About
Phase 1: Demystifying AI (Weeks 1-2 - 10 Days) Introduction to AI (2 Days): What is AI? A historical perspective and its impact on society. Different types of AI (Machine Learning, Deep Learning, Natural Language Processing) Applications of AI across various industries (healthcare, finance, robotics) The Math Behind AI (3 Days): An introduction to essential mathematical concepts used in AI (linear algebra, calculus, probability & statistics). Focus: Make it accessible even for those without a strong math background. Provide resources for further exploration (optional). Ethics & Societal Impact of AI (2 Days): Ethical considerations in AI development and deployment (bias, fairness, transparency). The potential impact of AI on jobs and society (automation, social good). Introduction to Python Programming (3 Days): Python as a popular language for AI applications. Learn basic syntax, data structures, and control flow. Target: Get comfortable with Python for further AI exploration (hands-on exercises). Phase 2: Diving Deeper into AI Techniques (Weeks 3-6 - 20 Days) Machine Learning Fundamentals (5 Days): Supervised learning (regression, classification) with hands-on implementation in Python libraries (Scikit-learn). Unsupervised learning (clustering, dimensionality reduction). Deep Learning with Neural Networks (6 Days): Introduction to Artificial Neural Networks (ANNs) and their structure. Building and training simple neural networks using frameworks like TensorFlow or PyTorch (hands-on projects). Natural Language Processing (NLP) (4 Days): Understanding human language: text processing, tokenization, and stemming. Introduction to NLP techniques like sentiment analysis and machine translation. Computer Vision with AI (5 Days): Fundamentals of image processing and computer vision concepts. Image classification and object detection using pre-trained models (e.g., convolutional neural networks). Phase 3: Putting AI into Action (Weeks 7-8 - 20 Days)