Explore data and create models to predict numeric values
Data exploration and analysis is at the core of data science. Data scientists require skills in languages like Python to explore, visualize, and manipulate data. n this module, you will learn how to use Python to explore, visualize, and manipulate data.You will also learn how regression can be used to create a machine learning model that predicts numeric values. You will use the scikit-learn framework in Python to train and evaluate a regression model.
Train and evaluate classification and clustering models
Classification is a kind of machine learning used to categorize items into classes. In this module, you will learn how classification can be used to create a machine learning model that predicts categories, or classes. You will use the scikit-learn framework in Python to train and evaluate a classification model. You will also learn how clustering can be used to create unsupervised machine learning models that group data observations into clusters. You will use the scikit-learn framework in Python to train a clustering model.
Train and evaluate deep learning models
In this module, you will learn about the fundamental principles of deep learning, and how to create deep neural network models using PyTorch or Tensorflow. You will also explore the use of convolutional neural networks to create image classification models.