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Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. This includes capabilities like learning, reasoning, problem-solving, perception, and decision-making. AI systems achieve this by processing data and using algorithms to identify patterns, make predictions, and solve problems


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Course Details

1. Introduction to Artificial Intelligence

  • What is AI? History and Evolution
  • Applications of AI in Various Industries
  • AI vs. Machine Learning vs. Deep Learning
  • AI Ethics and Responsible AI
  • AI Tools and Platforms Overview

  • State Space Representation
  • Uninformed Search: BFS, DFS
  • Informed Search: A*, Greedy Search
  • Constraint Satisfaction Problems (CSPs)
  • Adversarial Search (Minimax, Alpha-Beta Pruning)

  • Supervised, Unsupervised, and Reinforcement Learning
  • Regression and Classification Algorithms
  • Decision Trees, Naïve Bayes, KNN
  • Model Evaluation Metrics
  • Overfitting and Underfitting

  • Introduction to Neural Networks
  • Activation Functions, Loss Functions
  • Backpropagation and Gradient Descent
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs) & LSTMs
  • Deep Learning Frameworks (TensorFlow, PyTorch)

  • Text Preprocessing (Tokenization, Stemming, Lemmatization)
  • Word Embeddings (Word2Vec, GloVe, BERT)
  • Named Entity Recognition (NER)
  • Sentiment Analysis
  • Chatbots and Language Models

  • Image Processing Basics
  • Feature Extraction and Object Detection
  • Face Recognition & Emotion Detection
  • Generative Adversarial Networks (GANs)

  • Markov Decision Processes (MDPs)
  • Q-Learning & Deep Q Networks (DQN)
  • Policy Gradient Methods
  • Applications in Robotics and Game AI

  • AI for Healthcare, Finance, and Autonomous Vehicles
  • AI in Robotics
  • AI for Cybersecurity

  • Bias in AI and Fairness
  • Explainable AI
  • AI in the Future: AGI and ASI

  • Data Collection and Preprocessing
  • Model Selection and Training
  • Model Deployment and Optimization


Fees Structure : 15500 INR / 180 USD
Total No of Class : 42 Video Class
Class Duration : 47:00 Working Hours
Download Feature : Download Avalable
Technical Support : Call / Whatsapp : +91 8680961847
Working Hours : Monday to Firday 9 AM to 6 PM
Payment Mode : Credit Card / Debit Card / NetBanking / Wallet (Gpay/Phonepay/Paytm/WhatsApp Pay)

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Fees Structure : 22000 INR / 255 USD
Class Duration : 40 Days
Class Recording : Live Class Recording available
Class Time : Monday to Firday 1.5 hours per day / Weekend 3 Hours per day
Technical Support : Call / Whatsapp : +91 8680961847
Working Hours : Monday to Firday 9 AM to 6 PM
Payment Mode : Credit Card / Debit Card / NetBanking / Wallet (Gpay/Phonepay/Paytm/WhatsApp Pay)

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