How to Learn Data Science: 5 Effective Learning Methods You Need to Know

Data science is a field that draws from disciplines like mathematics, advanced analytics, statistics, programming, machine learning, and AI to unearth useful insights from an organization’s data that can help it make better decisions.

Due to the ever-increasing number of data sources and corresponding volume of data, data science is one of the fastest-growing fields across industries. The data science lifecycle includes data collection and ingestion, data storage and processing, data analysis, and communication. As more organizations see the value in data, they seek those with the skills to interpret this information and offer useful recommendations to improve how the business operates. One of the most effective ways to gain the skills necessary to pursue a career in data science is to enroll in a class, bootcamp, or certificate program that teaches the skills and tools necessary to handle data. 

Enroll in In-Person Data Science Classes

The most effective and engaging way to learn data science skills is through in-person coursework. For learners who thrive in the traditional classroom environment, in-person data science classes offer an interactive way to acquire this skill set. Participants learn from an expert instructor who has industry experience in data science. Lessons take place in a computer lab or similar space in which participants have access to the most current data science tools, software, and programs available. The live format ensures that learners can ask questions at any point and receive immediate support and guidance. In addition to connecting with a skilled instructor, those enrolled also have the added support of a cohort of learners. The connections made during live study can lead to networking opportunities and lifelong friendships. 

In-person data science classes are available from top educators around the country in a variety of formats. Students can select from short skills classes, which cover one particular data science tool or skill such as Python programming or machine learning. These courses are relatively short and can often be completed in just a day or two. Other in-person coursework is longer and more involved. Bootcamps and certificate programs, which are available in-person, can span weeks or months and provide participants with a range of data science tools and skills. Many of these programs also provide learners with professional development as part of tuition. In-person coursework ranges in cost from several hundred dollars for skills classes to several thousand dollars for bootcamps and certificate programs.

In-person coursework requires that participants live near a training facility. Often, these are located in major cities. Additionally, students must be able to attend classes that meet at regularly scheduled intervals. They also need to have reliable transportation to and from each class meeting. This learning format may require an additional financial investment for parking costs and transportation. However, the benefits of live study more than make up for these additional costs. Students who learn in this format receive high-quality instruction with the current best practices in data science and can apply these skills immediately to their current job or a new career path entirely. 

Attend Live Online Data Science Classes 

Another excellent way to acquire data science training is through live online coursework. Students who opt to study in this format receive many of the same benefits as those who elect for in-person training. Participants connect for courses using a teleconferencing platform like Zoom or Teams that provides an audio and video connection to the teacher in real time. This training type offers learners the opportunity to receive help on complex data science concepts and raise any questions as they arise. Students can even share their screens with the instructor (with permission) for additional support. Not only do those enrolled have access to a teacher with real-world data science training, but they also can connect virtually with other students in their cohort, which provides a support network while learning. 

Similar to in-person study, those who opt for live online data science classes can select from skills courses, bootcamps, or certificate programs. These classes vary in length from short skills classes that require just a few hours to complete to long bootcamps and certificates that span weeks or months. Cost varies for live online study. Like in-person learning, skills classes are available for several hundred dollars, whereas bootcamps and certificate programs can cost several thousand. Some live online classes focus exclusively on one data science skill such as working with SQL, whereas other content is more comprehensive and provides an overview of the field of data science and instruction in a range of tools. Live online classes are available for learners at all levels, from those who are just getting started working with data science to seasoned professionals with years of professional experience who are seeking advanced analytics training for a new career path. 

Live online classes take place remotely, which means students never have to waste time or money commuting to or from class or on parking fees. Coursework can be completed from any location with a strong internet connection. This ensures that those with busy schedules, including travel or other commitments, can still learn data science from their location. This training format is also a good option for students who don’t live near major cities with training facilities or who do not have reliable transportation. One important consideration of live online classes is that they still require that students attend regularly scheduled meetings. Some schools have night classes available, as well as weekend coursework or part-time programs that can be completed at night. However, it’s essential for prospective students to make sure they can commit to attending class to get the most out of their online experience. It is also essential to have a computer with the tools and software needed for study since this will not be provided, as is the case with in-person study.

