AI Algorithms and Applications
( 25 Modules )

Module #1
Introduction to Artificial Intelligence
Overview of AI, its history, and applications

Module #2
Machine Learning Fundamentals
Types of machine learning, supervised and unsupervised learning, and model evaluation metrics

Module #3
Linear Regression
Simple and multiple linear regression, gradient descent, and regularization techniques

Module #4
Decision Trees and Random Forests
Decision tree algorithms, random forests, and ensemble methods

Module #5
Support Vector Machines (SVMs)
SVM theory, kernel methods, and applications

Module #6
Clustering Algorithms
K-means, hierarchical clustering, and density-based clustering methods

Module #7
Naive Bayes and Bayesian Networks
Naive Bayes, Bayes theorem, and Bayesian network applications

Module #8
Deep Learning Fundamentals
Introduction to deep learning, neural networks, and activation functions

Module #9
Convolutional Neural Networks (CNNs)
CNN architectures, convolutional layers, and applications in computer vision

Module #10
Recurrent Neural Networks (RNNs) and LSTMs
RNN theory, LSTM architectures, and applications in natural language processing

Module #11
Generative Adversarial Networks (GANs)
GAN theory, generators, discriminators, and applications in image synthesis

Module #12
Natural Language Processing (NLP) Fundamentals
NLP concepts, text preprocessing, and word embeddings

Module #13
Text Classification and Sentiment Analysis
Text classification algorithms, sentiment analysis, and applications in NLP

Module #14
Image Processing and Computer Vision
Image processing techniques, object detection, and segmentation

Module #15
Unsupervised Learning and Dimensionality Reduction
Unsupervised learning techniques, PCA, t-SNE, and autoencoders

Module #16
Reinforcement Learning Fundamentals
Reinforcement learning concepts, Markov decision processes, and Q-learning

Module #17
Deep Reinforcement Learning and Policy Gradient Methods
Deep reinforcement learning, policy gradient methods, and actor-critic algorithms

Module #18
Ethics and Fairness in AI
AI ethics, bias detection, and fairness metrics

Module #19
AI Applications in Healthcare
AI in healthcare, medical imaging, and clinical decision support systems

Module #20
AI Applications in Finance
AI in finance, risk management, and portfolio optimization

Module #21
AI Applications in Autonomous Systems
AI in autonomous vehicles, robotics, and control systems

Module #22
AI Applications in Recommendation Systems
AI in recommendation systems, collaborative filtering, and content-based filtering

Module #23
AI Applications in Natural Language Understanding
AI in NLU, dialogue systems, and chatbots

Module #24
AI Project Development and Deployment
AI project development lifecycle, deployment strategies, and model serving

Module #25
Course Wrap-Up & Conclusion
Planning next steps in AI Algorithms and Applications career

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AI Algorithms and Applications ( 25 Modules )

AI Algorithms and Applications
( 25 Modules )