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Artificial Intelligence & Machine Learning (AI & ML)
Curriculum
12 Sections
12 Lessons
70 Hours
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Introduction to AI & ML (4hours)
2
1.2
Definitions, history, ML vs DL vs AI, supervised vs unsupervised learning
Python for AI & ML (4hours)
1
2.1
NumPy, pandas, matplotlib, scikit-learn basics
ML Algorithms & Concepts (6hours)
1
3.1
Linear regression, logistic regression, decision trees, SVM, KNN, clustering
Deep Learning with TensorFlow (8hours)
1
4.1
Neural networks, backpropagation, activation functions, model training & evaluation
PyTorch for Model Building (8hours)
1
5.1
Building DL models with PyTorch, autograd, optimization, GPU acceleration
Natural Language Processing (NLP) (8hours)
1
6.1
Text preprocessing, tokenization, TF-IDF, word embeddings, RNNs, Transformers
Computer Vision Applications (8hours)
1
7.1
Image classification, object detection, CNNs, OpenCV, transfer learning
AI in Healthcare (4hours)
1
8.1
Predictive diagnostics, medical imaging analysis, patient risk prediction
AI in Fintech (4hours)
1
9.1
Fraud detection, credit scoring, algorithmic trading, chatbot assistants
AI in Automation & IoT (4hours)
1
10.1
Industrial automation, robotics, smart systems, edge AI
Ethics and AI Governance (4hours)
1
11.1
AI fairness, transparency, data privacy, regulatory compliance
Capstone Project (10hours)
1
12.1
Domain-specific mini project using AI/ML models
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