AI for Everyone: No Coding to Advanced - dailycombo.online

 Artificial Intelligence (AI) Course Outline

Course Title: Introduction to Artificial Intelligence (AI)

Duration: 8-12 Weeks

Level: Beginner to Intermediate

Module 1: Introduction to AI

• Definition and History of AI

• Types of AI (Narrow AI, General AI, Super AI)

• Applications of AI in Various Industries

• Ethical Considerations in AI

Module 2: Foundations of AI

• Machine Learning vs. Deep Learning vs. AI

• Key Concepts: Algorithms, Models, and Data

• Supervised, Unsupervised, and Reinforcement Learning

Module 3: Machine Learning Basics

• Linear Regression & Logistic Regression

• Decision Trees and Random Forests

• Support Vector Machines (SVM)

• Model Evaluation Metrics (Accuracy, Precision, Recall, F1-Score)

Module 4: Deep Learning & Neural Networks

• Introduction to Neural Networks

• Activation Functions (ReLU, Sigmoid, Tanh)

• Convolutional Neural Networks (CNNs) for Image Processing

• Recurrent Neural Networks (RNNs) for Sequential Data

Module 5: Natural Language Processing (NLP)

• Text Preprocessing (Tokenization, Stemming, Lemmatization)

• Word Embeddings (Word2Vec, GloVe)

• Transformers & Large Language Models (LLMs) like GPT & BERT

Module 6: AI Tools & Frameworks

• Python for AI (NumPy, Pandas, Scikit-learn)

• TensorFlow & PyTorch for Deep Learning

• OpenAI & Hugging Face for NLP

Module 7: AI in Real-World Applications

• AI in Healthcare, Finance, and Autonomous Vehicles

• AI in Robotics & Computer Vision

• AI-powered Chatbots & Virtual Assistants

Module 8: Future Trends & Capstone Project

• Explainable AI (XAI)

• AI and Quantum Computing

• Final Project: Build an AI Model (e.g., Image Classifier, Chatbot, or Predictive Model)

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Assessment & Certification:

• Quizzes & Assignments

• Hands-on Projects

• Final Exam & Capstone Project Submission

• Course Completion Certificate

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