Introduction to Data Quality
Explore the basics of data quality management. Learn the key concepts, dimensions, and techniques for monitoring and improving data quality.
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Explore the basics of data quality management. Learn the key concepts, dimensions, and techniques for monitoring and improving data quality.
Take your Power BI visualizations up a level with the skills you already have. Learn alternative data storytelling techniques to simply building dashboards.
Learn to combine data across multiple tables to answer more complex questions with dplyr.
Learn to write SQL queries to calculate key metrics that businesses use to measure performance.
Data visualization is one of the most desired skills for data analysts. This course allows you to present your findings better using Tableau.
Learn the fundamentals of working with big data with PySpark.
Learn the nuts and bolts of LLMs and the revolutionary transformer architecture they are based on!
Learn to use Google Sheets to clean, analyze, and draw insights from data. Discover how to sort, filter, and use VLOOKUP to combine data.
Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.
Gain a clear understanding of data privacy principles and how to implement privacy and security processes.
In this course youll learn the basics of working with time series data.
Consolidate and extend your knowledge of Python data types such as lists, dictionaries, and tuples, leveraging them to solve Data Science problems.
Discover the fundamental concepts of object-oriented programming (OOP), building custom classes and objects!
Learn the key components of building a strong data culture within an organization.
Learn how to translate business questions to well-formed analytical questions and select the right analytical solutions.
Learn about the world of data engineering in this short course, covering tools and topics like ETL and cloud computing.
Dive into the world of machine learning and discover how to design, train, and deploy end-to-end models.
Discover the different ways you can enhance your Power BI data importing skills.
Understand the fundamentals of Machine Learning and how its applied in the business world.
Learn the essentials of VMs, containers, Docker, and Kubernetes. Understand the differences to get started!
Learn about fundamental deep learning architectures such as CNNs, RNNs, LSTMs, and GRUs for modeling image and sequential data.
Learn how to manipulate and visualize categorical data using pandas and seaborn.
Learn to clean data as quickly and accurately as possible to help you move from raw data to awesome insights.
Build on top of your Python skills for Finance, by learning how to use datetime, if-statements, DataFrames, and more.
Learn how and when to use hypothesis testing in R, including t-tests, proportion tests, and chi-square tests.
Learn to process, transform, and manipulate images at your will.
In this course you will learn the basics of machine learning for classification.
Explore the latest techniques for running the Llama LLM locally, fine-tuning it, and integrating it within your stack.
Learn about modularity, documentation, and automated testing to help you solve data science problems more quickly and reliably.
Dive into the exciting world of APIs as we introduce you to the basics of consuming and working with Web APIs using Python.