How to Learn Data

Professionals use data daily to track marketing campaigns, budgets, sales, and more. Data Scientists and Data Analysts use more complex data skills and tools to gather, manage, and review large amounts of data. The trends and opportunities that data highlight provide crucial insights into a company’s health and success. The number of options for learning data might be overwhelming at first glance. There are books, video tutorials, classes, and more to choose from; it all depends on your learning style and personal preferences. 

Here, we’ll discuss the various methods of learning data so you have the information you need to decide how you’d like to get started.

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 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.

In-Person Data Training

In-person data analytics and data science training occurs at a physical location where you learn face-to-face with an expert instructor. You also network with local professionals such as your teacher and classmates. In-person classes can be one of the best ways to learn data due to the guidance you receive from an instructor and the networking opportunities the class presents. The main drawbacks of in-person classes are their cost, the requirement to find a class time that works with your schedule, and the need to commute to the classroom location. Classes that meet on evenings and weekends can help students learn outside of regular office hours. Flexible payment plans can also ease the burden of financing an in-person class upfront.

In-person data training options will depend on your location. You can use the Noble Desktop Classes Near Me tool to find data classes in your area. Major metropolitan areas such as New York City have several in-person data science and data analytics classes, including Noble Desktop’s classes. NYIM Training offers classes on specific data tools such as Excel and Tableau. Flatiron School’s Data Science Bootcamp meets in NYC, Chicago, Seattle, D.C., San Francisco, and Houston. Programs like General Assembly’s Data Science Immersive have in-person classes in cities worldwide, including London, Paris, Melbourne, and Toronto. The Classes Near Me tool can help you research your local options wherever you are located.

Live Online Data Training

Live online data training includes many benefits of in-person training with a few additional perks. Expert instructors lead live online classes. Using a webcam and online learning portal, you get face-to-face interaction and real-time feedback comparable to an in-person class, but without the commute. Remote access maximizes your class scheduling options. Want to take a London class from your home in Chicago? You can do that. Need to access your class while on the road? All you need is your computer and an internet connection. Live online classes also provide the ability to collaborate with classmates and receive instructor guidance on hands-on projects. Hands-on experience is crucial to mastering data analytics and data science skills. The main drawbacks of live online classes are the tuition cost and that you will not have the same local networking opportunities offered with an in-person class. Flexible financing options and one-on-one mentorship help compensate for these issues.

You will want to compare different schools and courses to find the live online data class that’s best for you. Noble Desktop’s Classes Near Me tool lets you explore and compare live online data classes worldwide. Considerations to keep in mind include class meeting times, the cost of tuition, financing options, alumni outcomes, part-time vs. full-time enrollment, and whether the program includes additional benefits such as mentorship and job search assistance. You will also want to consider if a short-term class, a bootcamp, or an immersive program best fits your needs. Noble Desktop offers data science bootcamps like the Python Machine Learning Bootcamp and Python for Data Science Bootcamp. You can also look into immersive programs such as Noble’s Data Analysis Certificate program. NYC Data Science Academy offers online classes in machine programming with R, big data with Amazon Cloud, and data science with Python. Digital Workshop Center and NYIM Training offer courses on valuable tools like Excel. You can explore these and dozens of other class options with the Classes Near Me tool.

Free Online Courses & Tutorials

If you aren’t ready to dive into an entire course and want to begin with an overview of data, you can begin with free introductory data courses online. Noble Desktop offers a free online seminar to get you started in data science. You can watch this video on demand at any time. 

Paid learning platforms like Udemy and Coursera offer a free trial during which you can start data classes. You can view video courses on data science, data analytics, machine learning, SQL, Tableau, Excel, and more.

Read about more free data videos and online tutorials.

On-Demand Data Classes

On-demand classes, also known as self-paced or asynchronous classes, are courses you can progress through at your own pace, on your own schedule. Classes may consist entirely of pre-recorded videos and preloaded material or may include some time-sensitive work, such as assignments due at the end of each week. Most on-demand classes consist primarily of video content supplemented with downloadable materials. You can find these sorts of classes on paid learning platforms like Udemy, Coursera, and LinkedIn Learning. You can also find some free on-demand courses, which typically introduce a subject or provide a broad overview. 

On-demand courses work well for exploring less complex topics or topics you may have some familiarity with. However, the more complex a topic, the more challenging an on-demand course can prove. Lack of access to an instructor can leave students trying to figure things out on their own, which is both frustrating and time-consuming.

Explore Noble Desktop’s list of on-demand data classes to learn more about the types of available data training options. 

Which Learning Method is Right for Me?

With so many different resources available to help beginners learn data, you might need clarification on which one is best for you. Everyone has different learning styles and preferences, and you can experiment with multiple tools to see which one feels right for you. One of the great things about directing your learning is that you pick which combination of tools you prefer; you don’t have to stick with what a teacher chooses.

It’s also essential to consider your current schedule before selecting a learning method. If you have a lot of responsibilities, like a full-time job or family commitments, you may not be able to devote time to a structured course that requires you to attend at the same time every day. In this case, a self-paced class or video tutorials may be better since you can access them when your schedule allows. On the other hand, those with a more flexible schedule may prefer a structured course offered in-person or live online.

