Linear Algebra for Data Science in R
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
This course is an introduction to linear algebra, one of the most important mathematical topics underpinning data science.
Learn about Microsoft Copilot and 365 Copilot to enhance productivity, streamline workflows, and make informed, data-driven decisions in your business.
Learn to model and predict stock data values using linear models, decision trees, random forests, and neural networks.
Master the key concepts of data management, from life cycle stages to security and governance.
Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.
Leverage the power of tidyverse tools to create publication-quality graphics and custom-styled reports that communicate your results.
Evaluate portfolio risk and returns, construct market-cap weighted equity portfolios and learn how to forecast and hedge market risk via scenario generation.
Discover different types in data modeling, including for prediction, and learn how to conduct linear regression and model assessment measures in the Tidyverse.
In this course you will learn how to predict future events using linear regression, generalized additive models, random forests, and xgboost.
Learn cutting-edge methods for integrating external data with LLMs using Retrieval Augmented Generation (RAG) with LangChain.
Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.
Create interactive data visualizations in Python using Plotly.
Learn the fundamentals of data visualization using Google Sheets.
To understand Fabric’s main use cases, you will explore various tools in the seven Fabric experiences.
Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.
Learn the fundamentals of how to build conversational bots using rule-based systems as well as machine learning.
Learn about ARIMA models in Python and become an expert in time series analysis.
Learn about how dates work in R, and explore the world of if statements, loops, and functions using financial examples.
Learn all about the advantages of Bayesian data analysis, and apply it to a variety of real-world use cases!
Take your reporting skills to the next level with Tableau’s built-in statistical functions.
Learn the fundamentals of AI security to protect systems from threats, align security with business goals, and mitigate key risks.
Are customers thrilled with your products or is your service lacking? Learn how to perform an end-to-end sentiment analysis task.
Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control
Elevate decision-making skills with Decision Models, analysis methods, risk management, and optimization techniques.
This course will show you how to integrate spatial data into your Python Data Science workflow.
This course provides an intro to clustering and dimensionality reduction in R from a machine learning perspective.
In this course, youll learn how to import and manage financial data in Python using various tools and sources.
Learn how to make attractive visualizations of geospatial data in Python using the geopandas package and folium maps.
Use Seaborns sophisticated visualization tools to make beautiful, informative visualizations with ease.
Shiny is an R package that makes it easy to build interactive web apps directly in R, allowing your team to explore your data as dashboards or visualizations.