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AI & Machine Learning Fundamentals

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119 Published chapters
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01

Edxera Introduction

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02

The Machine Learning Paradigm

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03

Types of Machine Learning

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05

Python for AI Development

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06

Data Visualization for ML

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Exploratory Data Analysis (EDA)

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08

Feature Engineering Foundations

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09

Mathematics of ML: Linear Algebra

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Mathematics of ML: Calculus

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Mathematics of ML: Probability

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Introduction to Linear Regression

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Multiple Linear Regression

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Cost Functions and Loss

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Gradient Descent Optimization

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Overfitting and Underfitting

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Regularization Techniques

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Logistic Regression for Classification

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Performance Metrics: Classification

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K-Nearest Neighbors (KNN)

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Decision Trees Foundations

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Ensemble Learning: Random Forests

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Boosting Algorithms

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Support Vector Machines (SVM)

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Dimensionality Reduction: PCA

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Unsupervised Learning: K-Means

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Hierarchical Clustering

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Evaluation of Clusters

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Introduction to Neural Networks

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Activation Functions

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Backpropagation Explained

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Deep Learning Frameworks

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Building a Simple Neural Network

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Hyperparameter Tuning in Deep Learning

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Convolutional Neural Networks (CNNs)

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Image Preprocessing for CNNs

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Transfer Learning for Vision

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Object Detection Fundamentals

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Image Segmentation

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Recurrent Neural Networks (RNNs)

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Long Short-Term Memory (LSTM)

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Introduction to Natural Language Processing

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Word Embeddings

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Sequence-to-Sequence Models

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The Attention Mechanism

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Transformer Architecture

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BERT and Pre-trained Transformers

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Large Language Models (LLMs)

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Generative AI Foundations

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Generative Adversarial Networks (GANs)

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Diffusion Models

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Reinforcement Learning: Foundations

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Markov Decision Processes (MDP)

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Q-Learning and Deep Q-Networks

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Policy Gradient Methods

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AI for Time Series Forecasting

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Recommendation Systems

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Collaborative Filtering Deep Dive

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Ethics in AI: Bias and Fairness

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AI Privacy and Security

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Explainable AI (XAI)

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ML Engineering: The Pipeline

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MLOps: Deployment

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Model Monitoring and Maintenance

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Cloud AI Services: AWS

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Cloud AI Services: Google Cloud

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Cloud AI Services: Azure

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Edge AI and Mobile Deployment

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Graph Neural Networks (GNNs)

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Bayesian Neural Networks

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Self-Supervised Learning

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72

AI in Healthcare

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AI in Finance

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AI in Robotics

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Autonomous Vehicles

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AI for Sustainability

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Creative AI: Music and Art

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Multi-modal AI

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Prompt Engineering Mastery

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Fine-tuning LLMs

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Vector Databases

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Retrieval Augmented Generation (RAG)

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AI Agents and Autonomy

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Evaluation of LLMs

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85

Data Labeling and Annotation

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Anomaly Detection

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Advanced Time Series: Transformers

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Neuro-Symbolic AI

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Quantum Machine Learning

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Distributed Training

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Advanced Optimization: Adam and Beyond

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Loss Landscapes and Sharpness

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Neural Architecture Search (NAS)

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Federated Learning Deep Dive

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95

AI Governance and Compliance

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96

Feature Stores for ML

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Model Pruning and Quantization

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98

Active Learning Strategies

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99

Time Series: Fourier and Wavelet Transforms

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100

AI in Retail and Supply Chain

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101

AI for Cybersecurity

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102

Natural Language Understanding (NLU)

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103

Natural Language Generation (NLG)

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104

Practical Project: House Price Prediction

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Practical Project: Sentiment Analysis

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106

Practical Project: Image Classifier

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107

Practical Project: Customer Churn

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108

Practical Project: Document Summarizer

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109

Practical Project: Fraud Detection

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110

AI Career: Roles and Skills

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111

The AI Interview: Technical

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112

The AI Interview: Case Studies

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113

Building an AI Portfolio

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114

AI Product Management

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115

Freelancing in AI

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116

Research in AI

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117

Staying Current in AI

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118

AI Regulations and Law

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119

AI Strategy for Business

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120

Final Capstone Project

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