DataCamp
DataCamp is an online learning platform that offers courses and tutorials focused on data science, machine learning, and programming. It provides a wide range of interactive courses, projects, and assessments to help individuals learn and enhance their data science skills. DataCamp covers various topics such as data manipulation, data visualization, statistical analysis, machine learning, and more.
The platform offers a hands-on learning experience by providing interactive coding exercises in Python, R, SQL, and other popular programming languages used in data analysis. Learners can practice their skills directly in the browser, which helps them gain practical experience and reinforce their understanding of the concepts.
Learn how to import data into Python from sources like the web and by pulling data from APIs, such as the Twitter streaming API to stream real-time tweets.
Dive in and learn how to create classes and leverage inheritance and polymorphism to reuse and optimize code.
Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.
Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.
Learn the ETL process as well as useful tools and techniques that will help you extract, transform, and load data using Python and SQL.
Discover how to include multiple explanatory variables in a model, how interactions affect predictions, and how linear and logistic regression work in R.
Familiarize yourself with Git for version control. Explore how to track, compare, modify, and revert files, as well as collaborate with colleagues using Git.
Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.
Learn the basics of time series analysis in Python using several models, including autoregressive, moving average, and cointegration.
Learn what Bayesian data analysis is and how to use it for business modeling focusing on cash flows, investments, annuities, and saving for retirement in R
You’ll learn the many ways to read data into Python: from flat files such as CSVs to Excel spreadsheets and relational databases in SQLite & PostgreSQL.
Take your Tableau skills up a notch with advanced analytics and visualizations.
Learn to read .xls, .csv, and text files in R using readxl and gdata, before learning how to use readr and data.table packages to import flat file data.
In this course you will learn the basics of machine learning for classification.
Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.
