Class 12 Artificial Intelligence Notes

Introduction to Python Programming-II (CBSE Class 12 Artificial Intelligence) Build upon your Class XI Python knowledge and discover how Python, along with powerful libraries like NumPy and Pandas, forms the foundation of Artificial Intelligence, Data Science, and Machine Learning.

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Recap of NumPy Library (CBSE Class 12 Artificial Intelligence) Revise the fundamentals of the NumPy library, including arrays, dimensions, common functions, and its role in Artificial Intelligence, Data Science, and Machine Learning.

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Recap of Pandas Library (CBSE Class 12 Artificial Intelligence) Revise the Pandas library, its data structures, DataFrame operations, attributes, and its importance in Artificial Intelligence, Data Science, and Machine Learning.

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Importing and Exporting Data between CSV Files and DataFrames (CBSE Class 12 Artificial Intelligence) Learn how to import data from CSV files into Pandas DataFrames and export processed data back to CSV files for Artificial Intelligence and Data Science applications.

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Handling Missing Values (CBSE Class 12 Artificial Intelligence) Learn how to identify, remove, and replace missing values in datasets using the Pandas library to prepare clean and accurate data for Artificial Intelligence and Machine Learning.

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Linear Regression Algorithm (Advanced Learners) (CBSE Class 12 Artificial Intelligence) Learn the fundamentals of the Linear Regression algorithm, its working, implementation using Python, and how it is used to predict continuous values in Artificial Intelligence and Machine Learning.

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Practical: Import and Export Data between CSV Files and DataFrames (CBSE Class 12 Artificial Intelligence) Perform a complete practical to import data from a CSV file into a Pandas DataFrame, analyze the dataset, and export the processed data back to a CSV file using Python.

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Introduction to Data Science Methodology (CBSE Class 12 Artificial Intelligence) Understand the concept of Data Science Methodology, its importance in solving real-world problems, and how a systematic approach helps build reliable Artificial Intelligence solutions.

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Steps of Data Science Methodology (CBSE Class 12 Artificial Intelligence) Learn the systematic steps of the Data Science Methodology used to solve real-world problems, from understanding the business problem to deploying and monitoring AI models.

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Model Validation Techniques (CBSE Class 12 Artificial Intelligence) Learn the importance of model validation, different validation techniques, and how they help evaluate the performance and reliability of Machine Learning models before deployment.

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Model Performance Evaluation Metrics (CBSE Class 12 Artificial Intelligence) Learn the commonly used model performance evaluation metrics such as Confusion Matrix, Accuracy, Precision, Recall, F1-Score, Mean Squared Error (MSE), and Root Mean Squared Error (RMSE) used to evaluate Machine Learning models.

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Practical: Calculate MSE and RMSE using Microsoft Excel (CBSE Class 12 Artificial Intelligence) Learn how to calculate Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) using Microsoft Excel to evaluate the performance of regression models.

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Practical: Calculate Precision, Recall, F1-Score and Accuracy from a Confusion Matrix (CBSE Class 12 Artificial Intelligence) Learn how to calculate Accuracy, Precision, Recall, and F1-Score from a Confusion Matrix using manual calculations and Microsoft Excel to evaluate the performance of classification models.

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Practical: Python Code to Evaluate a Machine Learning Model (CBSE Class 12 Artificial Intelligence) Learn how to evaluate a Machine Learning classification model in Python using Scikit-learn by generating a Confusion Matrix, Accuracy, Precision, Recall, and F1-Score.

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Introduction to Making Machines See (CBSE Class 12 Artificial Intelligence) Understand how computers interpret visual information using Computer Vision, why machines need images as data, and how this technology powers modern Artificial Intelligence applications.

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How Machines See (CBSE Class 12 Artificial Intelligence) Learn how computers capture, represent, and interpret images using pixels, digital image processing, and Machine Learning to recognize objects just like humans.

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Working of Computer Vision (CBSE Class 12 Artificial Intelligence) Learn how Computer Vision systems capture, process, analyze, and interpret images step by step using Artificial Intelligence and Machine Learning techniques.

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Computer Vision Process (CBSE Class 12 Artificial Intelligence) Understand the complete Computer Vision process, from capturing an image to making intelligent decisions, and learn how each stage contributes to accurate visual recognition.

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Applications of Computer Vision (CBSE Class 12 Artificial Intelligence) Explore the diverse applications of Computer Vision in healthcare, transportation, agriculture, education, security, manufacturing, retail, and many other industries that use Artificial Intelligence.

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Challenges of Computer Vision (CBSE Class 12 Artificial Intelligence) Understand the major challenges faced by Computer Vision systems, including lighting conditions, image quality, occlusion, viewpoint variation, large datasets, computational requirements, and ethical concerns.

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