Can I Learn Data Visualization On My Own?

Each individual has a unique way of learning. You might identify as an auditory learner, whereas others might perceive you as a visual learner. The preference for traditional classroom learning versus independent study varies from person to person, so the ability to learn data visualization without external assistance may differ based on individual learning styles. In general, gaining some foundational knowledge is possible, but it may not be reasonable to expect to obtain expert-level skills. Data visualization is a field that can be learned independently with the right dedication and resources. However, learning data visualization independently requires commitment and self-motivation. Free resources and on-demand options exist for those interested in learning independently.

Advantages of Self-Teaching Data Visualization

In certain scenarios, self-teaching a new skill can be a valuable and practical option, taking into account personal considerations like schedule, budget, existing skills, and learning objectives. Although some may regard self-taught methods as challenging, others may be able to adapt to self-paced learning methods quickly. 

If you lack familiarity with data visualization, delving into some fundamental concepts on your own can provide a solid framework for grasping the subject before enrolling in a formal course. Through self-teaching, you can gain insight into its intricacies, acquire foundational knowledge, and even try some basic coding exercises. Through this process, you can assess if you're prepared to commit the resources for a structured course. Self-teaching can also be beneficial for people who already have some experience. If you're already familiar with certain data visualization techniques and are seeking to expand your knowledge, self-teaching could be beneficial as it may reduce the need for ongoing instructor support.

While self-teaching can have the downside of not giving you access to instructor guidance, one benefit of teaching yourself is that you can learn at your own pace, allowing you to spend the time you need to get a solid understanding of the material. You can pause and review material whenever needed and take as much time as you need to understand new skills. Since you direct your learning pace, you can also learn on a schedule that works for you. In addition, you can include a lot of practice time in your learning schedule. Practice is an important part of mastering data visualization. It reinforces the concepts you have learned, helps you master them, and teaches you to apply them in real-world situations. 

Data Visualization Self-Teaching Tools

You can learn data visualization skills in various ways on your own. Many websites, like YouTube, offer free tutorials. These resources cover many different aspects of data visualization, introducing various topics and showing different data analyses. Many data visualization schools also provide free information to help prospective students better understand this field before committing to a formal class. For instance, Noble Desktop offers many free data seminars that cover introductory information. These short, free articles are an excellent option for learners who want to explore different data visualization topics before enrolling in a course. Udemy offers a range of short videos on data visualization topics, such as Matplotlib Tutorial, Install Tableau Desktop, Introduction to Predictive Analytics Models, and Introduction to Time Series with Pandas. Each video is between three and nine minutes long.

On-demand classes are another self-directed data visualization learning resource. These classes contain pre-recorded content that you work through at your own pace. With an on-demand course, you can work as quickly or as slowly as you want to, stopping and starting wherever you need to. Some on-demand classes are free, and those that cost money are generally relatively inexpensive compared to live class options. While on-demand classes are not 100 percent self-taught, they do require a high level of self-motivation and self-direction. Coursera and edX are two sites that offer free on-demand data visualization classes.

There is also a lot of free online content designed to help people who are trying to learn a specific data skill or troubleshoot a problem. You’ll find many short free tutorials on sites like YouTube that can help you with specific data issues. You’ll also find online forums where more experienced data professionals are often happy to share their expertise for free. Solving problems is a fundamental part of data visualization, so if you’re learning, you can expect to find yourself troubleshooting often. Consistency is key. You can develop some valuable data visualization skills even without a formal education by dedicating time, utilizing free resources, and actively practicing.

Drawbacks to Learning Data Visualization on Your Own

While self-teaching options may be viable, it's essential to carefully evaluate your choices, factoring in your current skill level and aptitude for grasping data visualization concepts. The potential drawbacks deserve thorough consideration, as they can significantly impact your learning journey.

