Best Free Data Resources & Tutorials

Interested in data analysis and data science but worried about the cost? Discover a wealth of free resources available to help beginners learn invaluable skills, including free tools like Google Analytics, Tableau Public, and Python, plus free trials and online classes.

Key Insights

  • Committing to learning data skills doesn't have to be costly. Free resources are available for beginners to help build foundational knowledge and pinpoint specific areas of interest.
  • Several free data tools like Tableau Public, Google Analytics, and Python are freely available and can help in fostering necessary data skills.
  • There's also the option to utilize free trials of paid data tools like Microsoft Excel, providing the opportunity to practice hands-on projects and explore the tool's features.
  • Free online data training courses are accessible on a wide array of subjects. Noble Desktop’s Learning Hubs, for example, offer a range of free resources and allow comparison of different data training options.
  • Data-centric careers such as Data Analysts, Data Scientists, Machine Learning Engineers, and Marketing Analysts are in high demand due to the important role data plays in businesses' efficiency and growth.
  • With expertise in data analytics and data science, you can potentially pursue high-demand jobs including Python Engineers, Data Journalists, Data Engineers, and Business Analysts.

Many professionals are eager to learn data but hesitant to commit because of the perceived upfront costs. Some data tools require a monthly subscription fee, and classes might appear too expensive, especially if you plan to enroll in more than one. However, a surprising amount of free resources are available to help beginners learn data analytics and data science skills. Free resources include free tools, free trials, and free online classes you can use to start your data-training journey.

Read on to learn more about the free resources and tutorials available to help you learn data. 

What is Data?

Data refers to facts and statistics collected for reference or analysis. Data allows businesses to track finances, marketing campaigns, market share, efficiency, and more. Today, data management systems can sort complex data from numerous sources using artificial intelligence and machine learning, giving businesses unparalleled insights. Some data management systems can also make future projections based on existing data. These forecasts assist businesses in planning budgets, setting goals, determining deadlines, and more.

We all use data daily, but some professions specialize in gathering, analyzing, storing, and managing data. These careers include Data Analysts, Data Scientists, Machine Learning Engineers, Business Intelligence Analysts, Data Architects, Marketing Analysts, Business Systems Analysts, and more. Whether you wish to pursue one of these careers or simply want to understand the data systems and strategies that impact your business, online and in-person classes can teach you valuable skills. 

Read more about what data is and why you should learn it. 

What Can You Do with Data?

Data Analytics Certificate: Live & Hands-on, In NYC or Online, 0% Financing, 1-on-1 Mentoring, Free Retake, Job Prep. Named a Top Bootcamp by Forbes, Fortune, & Time Out. Noble Desktop. Learn More.

Data has nearly endless uses. Data measures the effectiveness of marketing campaigns, determines budgets, forecasts company growth, and highlights industry trends, trends within an organization, and more. Understanding data science and data analytics can help business owners better manage their organizations, help marketing teams become more efficient and effective, assist business leaders in determining goals, or help launch your career as a Data Analyst or Data Scientist. 

Data science jobs include Python Engineers, Data Journalists, Data Engineers, Business Analysts, and more. Data Scientists create machine learning models that help process raw data, giving a company better insights. Analysts interpret and track this data to continuously improve processes. Data helps organizations make the most of every minute and every dollar, which is one reason Data Scientists and Data Analysts are in such high demand.

Free Data Tools

Some of the most popular and valuable data analytics and data science tools are available at no cost. Free tools include Google Analytics, Tableau Public, and Power BI Desktop. You can also use Python, a programming language used by Data Scientists and Data Analysts for multiple tasks, at no cost. For paid tools like Microsoft Excel, you can use a free trial period to learn the software. 

Google Analytics is a free tool used to track web and app traffic and is popular with more than just Data Analysts. Marketers, Business Owners, and anyone else who tracks website data can use this data tool. Google Analytics reveals the behavior patterns of your website and app visitors. Data on this behavior can help you improve webpages to keep visitors engaged for extended periods, learn what sources (such as a social media campaign) increase web traffic, and how many users convert into leads or paying customers. You can also study the demographic information collected about your visitors and run reports. 

