Introduction to Network Analysis in Python
This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
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By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.
Learn how to build advanced and effective machine learning models in Python using ensemble techniques such as bagging, boosting, and stacking.
Learn how to work with streaming data using serverless technologies on AWS.
Use Seaborns sophisticated visualization tools to make beautiful, informative visualizations with ease.
In this course, students will learn to write queries that are both efficient and easy to read and understand.
Visualize seasonality, trends and other patterns in your time series data.
Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.
Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.
Use RNA-Seq differential expression analysis to identify genes likely to be important for different diseases or conditions.
Help a fictional company in this interactive Power BI case study. You’ll use Power Query, DAX, and dashboards to identify the most in-demand data jobs!
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.
Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.
Learn how to ensure clean data entry and build dynamic dashboards to display your marketing data.
Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.
In this case study, you’ll use visualization techniques to find out what skills are most in-demand for data scientists, data analysts, and data engineers.
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.
Orchestrate data using unions, joins, parsing, and performance optimization in Alteryx.
Learn how to detect fraud using Python.
Analyze text data in R using the tidy framework.
You will use Net Revenue Management techniques in Excel for a Fast Moving Consumer Goods company.
Using Python and NumPy, learn the most fundamental financial concepts.
Explore Power BI Service, master the interface, make informed decisions, and maximize the power of your reports.
Master SQL Server programming by learning to create, update, and execute functions and stored procedures.
Explore ways to work with date and time data in SQL Server for time series analysis
Advance your Java skills by learning to handle files, process data, and build clean, reusable code using real-world techniques.
Learn to manipulate and analyze flexibly structured data with MongoDB.
In this course, youll learn how to import and manage financial data in Python using various tools and sources.
Learn powerful command-line skills to download, process, and transform data, including machine learning pipeline.
Solidify your decision science skills by designing data-informed frameworks and implementing efficient solutions.
Learn to tame your raw, messy data stored in a PostgreSQL database to extract accurate insights.