What Type of Learner are You? 

Choosing the best data training method for your needs involves knowing how you learn best. Are you a visual, auditory, or kinesthetic learner? Visual learners retain information by seeing. Auditory learners prefer to hear information. Kinesthetic learners, also known as tactile learners, learn best by doing. Most people do not fall neatly into just one category, instead benefitting from a combined learning approach. Still, knowing which of these learning styles you prefer can help you choose the proper data training format.

Visual and auditory learners benefit from video content as they can replay the material however often they please. Visual learners can observe data visualizations like graphs, charts, and infographics to help retain information. Auditory learners can listen to lectures and information, rewinding to any point they wish to hear again. On-demand classes like those found on Udemy, LinkedIn Learning, and Coursera consist primarily of video material. There are also free video courses available on YouTube. Such video classes can prove especially beneficial for visual and auditory learners in the beginning stages. However, as data skills and tools grow increasingly complex, video courses may no longer suffice. These on-demand and video courses lack access to an instructor, so students have to figure out the answers to any questions themselves. On-demand classes may also contain outdated information, as some are not regularly updated.

In-person and live online classes allow visual and auditory learners to observe lectures and video demonstrations in real time. Access to an instructor means having your questions answered without delay and receiving immediate, personalized feedback. Visual and auditory learners also need not choose between video and instructor-led courses. Between your real-time classes, you can use videos to supplement your knowledge, allowing you to learn faster and in your own way.

For kinesthetic/tactile learners, nothing beats a class that includes hands-on experience. In-person classes often serve kinesthetic learners best by placing them in a physical learning environment with all the necessary equipment. However, live online classes that include hands-on projects also provide tactile learners with first-hand experience so they can learn by doing. Both options include real-time access to an instructor who will guide you through assignments step-by-step.

Benefits and Drawbacks of Each Learning Method

The three primary means of learning data are on-demand/self-paced online, in-person, and live online classes. Each learning method has benefits, challenges, and drawbacks. Understanding each learning method’s advantages and limitations will help you determine which learning method or combination best fits your needs.

On-demand/self-paced classes, sometimes called asynchronous classes, consist of prerecorded videos and mostly static/unchanging course content. You can access these classes by paying a monthly subscription to an online learning platform like Udemy, LinkedIn Learning, or Coursera. The benefits of on-demand classes include the following:

• You can learn on your schedule. There are no scheduled class times.
• You can advance at your own pace.
• You can rewatch videos and review class material as often as you wish.
• Visual learners and those that learn by reading benefit from visual materials like videos and transcripts.
• Affordability. On-demand class subscriptions start at around $30 per month.
• Exercises. Some courses include downloadable templates and assignments kinesthetic learners can use to gain hands-on experience.
• Some instructor access. Classes may allow students to email an instructor or meet with an instructor at specified times, providing a means of having questions answered.
• The range of topics. You can find an on-demand class covering almost any data subject you can imagine.

Some drawbacks of the on-demand/self-paced learning method include the following: 

• Lack of instructor access. Some on-demand classes offer no access to an instructor at all. Those that do may only offer limited office hours or email support, leaving students to sit with their questions for hours or days, impeding their progress and causing frustration.
• Lack of hands-on projects. Classes may include downloadable exercises you can follow along with, but without access to an instructor, the benefit is limited. On-demand courses remain largely static, which means hands-on projects may not reflect the latest advances in the industry and may lack variety.
• Due to the static nature of self-paced class content, an on-demand class may include outdated information.
• One-size-fits-all. The one-size-fits-all approach of on-demand classes means you are not receiving information personalized to your career path, learning style, or interests.

In-person classes are conducted at a physical location in your local area. An expert instructor guides the class through lectures and hands-on projects. Benefits of the in-person learning method include the following: 

• Local networking. Only an in-person class can connect you with local professionals, including your instructor and classmates. These connections can help you advance your career or find a job in a new field.
• Equipment access. Many in-person classes will provide computers with the necessary software and tools for learning data skills.
• Hands-on experience. In-person classes allow you to collaborate with classmates and gain first-hand experience organizing data, creating visualizations, and more.
• Portfolio creation: The projects you complete become part of your professional portfolio, showcasing your data skills to prospective employers.
• Mentoring. Some in-person classes include one-on-one mentoring. 
• Job assistance: Some in-person classes include resume reviews and other job training benefits to help you start your new career.
• Small class sizes. In-person classes often consist of 15 students or less, so you receive individualized attention from your instructor.
• Evening and weekend classes. Many in-person classes meet on evenings and weekends so students with day jobs can attend after the workday or on days off.
• Combined learning approach. Most people benefit from a combined learning approach. In-person classes provide this by supplementing lectures and demonstrations with hands-on projects.
• Real-time feedback and instruction. You get personalized, instant feedback on your work with an instructor in the room. You also have an expert available to answer your questions as they come up.

