To get an understanding of data, you need to analyze it using a variety of different techniques. This course delves into the use of SQL queries, and especially visualizations and dashboards to identify patterns and trends in data.

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

Master sampling to get more accurate statistics with less data.

This course covers the important considerations for scikit-learn models in improving prediction latency and throughput; specific feature representation and partial learning techniques, as well as implementations of incremental learning, out-of-core learning, and multicore parallelism.

Learn how to build and evaluate machine learning models using scikit-learn, from data preprocessing to model selection and evaluation.

R is a widely used programming language for statistical computing. This course will teach you the fundamentals of scraping data from the web with R.

In this course, you will gain the ability to scrape web pages for data with the R programming language. You'll learn about the web scraping workflow along with Rvest, which is a web scraping package for R.

Elasticsearch is a popular enterprise search engine, which allows you to build powerful search capability. This course focuses on understanding search components and algorithms from first principles, and applying these in practice using REST APIs.

This course will cover all the tips, tricks, and nuances that are related to text searches and text indices.

Data warehouse in Microsoft Fabric is a comprehensive platform for data and analytics, featuring advanced query processing and full transactional T-SQL capabilities for easy data management and analysis.

Secure coding guide for Developers, Analysts and Architects

In this course, we’ll learn how to make predictions on sequences of data.