Artificial Intelligence Subject Code 417
COMMUNICATION SKILLS
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Communication is the process of sharing information between people.
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It includes speaking, listening, reading and writing.
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Good communication helps in building better relationships.
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There are two main types: verbal and non-verbal communication.
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Verbal communication uses words to express ideas.
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Non-verbal communication includes body language, gestures and facial expressions.
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Active listening is an important part of good communication.
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Clear communication reduces misunderstandings.
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Effective communication is important in school and the workplace.
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Technology also helps communication through email, messages and video calls.
SELF-MANAGEMENT SKILLS-1
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Self-management means controlling your thoughts, emotions and actions.
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It helps you stay organised and responsible.
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Goal setting is an important part of self-management.
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Time management helps you finish tasks on time.
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Staying motivated helps achieve long-term goals.
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Self-awareness helps you understand your strengths and weaknesses.
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Managing stress keeps the mind calm and focused.
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Maintaining discipline improves work quality.
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Self-management is useful for both studies and daily life.
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Good self-management leads to better decision-making.
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INTRODUCTION TO AI
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Artificial Intelligence is a technology that enables machines to think and act like humans.
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AI systems learn from data and improve their performance over time.
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Narrow AI is designed to perform a specific task, like voice assistants or face unlock.
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General AI is a type of AI that can think and learn like humans, but it does not exist yet.
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AI works by using algorithms that help machines process information and make decisions.
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Many apps we use daily—like YouTube, Google Maps, and Instagram—use AI to give personalized results.
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AI helps in different fields like healthcare, education, banking, and transportation.
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AI can make mistakes if the data used for training is wrong or biased.
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With the help of sensors, AI can understand images, speech, and text.
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AI saves time and reduces human effort by automating repetitive tasks.
AI PROJECT CYCLE
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It mainly includes four stages: Problem Scoping, Data Acquisition, Data Exploration, and Modelling.
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In Problem Scoping, we clearly identify the problem and understand the user’s needs.
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Empathy maps are used to understand what the user says, thinks, does, and feels.
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Data Acquisition involves collecting the correct data from various sources like surveys, sensors, or databases.
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In Data Exploration, we study the collected data using charts and graphs to understand patterns.
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Modelling is the process of building an AI model using Machine Learning techniques.
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The model is trained using training data and tested using testing data.
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Evaluation helps us check how accurate and reliable the AI model is.
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The AI Project Cycle is iterative, meaning the model can be improved again and again using feedback.
3-NEURAL NETWORKS
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A neural network is a type of Artificial Intelligence that tries to work like the human brain.
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It is made up of layers of interconnected nodes called neurons.
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Each neuron receives information, processes it, and passes it to the next layer.
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Neural networks can learn patterns from large amounts of data.
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They are used for tasks like image recognition, speech recognition, and language translation.
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A neural network has three main layers: input layer, hidden layers, and output layer.
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Hidden layers perform most of the calculations in the network.
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When a neural network makes mistakes, it improves using a method called backpropagation.
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Deep Learning uses neural networks with many hidden layers.
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Neural networks become more accurate as they are trained with more data.
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