Data Science with Python :

• Vectors, Matrices, and Arrays
• Data Pre-Processing/Wrangling
• Handling Numerical Data
• Handling Categorical Data
• Handling Text
• Handling Dates and Times
• Handling Images
• Introduction to Data Visualizations and Statistical Data Analysis-Basic
• Statistical Inference & Relationship Between Variables
• Machine Learning for Data Science
• Unsupervised Learning
• Supervised Learning
• Artificial Neural Networks (ANN) and Deep Learning (DL)Loading Data
• Dimensionality Reduction Using Feature Extraction
• Dimensionality Reduction Using Feature Selection
• Model Evaluation, Model Selection
• Linear Regression, Trees and Forests, K-Nearest Neighbours, Logistic Regression
• Support Vector Machines
• Naive Bayes
• Clustering
• Neural Networks
• Saving and Loading Trained Models