The drawbacks of in-person classes are the cost, the schedule, the topics covered, and the need to commute. In-person classes can cost several thousands of dollars, though flexible payment plans make this easier to pay over time. Because classes meet at specific times, you may have limited choices when finding a class that fits your schedule. You will also be limited to local course offerings regarding the topics covered. Finally, in-person classes require you to commute to the class location, which wastes additional time. 

Live online classes offer all of the benefits of in-person classes with two exceptions: you will not necessarily network with local professionals through an online class since students and teachers can join from anywhere in the world. You will need to use your own computer and tools to complete assignments. Live online classes often cost the same as in-person classes but come with some distinct advantages: 

• Remote learning. You can learn from home or wherever you choose with live online classes, so there is no commute. 
• Maximal options. Since you can take courses offered anywhere in the world, you have the broadest possible selection in choosing a class time and topic that fits your needs.
• Free retake. Look for a live online class that includes a free retake. This way, you can review any part of the class you want to gain a deeper understanding.
• Part-time and full-time enrollment. Live online classes may offer part-time or full-time enrollment options. Part-time is best for those balancing work and learning. If you can commit to full-time enrollment, you can finish your course in about half the time.

Every data training format has its advantages and drawbacks. Considering which of these options best suits you will help narrow down your options.

Why Learn Data?

Why should you learn data? Data informs business decisions by displaying the numbers behind the business. Data reveals how much money a business spends, how efficient company processes are, the effectiveness of marketing efforts, the cost to obtain a customer, how much revenue the company has coming in, and more. Reliable data is crucial to any organization’s health and success, whether the organization is a multinational company or a local nonprofit.

Data science uses scientific methods, systematic processes, and algorithms to filter, sort, organize, and manage raw data from numerous sources. Data Scientists and Data Analysts are in high demand and have high earning potential. The U.S. Bureau of Labor Statistics found the 2021 median pay for Data Scientists was $100,910 per year, with anticipated job growth of 36% over the next decade. Even if you do not wish to pursue a career as a Data Scientist or Data Analyst, data plays a critical role in marketing, project management, team leadership, and more. 

Read more about why you should learn data. 

Level of Difficulty, Prerequisites, & Cost 

The difficulty level of learning data varies considerably based on your educational and professional background, familiarity with data concepts and tools, and the specific skills you wish to gain. Read on to learn more about the difficulty, prerequisites, and cost of learning data science and data analytics. 

Because much of data science depends on having a background in science, mathematics, and sometimes engineering, data analytics can prove a more accessible place to start. Many professions use data analytics daily, even if “analyst” is not in the job title. For example, Marketing Specialists, Marketing Managers, and other marketing professionals depend on data analysis to gauge the effectiveness of digital marketing strategies. Because so many professions use at least a basic level of data analysis, just about anyone can benefit by taking a data analytics course with broad applications, such as Noble Desktop’s Google Analytics Bootcamp or Excel for Data Analytics class. Individual, focused courses such as these tend to cost around $600 to $700. 

Longer courses have an increased cost, with certificate programs often the most expensive due to their length and the instructor’s active involvement. Noble’s Data Analytics Certificate program costs around $5,000, with flexible payment plans available. Some companies cover the cost of classes as part of an employee’s internal professional development, so it is always worth checking with your employer about their reimbursement policies.

Data science is a challenging, multidisciplinary field involving statistics, business knowledge, and computer programming. Prerequisites include understanding mathematical modeling, machine learning, and other means of extracting valuable insights from raw data. Businesses of all sizes, from startups to government agencies, hire Data Scientists. Data science skills include learning Python, SQL, machine learning, and more. The complexity of data science makes it extremely difficult to learn independently, so an instructor-led course often provides the best way to learn. The best way to establish foundational data science skills and knowledge is through an instructor-led program such as Noble Desktop’s Data Science Certificate program. Certificate programs like this cost around $4,000 and up, depending on the school, the length of the program, and more. 

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 multiple data analytics and data science training options here.

Key Insights

• Deciding how to learn data can feel overwhelming due to the number of choices. 
• Knowing what type of learner you are will help narrow down your options.
• Visual, auditory, and kinesthetic/tactile are the three types of learners.
• The three primary forms of data training are on-demand/self-paced online classes, in-person classes, and live online classes. Each has its benefits and drawbacks.
• Benefits of on-demand classes include video content for visual and auditory learners, affordable subscription options, and the ability to learn at your own pace, on your schedule. 
• Drawbacks of on-demand classes include lack of instructor access, the potential for outdated information and materials, and limited hands-on experience.
• Benefits of in-person classes include local networking, access to equipment, the ability to collaborate in person, and immediate feedback from your instructor.
• Drawbacks of in-person classes include the need to commute, the cost of tuition, and the limited choices regarding class time and curriculum.
• Benefits of live online classes include real-time instructor access, no need to commute, and an extensive range of options for class topics and schedules.
• Drawbacks of live online classes include not being able to network locally, the cost of tuition, and the need to use your own computer and tools.
• You can receive comprehensive data training through an in-person or live online course with Noble Desktop.