SQL Server offers powerful native tools for data cleansing. Without using a third-party solution for data cleansing, you can enhance data quality with TSQL. This course will teach you solutions and best practices for data cleaning in SQL Server.

Transactions and error handling are great, but they have some pitfalls that it helps to know about. This course will teach you how to work with transactions and error handling to make your system efficient, well-performing, and observable.

Learn how to design and implement triggers in SQL Server using real-world examples.

BI Data Analysts use Python and SQL to query, analyze, and visualize data — and Tableau and Excel to communicate findings.

An introduction to the intellectual enterprises of computer science and the art of programming.

Prepare for data analyst interviews from job postings to technical interviews.

Messy data and inconsistencies often lead to inaccurate conclusions and missed opportunities. This course will teach you to identify and resolve data inconsistencies, master essential cleansing techniques, and implement optimal maintenance practices.

Master the complex SQL queries necessary to answer a wide variety of data science questions and prepare robust data sets for analysis in PostgreSQL.

Prepare for the data science interview process, from navigating job postings to passing the technical interview.

Data Analysts and Analytics Data Scientists use Python and SQL to query, analyze, and visualize data — and communicate findings.

Inference Data Scientists run A/B tests, do root-cause analysis, and conduct experiments. They use Python, SQL, and R to analyze data.

Good data is central to effective AI applications. This course teaches the basics of data for AI, covering what data is needed, how to extract data from existing databases and basic data skills including setup of a Python notebook environment, basic data exploration and simple data visualizations.