Hands-Off Approach

Learning data visualization independently has its drawbacks, with on-demand classes offering convenience but lacking hands-on experience, interaction, and personalization typically found in live delivery methods. This could pose a significant challenge for individuals who excel in learning through interactive experiences and conversations, as well as those who are relatively new to data visualization and related ideas. In addition, the lack of an instructor can be a major drawback, particularly for beginners, who will likely have a higher learning curve than someone who already has data visualization knowledge. The projects completed in a self-paced or self-taught class are usually comparable to a live training course, but they are completed independently. 

Potential Roadblocks 

Because of the independent nature of on-demand classes or self-taught options, students are at a higher risk of facing perplexing situations and obstacles. Some common struggles include software malfunctions, needing to understand how to use tools, failing to follow data principle guidelines, or falling short on project requirements. You may have to spend additional time outside the on-demand class answering your questions and figuring out how to fix errors solo, which wouldn’t be necessary in a live course. This might significantly extend the time it takes for you to learn, which kind of defeats the purpose of opting for a self-paced or self-taught learning approach.

Not Fit For Mastery

Additionally, more than free resources, self-paced classes, and self-teaching methods are often needed to provide an expert-level understanding of data visualization. Instead, they work more as supplemental material. To excel in their careers, many data professionals pursue several courses or intensive bootcamps to gain expertise in the field. Plus, traditional live classes allow students to build their portfolios, develop interview techniques, and gain more insight into the professional world. While it is possible to gain some data visualization knowledge on your own, you will have to consider all the different training options available to become a data visualization expert and working professional.

Alternatives to Learning Data Visualization on Your Own

In addition to self-study or on-demand courses, a wide variety of live classes are available that can greatly facilitate the data visualization process. Training centers, both US-based and international, offer in-person and live online courses at different levels, so there is a course out there that suits your current skills. A live class implies that students will have extended interaction with the material and the various technologies they will use in data visualization, as well as with the instructor and fellow peers. Overall, these courses give students the most thorough learning experience.

When acquiring a new skill, live training, whether in-person or online, is generally regarded as the best option. The interactive space that live classes offer is one of the main benefits that self-paced and on-demand options don’t provide. During a live classroom session, students can directly interact with the instructor, asking questions and obtaining immediate feedback, which is particularly beneficial for novice learners who often face obstacles and periods of confusion. Additionally, live courses are taught by an expert, so a real-world understanding of the data visualization field influences the feedback each student receives. Plus, many live classes have additional benefits not included with self-learning options, such as limited licenses, access to computer labs, setup assistance, portfolio development, and career preparation. The alternatives to self-paced learning are worth considering if you want to become a data professional.

Live Training Options at Noble Desktop

If you’re interested in studying data visualization, Noble Desktop offers several in-person and live online courses that provide hands-on training. Noble’s Tableau for Data Visualization Bootcamp is an excellent option for those who wish to work with Tableau to visualize data. Participants receive an overview of the field of data visualization and learn about Tableau Public’s visualization tools. By course completion, students will have a solid understanding of identifying which datasets to connect to and how to analyze, filter, and organize data to make customized, publishable visualizations. This course also offers the option of a free retake for those interested in revisiting Tableau concepts. 

Noble’s in-person or live online Data Analytics Certificate is another good learning option for those seeking a more intensive study option. This rigorous program provides expert instruction on various data analytics concepts and prepares learners to become Business Analysts or Data Analysts. By course completion, all participants will be familiar with core business intelligence, statistical analysis, data analysis, and data visualization concepts. This is a project-based course in which students will complete various real-world projects using prescriptive and predictive analytics. All students receive one-on-one mentoring as part of tuition.

In addition, other in-person and live online data visualization courses are also available from Noble Desktop. Those who wish to learn the tools to become Data Scientists may consider enrolling in Noble’s Data Science Certificate, which covers machine learning, automation, SQL, and Python. A Python for Data Science Bootcamp covers fundamental and complex Python programming concepts, such as creating programs and using statistics to make machine learning models. 

The Excel Bootcamp is also available, which teaches core spreadsheet functions like working with macros, formulas, and PivotTables. Finally, those interested in working with SQL to extract information from databases can enroll in Noble’s SQL Bootcamp. This course prepares learners to write queries, aggregate data, and filter results using PostgreSQL.