Tableau is a business-intelligence data visualization software. Using this software can prove expensive if you go for the paid options, which range from around $40 to $70 per user per month. You can save money using the free version of Tableau, which is known as Tableau Public. You must create an account and download the Tableau Public desktop application to use Tableau Public. All workbooks and data you use in Tableau Public must be publicly accessible, all data must be extracts, and you have a limit of one million rows. You can also only connect to local data. All work is saved to the public Tableau server. While Tableau Public doesn’t have all the bells and whistles included in the paid versions, it provides plenty of features for getting started. You can use Tableau Public for as long as you wish, ensuring you have access throughout your data training process. 

Microsoft Power BI provides business insights, reporting features, and data visualization tools. This software is part of the Microsoft Power Platform, which includes tools such as Power Automate and Power Virtual Agents. The Power BI Desktop version is free for anyone to use. So, you can learn fundamental Power BI skills and gain hands-on experience without paying the $10-20 monthly fee required for paid Power BI plans.

Many Data Analysts and Data Scientists also rely on the Python programming language for data visualizations, automation, and machine learning. Because Python is an open-source coding language that is free and available to the public, you can use its libraries, framework, and other tools for free. You will also find a wealth of free resources for using Python, including documentation and tutorials. The nonprofit Python Software Foundation manages Python. You can download the latest version of Python, join the Python programming community, read documentation and learning guides, and more on their website.

Microsoft Excel is one of the most well-known and popular data tools. However, it does require a paid Microsoft 365 subscription. You can use the free trial period to explore Excel’s uses and features. To make the most of this trial period, gain hands-on experience by completing exercises and testing Excel’s functions. Hands-on experience reinforces what you learn and is especially useful to kinesthetic or tactile learners who learn by doing.

Free Data Classes

Before committing to a paid class, you should explore different topics for free to help build foundational skills and narrow down what skills and tools you want to learn. You can find free data classes on all sorts of topics, including data science fundamentals, an overview of Python programming, how to use data tools like Microsoft Excel, and more. 

You can gain a high-level overview of data science with Noble Desktop’s free video course, Get Started in Data Science. You can also explore other free video classes included in the Python, Data Science, & SQL YouTube playlist.

Noble also has Learning Hubs for specific data tools and skills, including Tableau, SQL, Excel, and Python. Find dozens of data learning resources in one place and explore different data training options with Noble Desktop’s Data Learning Hub.

Key Insights

  • Learning data might initially be an expensive venture. But you can explore free data training resources to build foundational skills, further your knowledge, and determine your areas of interest.
  • Free data tools include Tableau Public, Google Analytics, Python programming tools, and Power BI Desktop. These tools are always free and publicly available.
  • You can use a free trial of a paid data tool such as Microsoft Excel to practice hands-on projects and explore the functions and features of the tool. This option benefits kinesthetic/tactile learners, who learn best by doing.
  • You can find free data training courses online for many subjects. Noble Desktop’s Learning Hubs provide free resources and let you compare many different options for data training.

Learn Data with Hands-on Training at Noble Desktop

Noble Desktop offers hands-on training in data science and data analytics. These courses are led by expert instructors and include hands-on projects, small class sizes, and free retake options. Noble offers a Data Analytics Certificate and Data Science Certificate. Both certificate programs include one-on-one mentoring, setup assistance, flexible payment options, and career preparation. 

You can also focus on learning specific data science or analytics skills through classes and bootcamps. Learn how to write SQL queries, join tables, aggregate data, and filter results with SQL Bootcamp. The Tableau for Data Visualization course shows you how to convert raw data into interactive visualizations. 

You can explore data analytics and data science training options here.

How to Learn Data

Master data analytics, data science, and data visualization with hands-on training. Learn tops tools for working with data, including Python for data science and software like Excel, Tableau, and SQL.

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