Which Data Training Format Is Right for Me?

You may want to learn data to gain more detailed insights about your business or organization. Or, maybe you want to advance your marketing skills by adding analytics to your resume or launch a new career in data analytics or data science. When comparing types of data training, there are many factors to consider. Everyone learns differently, and choosing the proper training is critical to your experience.

Keep reading to learn more about the different formats of data training, how they compare, and how to determine which is best for you.

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.

Training Formats for Data

Three main data training methods are on-demand/self-paced, in-person, and live online courses. On-demand/self-paced courses are those that you progress through at your own pace and schedule. This format offers maximum flexibility as to what and when you learn. On-demand classes consist mainly of video content which can be beneficial due to the ability to pause, rewind, and rewatch as many times as you choose. This data training method is also the least expensive since you can find free video classes and paid classes for around $30 to $50 per month through sites like Udemy, LinkedIn Learning, and Coursera.

Instructor-led classes can be in-person classes that meet in a physical location or live online classes that meet virtually. Both data training methods provide real-time feedback and guidance from an expert instructor, which is especially helpful when learning complex subjects and completing hands-on projects. You can also collaborate with classmates and have questions answered immediately with both formats. In-person and live online instructor-led formats tend to cost the same, so which format you choose depends on which method best fits your needs.

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. Coursera also offers free data classes, including Data Processing for Python, Python and Statistics for Financial Analysis, Data Science Math Skills, and more. You can also find introductory data science courses and free classes on data science essentials on Udemy.

Read about more free data videos and online tutorials.

On-Demand Classes

On-demand/self-paced classes include pre-recorded video courses you can watch anytime. Some video courses include supplemental material such as documentation and assignments. You can use free YouTube video courses to gain a high-level overview of a topic, such as learning data. Learning platforms like Udemy, Coursera, and LinkedIn Learning offer on-demand classes through paid subscriptions. The primary advantage of asynchronous classes is that you can learn on your schedule. You choose the time, place, and pace at which you learn. The main disadvantage of on-demand classes is the lack of instructor access. You may have an instructor you can email or meet with at specified times, but both options require waiting several hours or days for a response. For this reason, many people use on-demand courses as a starting point to better understand a topic, then follow up with an instructor-led course. Explore on-demand data classes to find free and paid training options.

Comparison of Data Training Formats

Three main data training formats are in-person data classes, live online data courses, and on-demand/self-paced data courses.

In-person data classes meet at a physical location. A local instructor leads the class, answering questions and guiding students through hands-on projects that reinforce data skills. In-person classes allow you to network with local professionals such as your instructor and classmates. Small class sizes ensure more individual attention and training. Students' main difficulties with in-person data classes are finding a time and location that works. Commuting to a physical learning location requires dedicating more time to your data training. Since local classes may have a limited selection, you may struggle to find a class that teaches exactly the skills you wish to pursue or meets at a time that works for your schedule. In-person classes include high tuition compared to other forms of learning, though many offer flexible financing plans to ease the upfront costs. This type of training works best for those looking to make local connections and who prefer to learn in a traditional classroom setting.

Live online data classes include many benefits offered with in-person classes, minus the commute. Expert instructors lead online courses and provide real-time feedback, answering your questions, assisting with technical difficulties, and guiding hands-on projects. Remote learning enables students and teachers to access the class from anywhere with an internet connection. So, you can learn from any location and take classes from instructors anywhere in the world. The freedom to enroll in online classes from schools in New York, London, Sydney, and more maximizes your options, enabling you to find a class that meets at a time convenient to your schedule and teaches the skills you wish to learn. Live online classes tend to cost the same as in-person courses. The ability to network locally is the one aspect of in-person learning that online classes cannot replicate.

On-demand data classes, also known as self-paced classes, have the lowest cost of any data training format. These classes work best as a starting point to gain a high-level overview of a topic. Some platforms, like YouTube, include free video classes. Other platforms, like Udemy, LinkedIn Learning, and Coursera, include video-based on-demand classes accessible through paid subscriptions. Because data science and data analysis require so much technical knowledge and can prove complex and challenging, learning data with self-paced courses can prove frustrating. The lack of instructor access is the biggest drawback to this learning format. Students may have to wait hours or days for an instructor to reply through email, halting their progress completely. Instructor-led courses, by contrast, provide real-time feedback.

Is it Possible to Teach Yourself Data?

It is possible to teach yourself some data skills and tools, though the more complex a subject, the harder it will be. The best approach for most people is to learn foundational skills through free or low-cost data training options, determine the skills and tools needed to meet your professional goals, then select an instructor-led class that covers these skills and tools. 

When you start to dive deeper into data, it helps to have an expert to answer your questions and give you feedback. Instructor-led courses help break down complicated concepts and processes with step-by-step instructions. You also gain hands-on experience with expert guidance from your instructor. Many instructor-led programs include one-on-one mentoring, free retakes, and job search assistance. 

How to Decide the Best Way to Learn Data

Deciding the best way to learn data starts with knowing what you want to do with your acquired skills. Are you looking to advance your current career or start a new one? Are you building on existing skills or starting from scratch? Do you want to focus on data analytics, data science, or both? You can opt for a broad approach or focus on a niche area. Research specific job titles to find a training method that caters to the skills required for that role.

There are a few different data training methods to explore. On-demand data analysis and data science classes consist of pre-recorded videos and textual content that students progress through at their own pace. These classes are the most affordable of the paid options but have the significant drawback of limited guidance or feedback. The lack of access to an instructor can leave students stuck on a question or technical issue for hours or days. Due to their affordability, on-demand classes on paid subscription services like Coursera and LinkedIn Learning can be a good starting point for learning data.

If you are just starting out and not ready to commit to a paid class or program, you can gain a high-level overview of data with free introductory classes. Noble Desktop offers free resources, including the Get Started in Data Science video course and Python, Data Science, & SQL YouTube playlist. Free video courses can introduce you to a topic. But because of the complexities involved in learning data analytics and data science, an instructor-led program often works best once you’re ready to dive deeper.

If you want to develop a solid working knowledge of data, plug a skill gap, or grow within your current career, a bootcamp can help you upskill quickly. Some bootcamps focus on specific topics within data science, such as Noble Desktop’s Python for Data Science & Machine Learning Bootcamp and Python for Data Science Bootcamp. You can also look into data analysis bootcamps such as Noble’s Data Analytics Technologies Bootcamp.

If you want to master data for a new career or pivot to a new industry, a certificate program can help pave the way. Noble Desktop offers a Data Analytics Certificate program and a Data Science Certificate program with live online classes, small class sizes, setup assistance, flexible payment plans, one-on-one mentoring, and a free retake.

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.