Applications in Healthcare, Finance, and Retail

Latest Trends in Artificial Intelligence and Machine Learning

Python Fundamentals (Variables, Data Types, Control Structures, Functions)

NumPy and Pandas (Arrays, DataFrames, Series)

Matplotlib for Data Visualization

TensorFlow Fundamentals (Tensors, Variables, Operations, Graphs)

Neural Networks (Feedforward, Recurrent)

Convolutional Neural Networks (CNNs)

Recurrent Neural Networks (RNNs)

Long Short-Term Memory (LSTM)

Autoencoders

Generative Adversarial Networks (GANs)

Transfer Learning and Word Embeddings

TensorFlow for Deep Learning (Keras API, Model Building)

Linear Regression (Simple, Multiple)

Logistic Regression (Binary, Multinomial)

Decision Trees (Classification, Regression)

Random Forests (Classification, Regression)

Support Vector Machines (SVM – Linear, Non-Linear)

Clustering (K-Means, Hierarchical, DBSCAN)

Principal Component Analysis (PCA)

Anomaly Detection (Isolation Forest, Local Outlier Factor)

Splitting Data & Cross-Validation

Hyperparameter Tuning (Grid Search, Random Search)

Evaluation Metrics (Accuracy, Precision, Recall, F1-Score, ROC, AUC)

Image Classification (CNNs, Transfer Learning)

Sentiment Analysis (RNNs, Word Embeddings), Fraud Detection, Recommender Systems

Ethical AI, Bias Mitigation, Deployment Challenges

Monitoring Models and Ensuring Responsible AI Practices