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Learn how to design and implement triggers in SQL Server using real-world examples.
Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.
Learn how to access financial data from local files as well as from internet sources.
In this Power BI case study you’ll play the role of a junior trader, analyzing mortgage trading and enhancing your data modeling and financial analysis skills.
Learn to work with time-to-event data. The event may be death or finding a job after unemployment. Learn to estimate, visualize, and interpret survival models!
Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.
Learn survey design using common design structures followed by visualizing and analyzing survey results.
In this course, you’ll learn to classify, treat and analyze time series; an absolute must, if you’re serious about stepping up as an analytics professional.
Learn about GARCH Models, how to implement them and calibrate them on financial data from stocks to foreign exchange.
Become an expert in fitting ARIMA (autoregressive integrated moving average) models to time series data using R.
Learn how to import, clean and manipulate IoT data in Python to make it ready for machine learning.
Learn to analyze financial statements using Python. Compute ratios, assess financial health, handle missing values, and present your analysis.
Learn how to use Python parallel programming with Dask to upscale your workflows and efficiently handle big data.
Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.
Learn how to efficiently collect and download data from any website using R.
Learn to distinguish real differences from random noise, and explore psychological crutches we use that interfere with our rational decision making.
Learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.
Step into the role of CFO and learn how to advise a board of directors on key metrics while building a financial forecast.
Learn the bag of words technique for text mining with R.
Learn how to analyze survey data with Python and discover when it is appropriate to apply statistical tools that are descriptive and inferential in nature.
Learn to use the Census API to work with demographic and socioeconomic data.
Apply statistical modeling in a real-life setting using logistic regression and decision trees to model credit risk.
Take vital steps towards mastery as you apply your statistical thinking skills to real-world data sets and extract actionable insights from them.
Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.
Practice Tableau with our healthcare case study. Analyze data, uncover efficiency insights, and build a dashboard.
Ensure data consistency by learning how to use transactions and handle errors in concurrent environments.
Learn to read, explore, and manipulate spatial data then use your skills to create informative maps using R.
Learn how to pull character strings apart, put them back together and use the stringr package.