Dealing with Missing Data in Python
Learn how to identify, analyze, remove and impute missing data in Python.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
Learn how to identify, analyze, remove and impute missing data in Python.
Learn how to use Python to analyze customer churn and build a model to predict it.
Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.
Learn about risk management, value at risk and more applied to the 2008 financial crisis using Python.
Prepare for your next coding interviews in Python.
Learn efficient techniques in pandas to optimize your Python code.
This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.
Use your knowledge of common spreadsheet functions and techniques to explore Python!
Build multiple-input and multiple-output deep learning models using Keras.
Learn how to prepare credit application data, apply machine learning and business rules to reduce risk and ensure profitability.
Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.
Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.
Create interactive data visualizations in Python using Plotly.
Learn how to build interactive and insight-rich dashboards with Dash and Plotly.
Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.
Learn fundamental probability concepts like random variables, mean and variance, probability distributions, and conditional probabilities.
Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.
Learn the practical uses of A/B testing in Python to run and analyze experiments. Master p-values, sanity checks, and analysis to guide business decisions.
Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.
Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.
This course will show you how to integrate spatial data into your Python Data Science workflow.
In this course, you'll learn how to import and manage financial data in Python using various tools and sources.
Learn about ARIMA models in Python and become an expert in time series analysis.
Learn techniques to extract useful information from text and process them into a format suitable for machine learning.
Learn to perform linear and logistic regression with multiple explanatory variables.
Learn to tune hyperparameters in Python.
In this course, you'll learn the basics of relational databases and how to interact with them.
Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.
Learn to manipulate and analyze flexibly structured data with MongoDB.
Learn how to approach and win competitions on Kaggle.