<li>How do you handle unknown words in text classification?<\/li>\n<\/ul>\n\n\n\n<hr class=\"wp-block-separator has-alpha-channel-opacity\"\/>\n\n\n\n<h2 class=\"wp-block-heading\">Conclusion<\/h2>\n\n\n\n<p>These Python programs cover various AI topics in the CBSE Class 10 syllabus such as NLP, computer vision, regression, and classification. Each can be expanded into a complete project report by adding objective, problem statement, dataset description, methodology, results, conclusion, and ethical considerations.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Introduction Artificial Intelligence is an exciting field and CBSE Class 10 AI curriculum encourages students to build simple, meaningful projects using the AI Project Cycle. These projects help students understand problem solving, data collection, data processing, model building, and result evaluation. Below are six CBSE Class 10 AI project ideas in Python with complete code. [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":1878,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"googlesitekit_rrm_CAow44u0DA:productID":"","footnotes":""},"categories":[225],"tags":[],"class_list":["post-1877","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-project"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v26.9 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Python Programs for CBSE Class 10 AI Projects - Itxperts<\/title>\n<meta name=\"description\" content=\"Simple and practical CBSE Class 10 AI project ideas using Python explained step by step without code Samples include NLP sentiment analysis image classification marks prediction rule based chatbot and more\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/itxperts.co.in\/blog\/cbse-class-10-ai-python-projects\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Python Programs for CBSE Class 10 AI Projects\" \/>\n<meta property=\"og:description\" content=\"Simple and practical CBSE Class 10 AI project ideas using Python explained step by step without code Samples include NLP sentiment analysis image classification marks prediction rule based chatbot and more\" \/>\n<meta property=\"og:url\" content=\"https:\/\/itxperts.co.in\/blog\/cbse-class-10-ai-python-projects\/\" \/>\n<meta property=\"og:site_name\" content=\"Itxperts\" \/>\n<meta property=\"article:publisher\" content=\"https:\/\/www.facebook.com\/itxperts.co.in\" \/>\n<meta property=\"article:published_time\" content=\"2025-08-13T10:56:28+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-08-13T10:56:56+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/itxperts.co.in\/blog\/wp-content\/uploads\/2025\/08\/CBSE-Class-10-AI-Python-Projects.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1536\" \/>\n\t<meta property=\"og:image:height\" content=\"1024\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"@mritxperts\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"@mritxperts\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"3 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/itxperts.co.in\/blog\/cbse-class-10-ai-python-projects\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/itxperts.co.in\/blog\/cbse-class-10-ai-python-projects\/\"},\"author\":{\"name\":\"@mritxperts\",\"@id\":\"https:\/\/itxperts.co.in\/blog\/#\/schema\/person\/77ad4d47f9f82583ee23e37010a52fc6\"},\"headline\":\"Python Programs for CBSE Class 10 AI Projects\",\"datePublished\":\"2025-08-13T10:56:28+00:00\",\"dateModified\":\"2025-08-13T10:56:56+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/itxperts.co.in\/blog\/cbse-class-10-ai-python-projects\/\"},\"wordCount\":518,\"publisher\":{\"@id\":\"https:\/\/itxperts.co.in\/blog\/#organization\"},\"image\":{\"@id\":\"https:\/\/itxperts.co.in\/blog\/cbse-class-10-ai-python-projects\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/itxperts.co.in\/blog\/wp-content\/uploads\/2025\/08\/CBSE-Class-10-AI-Python-Projects.png\",\"articleSection\":[\"Project\"],\"inLanguage\":\"en-US\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/itxperts.co.in\/blog\/cbse-class-10-ai-python-projects\/\",\"url\":\"https:\/\/itxperts.co.in\/blog\/cbse-class-10-ai-python-projects\/\",\"name\":\"Python Programs for CBSE Class 10 AI Projects - 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