Analyzing Financial Statements in Python
Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.
Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.
Advance you R finance skills to backtest, analyze, and optimize financial portfolios.
Learn tools and techniques to leverage your own big data to facilitate positive experiences for your users.
Dive into the world of digital transformation and equip yourself to be an agent of change in a rapidly evolving digital landscape.
Diagnose, visualize and treat missing data with a range of imputation techniques with tips to improve your results.
Learn to use the Census API to work with demographic and socioeconomic data.
Learn how to manipulate, visualize, and perform statistical tests through a series of HR analytics case studies.
Learn how to create and assess measurement models used to confirm the structure of a scale or questionnaire.
Learn how to produce interactive web maps with ease using leaflet.
Learn to develop R packages and boost your coding skills. Discover package creation benefits, practice with dev tools, and create a unit conversion package.
Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.
Learn how to create interactive data visualizations, including building and connecting widgets using Bokeh!
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.
Learn to set up a secure, efficient book recommendation app in Azure in this hands-on case study.
Learn efficient techniques in pandas to optimize your Python code.
Learn how to use plotly in R to create interactive data visualizations to enhance your data storytelling.
Learn how to visualize time series in R, then practice with a stock-picking case study.
In this course, youll prepare for the most frequently covered statistical topics from distributions to hypothesis testing, regression models, and much more.
In this course youll learn how to use data science for several common marketing tasks.
This course is for R users who want to get up to speed with Python!
Learn to build pipelines that stand the test of time.
Learn to use the Bioconductor package limma for differential gene expression analysis.
Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.
Strengthen your knowledge of the topics covered in Manipulating Time Series in R using real case study data.
This course will introduce the support vector machine (SVM) using an intuitive, visual approach.
Use survival analysis to work with time-to-event data and predict survival time.
Learn the basics of A/B testing in R, including how to design experiments, analyze data, predict outcomes, and present results through visualizations.
Learn to use R to develop models to evaluate and analyze bonds as well as protect them from interest rate changes.
Use generative AI to tackle data cleaning, fixing duplicates, nulls, and formatting for consistent, accurate datasets.