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Learn Applied Analytics, earn certificates with paid and free online courses from Stanford, MIT, University of Pennsylvania, University of Michigan and other top universities around the world. Read reviews to decide if a class is right for you.
Through inspiring examples and stories, discover the power of data and use analytics to provide an edge to your career and your life.
Prepare business data for analysis in Python: filter and explore pandas DataFrames, apply tidy data principles, fix missing values, and work in JupyterLab or Colab.
Learn how data analysts describe, predict and inform business decisions across customer, operations, people and accounting analytics, then interpret a data set to recommend business strategy.
Due to python’s simplicity and high readability, it is gaining its importance in the financial industry. The course combines both python coding and statistical concepts and applies into analyzing financial data, such as stock data.
Build data analytics skills with Excel, SQL, ETL, Tableau, Power BI, Python and R, then apply generative AI, data ethics and Azure data fundamentals in a capstone.
Apply analytics to business problems: group observations for efficiency, model credit scoring and employee attrition, forecast with survival analysis and seasonality, then pitch actionable recommendations.
Business analytics is one of the highest-impact, most in-demand skills. This course will introduce you to some basic concepts and terms that you'll need to step into business analytics.
Apply analytics and AI to management decisions: analytics tools and techniques, advanced analytics, Gen AI-powered business case studies, privacy, ethics and risk, plus a capstone project.
Learn to collect, analyze, and visualize business data with Power BI, Alteryx, and RStudio, applying machine learning and analytics to marketing, accounting, and strategic decisions.
Apply statistical techniques in R to business cases: forecast events, segment customers, compute customer scores and lifetime value, and present insights to stakeholders.
Learn essential analytics models and methods and how to appropriately apply them, using tools such as R, to retrieve desired insights.
How to Build a Profitable and Winning Company Using Business Analytics
Analyze financial loan data end to end: clean missing values and outliers, classify loans and predict defaults, allocate funds with clustering and simulation-based optimization, then present findings.
Build an analytics toolkit for digital transformation: work through predictive analytics, simulation, and prescriptive analytics with Python exercises and case studies.
Apply R to business analytics projects: detect fraud, analyze marketing performance with R and Excel, and model HR attrition using feature selection and predictive validation.
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