Data Analysis Online Courses & Certifications
Data analysis refers to the process of inspecting, cleaning, transforming, and modeling data to uncover useful information, draw conclusions, and support decision-making. It involves applying various techniques and methodologies to explore and make sense of data, extract insights, and derive meaningful conclusions. Data analysis is widely used in various fields, including business, finance, marketing, healthcare, social sciences, and more.
There are numerous tools and software available to support data analysis, ranging from spreadsheet applications like Excel to more advanced statistical packages like R and Python libraries. These tools provide a wide range of functionalities for data manipulation, statistical modeling, and visualization, facilitating the data analysis process.
Course will help to learn how to use SQL for product development and marketing, reduce your dependence on data analysts and solve most typical SQL tasks. You will get hands-on skills working with a marketplace database. You will gather, examine, clean up data, and calculate key metrics to use this information to tackle key product and marketing issues.
This series of three courses is designed to take you through the cycle of data creation and introduce frameworks, resources, and essential Amplitude tools to help you be successful at each step. You will go through the Fundamentals of Data Taxonomy Design, the Instrumenting Your Data Taxonomy, as well as the Data Governance and Maintenance Best Practices courses. The Getting Started with Amplitude Data is not a prerequisite for this learning path; however, the Amplitude Data product will be referenced as a tool where appropriate.
Pandas provides tools for working with tabular data, i.e. data that is organized into tables that have rows and columns. Tabular data has a lot of the same functionality as SQL or Excel, but Pandas adds the power of Python.
Excel is designed as a one-stop shop for storing and analyzing data, with built-in tools to help you transform data of all kinds into business insights. Used for everything from complex financial modeling to tracking shipment orders, knowledge of Excel is foundational to any career in data analysis or business intelligence.
A goal of many analytics projects is to answer “how much did factor x affect the outcome?”, otherwise known as the treatment effect. But it can be very hard to do that with real data because it’s often incomplete. This course will introduce you to two techniques to fix that problem: Regression Discontinuity Design and Instrumental Variables.
Estimate effects by analyzing trends over time.
Learn about calculus, including how to analyze functions using limits and derivatives.
Data is everywhere, and more companies than ever are tracking and analyzing data to inform their decisions. In this Skill Path, you will learn to analyze data statistically and create meaningful data visualizations.
Whatever the task, Microsoft Excel is an incredibly powerful tool that enables you to store and make sense of your data.
Take your Tableau skills up a notch with advanced analytics and visualizations.
Take your reporting skills to the next level with Tableau’s built-in statistical functions.
Learn how to use Power Query Editor in Power BI to transform and shape your data for analysis. Plus, get to grips with numerical transformations in Power BI.
Enhance your reports with Power BI’s Exploratory Data Analysis (EDA). Learn what EDA is for Power BI and how it can help you extract insights from your data.
Learn to connect Tableau to different data sources and prepare the data for a smooth analysis.
Learn how to use dplyr to transform and aggregate data, then add, remove, or change variables. You’ll then apply your skills to a real-world case study.