Forecasting Product Demand in R
Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.
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Learn how to identify important drivers of demand, look at seasonal effects, and predict demand for a hierarchy of products from a real world example.
Predict employee turnover and design retention strategies.
Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.
Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.
Learn how to predict click-through rates on ads and implement basic machine learning models in Python so that you can see how to better optimize your ads.
Extract and visualize Twitter data, perform sentiment and network analysis, and map the geolocation of your tweets.
Learn strategies for answering probability questions in R by solving a variety of probability puzzles.
Learn how to analyze business processes in R and extract actionable insights from enormous sets of event data.
Unlock the power of parallel computing in R. Enhance your data analysis skills, speed up computations, and process large datasets effortlessly.
In this course youll learn how to use data science for several common marketing tasks.
Learn to create animated graphics and linked views entirely in R with plotly.
Continue learning with purrr to create robust, clean, and easy to maintain iterative code.
Learn to detect fraud with analytics in R.
Manipulate text data, analyze it and more by mastering regular expressions and string distances in R.
Learn how to write scalable code for working with big data in R using the bigmemory and iotools packages.
Learn to analyze and model customer choice data in R.
Learn statistical tests for identifying outliers and how to use sophisticated anomaly scoring algorithms.
Learn the fundamentals of valuing stocks.
Learn defensive programming in R to make your code more robust.
Master the essential skills of data manipulation in Julia. Learn how to inspect, transform, group, and visualize DataFrames using real-world datasets.
Use C++ to dramatically boost the performance of your R code.
Learn mixture models: a convenient and formal statistical framework for probabilistic clustering and classification.
Learn to predict labels of nodes in networks using network learning and by extracting descriptive features from the network
Master data visualization in Julia. Learn how to make stunning plots while understanding when and how to use them.
Learn to build simple models of market response to increase the effectiveness of your marketing plans.
Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.