How to use Artificial Intelligence – A guide for everyone! Course

Module 1: Introduction to AI Fundamentals

⏳ 30 minutes

• Defining AI, ML, and DL; history and evolution of the field

• Overview of AI subdomains and key terminology

Module 2: The AI Development Workflow

⏳ 45 minutes

• Data gathering and preprocessing essentials

• Training, validation, and testing phases with performance metrics

Module 3: Machine Learning Techniques

⏳ 1 hour

• Supervised learning algorithms: linear regression, decision trees, and support vector machines

• Unsupervised methods: clustering (k-means) and dimensionality reduction (PCA)

Module 4: Deep Learning & Neural Networks

⏳ 1 hour

• Neural network architecture, activation functions, and backpropagation

• Introduction to CNNs for image tasks and RNNs for sequence data

Module 5: AI Tools & Platforms Overview

⏳ 45 minutes

• High-level demos of TensorFlow/Keras, PyTorch, and popular AutoML services

• Using AI APIs (NLP, vision, speech) without code

Module 6: Real-World Applications & Case Studies

⏳ 45 minutes

• AI in healthcare diagnostics, fraud detection, recommendation engines, and chatbots

• Business impact analysis and ROI considerations

Module 7: Responsible AI & Ethics

⏳ 30 minutes

• Bias identification and mitigation strategies

• Privacy, transparency, and regulatory frameworks

Module 8: Next Steps & Career Pathways

⏳ 30 minutes

• Building an AI portfolio: sample projects and Kaggle challenges

• Recommended learning paths: specialization courses, certifications, and communities

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