Statistical Thinking in Python (Part 1)
Build the foundation you need to think statistically and to speak the language of your data.
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By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.Build the foundation you need to think statistically and to speak the language of your data.
Learn how to leverage statistical techniques using spreadsheets to more effectively work with and extract insights from your data.
In this Introduction to DevOps, you’ll master the DevOps basics and learn the key concepts, tools, and techniques to improve productivity.
Discover how to make better business decisions by applying practical data frameworks—no coding required.
Conquer NoSQL and supercharge data workflows. Learn Snowflake to work with big data, Postgres JSON for handling document data, and Redis for key-value data.
Build up your pandas skills and answer marketing questions by merging, slicing, visualizing, and more!
Understand the concept of reducing dimensionality in your data, and master the techniques to do so in Python.
Discover how Marketing Analysts use data to understand customers and drive business growth.
You will investigate a dataset from a fictitious company called Databel in Tableau, and need to figure out why customers are churning.
Build your OOP skills with descriptors, multilevel inheritance, and abstract base classes!
Discover the exciting world of Deep Learning for Text with PyTorch and unlock new possibilities in natural language processing and text generation.
R Markdown is an easy-to-use formatting language for authoring dynamic reports from R code.
In this course, you’ll explore the modern MLOps framework, exploring the lifecycle and deployment of machine learning models.
Master the key concepts of data management, from life cycle stages to security and governance.
Learn how to build intelligent agents that reason, act, and solve real-world tasks using Python.
Master data preparation, cleaning, and analysis in Alteryx Designer, whether you are a new or seasoned analyst.
Explore AI and data monetization strategies, build ethical infrastructures, and align products with business goals.
Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.
Expand your Google Sheets vocabulary by diving deeper into data types, including numeric data, logical data, and missing data.
In this conceptual course (no coding required), you will learn about the four major NoSQL databases and popular engines.
Learn the fundamentals of data visualization using Google Sheets.
Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control
Learn how to make predictions from data with Apache Spark, using decision trees, logistic regression, linear regression, ensembles, and pipelines.
Learn how to work with Claude using the Anthropic API to solve real-world tasks and build AI-powered applications.
Understand the role and real-world realities of Explainable Artificial Intelligence (XAI) with this beginner friendly course.
Learn techniques for automated hyperparameter tuning in Python, including Grid, Random, and Informed Search.
Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.
Learn to create your own Python packages to make your code easier to use and share with others.
Learn to use the KNIME Analytics Platform for data access, cleaning, and analysis with a no-code/low-code approach.
Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.