Analyzing Business Data in SQL
Learn to write SQL queries to calculate key metrics that businesses use to measure performance.
Follow short videos led by expert instructors and then practice what you’ve learned with interactive exercises in your browser.
Learn to write SQL queries to calculate key metrics that businesses use to measure performance.
Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.
Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.
In this course you will learn the details of linear classifiers like logistic regression and SVM.
Discover modern data architectures key components, from ingestion and serving to governance and orchestration.
Learn to process, transform, and manipulate images at your will.
In this four-hour course, you’ll learn the basics of analyzing time series data in Python.
Explore the latest techniques for running the Llama LLM locally, fine-tuning it, and integrating it within your stack.
Learn to clean data as quickly and accurately as possible to help you move from raw data to awesome insights.
Learn to perform linear and logistic regression with multiple explanatory variables.
Find tables, store and manage new tables and views, and write maintainable SQL code to answer business questions.
In this course, you will use T-SQL, the flavor of SQL used in Microsofts SQL Server for data analysis.
Master Power Pivot in Excel to help import data, create relationships, and utilize DAX. Build dynamic dashboards to uncover actionable insights.
Learn to acquire data from common file formats and systems such as CSV files, spreadsheets, JSON, SQL databases, and APIs.
Building on your foundational Power Query in Excel knowledge, this intermediate course takes you to the next level of data transformation mastery
Learn to create your own Python packages to make your code easier to use and share with others.
Master Apache Kafka! From core concepts to advanced architecture, learn to create, manage, and troubleshoot Kafka for real-world data streaming challenges!
Gain the essential skills using Scikit-learn, SHAP, and LIME to test and build transparent, trustworthy, and accountable AI systems.
Leverage the OpenAI API to get your AI applications ready for production.
Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.
Unlock BigQuerys power: grasp its fundamentals, execute queries, and optimize workflows for efficient data analysis.
Learn to start developing deep learning models with Keras.
Learn to write faster R code, discover benchmarking and profiling, and unlock the secrets of parallel programming.
Learn key object-oriented programming concepts, from basic classes and objects to advanced topics like inheritance and polymorphism.
Unlock more advanced AI applications, like semantic search and recommendation engines, using OpenAIs embedding model!
Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.
Create new features to improve the performance of your Machine Learning models.
Learn how to build your own SQL reports and dashboards, plus hone your data exploration, cleaning, and validation skills.
Learn how to perform financial analysis in Power BI or apply any existing financial skills using Power BI data visualizations.
Learn how to design Power BI visualizations and reports with users in mind.