Market Basket Analysis in Python
Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.
Explore association rules in market basket analysis with Python by bookstore data and creating movie recommendations.
Learn how to create a range of visualizations in Excel for different data layouts, ensuring you incorporate best practices to help you build dashboards.
Learn to use essential Bioconductor packages for bioinformatics using datasets from viruses, fungi, humans, and plants!
Learn to use Python for financial analysis using basic skills, including lists, data visualization, and arrays.
Explore association rules in market basket analysis with R by analyzing retail data and creating movie recommendations.
Explore ways to work with date and time data in SQL Server for time series analysis
Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.
Learn to analyze, plot, and model multivariate data.
An introduction to data science with no coding involved.
Understand how to prepare Excel data through logical functions, nested formulas, lookup functions, and PivotTables.
Elevate your data storytelling skills and discover how to tell great stories that drive change with your audience.
Master core concepts about data manipulation such as filtering, selecting and calculating groupwise statistics using data.table.
In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.
Enhance your reports with trend analysis techniques such as time series, decomposition trees, and key influencers.
Transform almost any dataset into a tidy format to make analysis easier.
Learn to analyze and visualize network data with the igraph package and create interactive network plots with threejs.
Develop a strong intuition for how hierarchical and k-means clustering work and learn how to apply them to extract insights from your data.
Explore latent variables, such as personality, using exploratory and confirmatory factor analyses.
Use survival analysis to work with time-to-event data and predict survival time.
In this four-hour course, you’ll learn the basics of analyzing time series data in Python.
Learn the core techniques necessary to extract meaningful insights from time series data.
Learn to analyze data over time with this practical course on Time Series Analysis in Power BI. Work with real datasets & practice common techniques.
Learn the fundamentals of exploring, manipulating, and measuring biomedical image data.
Learn to use the Bioconductor package limma for differential gene expression analysis.
Learn how to use PostgreSQL to handle time series analysis effectively and apply these techniques to real-world data.
In this course, you will learn to read CSV, XLS, and text files in R using tools like readxl and data.table.
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.
Learn how to calculate meaningful measures of risk and performance, and how to compile an optimal portfolio for the desired risk and return trade-off.
This Power BI case study follows a real-world business use case on tackling inventory analysis using DAX and visualizations.
In ecommerce, increasing sales and reducing costs are key. Analyze data from an online pet supply company using Power BI.
In ecommerce, increasing sales and reducing expenses are top priorities. In this case study, you'll investigate data from an online pet supply company.
Apply your finance and R skills to backtest, analyze, and optimize financial portfolios.
Learn how to visualize time series in R, then practice with a stock-picking case study.
Enhance your Tableau skills with this case study on inventory analysis. Analyze a dataset, create calculated fields, and create visualizations.
Apply fundamental concepts in network analysis to large real-world datasets in 4 different case studies.
This Power BI case study follows a real-world business use case where you will apply the concepts of ETL and visualization.
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.
Learn to conduct image analysis using Keras with Python by constructing, training, and evaluating convolutional neural networks.
Learn how to manipulate data and create machine learning feature sets in Spark using SQL in Python.
Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.
Explore Excel Power Query for advanced data transformation and cleansing to boost your decision-making and analysis.
Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.
Learn to analyze and model customer choice data in R.
Learn how to analyse and interpret ChIP-seq data with the help of Bioconductor using a human cancer dataset.
Learn about Excel financial modeling, including cash flow, scenario analysis, time value, and capital budgeting.
Master sampling to get more accurate statistics with less data.
Get hands-on experience making sound conclusions based on data in this four-hour course on statistical inference in Python.
Learn about AWS Boto and harnessing cloud technology to optimize your data workflow.
Learn how to draw conclusions about a population from a sample of data via a process known as statistical inference.