Sign up for On-Demand Online Data Science Classes

For those who aren’t able to commit to regularly meeting data science courses, a third option is available. Participants can learn this skill set through on-demand coursework. Unlike in-person study or live online training, on-demand classes occur asynchronously. The content was recorded at a previous time by an educator and is placed online. This means that students can study data science from any location with a strong internet connection. Not just that, but they can spend as much or as little time on coursework as necessary. Self-paced study material is the most flexible learning format; it can be completed for fifteen minutes a night after work over weeks, or students can opt to devote an entire weekend to learning data science. 

Self-paced data science training materials are widely available from a range of educators. Students can select from short YouTube videos that require only minutes to watch and cover one particular skill such as how to write a basic SQL query or how to automate a repetitive task like formatting when working with a large dataset. Learners can opt to watch one or multiple videos to acquire the data-related skills they need. Other content is much longer and more involved. Some providers offer full skills classes, bootcamps, or certificates that take weeks or months to complete. These courses provide a robust overview of the field of data science, the most commonly used tools, programming languages, and software, and the core skills needed to work as a Data Scientist. Often, these classes include a combination of video content, tutorials, quizzes or tests, and other training materials. Some self-paced classes focus entirely on Python, SQL, or R, whereas others provide comprehensive instruction on statistical analysis, computer programming, advanced analytics, and data visualization. 

Cost is another important consideration when enrolling in data science training. Often, self-paced material is less expensive than live content. Since it is pre-recorded, the educator can provide the class to hundreds or thousands of learners rather than limit enrollment to a small cohort. Whereas in-person or live online certificate programs can cost more than $10,000, a self-paced data science class may only cost several hundred dollars or even less, depending on the provider. Some educators even offer free training materials online. 

Unlike live classes in which the teacher sets the learning pace, on-demand content pacing is dictated by the learner. Students can pause lessons as often as necessary to facilitate note-taking. They can also rewind or re-watch entire lessons as needed to master complex skills. However, no instructor is available. This can make it challenging for some students to fully grasp complicated data science materials in this format. Self-paced coursework is most suited to independent learners who are able to self-motivate to find answers to questions on their own. It is also often a good starting point for those who are new to data science and need basic training before enrolling in a more structured live class.

Another important consideration for those who are interested in self-paced data science training is finding good content. It’s important for aspiring students to do research into the educational provider before committing to a course. This may involve reading the syllabus (which is often available online), as well as student reviews that highlight their experiences in the program. Selecting a reputable educator can make the difference between a positive or a negative learning experience. Live coursework is up-to-date because it is taught in real-time, whereas asynchronous material can quickly become dated. This is why it’s essential to choose content that is current and reflects the best data science practices being used in the industry. It is also vital to choose coursework at the appropriate learning level. Those who are new to data science, for example, will likely not be prepared for intermediate or advanced-level training, especially without the help of a live instructor. Similarly, a beginner-level class will probably not help experienced Data Scientists acquire the necessary training.

For learners who are studying data science for professional reasons such as to use their skills in a current work project or to apply to a new professional role, in-person or live online training may be a more useful way to master this complex subject matter. Often, live bootcamps or certificates also provide learners with professional support such as resume reviews or job search advice. Self-paced study options typically lack this support.

Watch Free Data Science Tutorials 

It’s possible to study data science without having to spend a penny. A variety of free data science tutorials and training material is available online. This content is pre-recorded by educators like Udemy, Noble Desktop, and Coursera, among others. Self-paced, free material takes many forms. Students can subscribe to a YouTube channel devoted entirely to short data science tutorials, enroll in an hour-long webinar that presents an introduction to data science, or opt for more involved training material that spans hours or days and covers a particular coding language. Content is available for beginners, intermediate learners, and advanced students.

Students who opt for free data science tutorials have all the perks of self-paced study without any of the cost. They can complete lessons on their own time, at their own pace, and from any location with a strong internet connection. They also can dictate their learning speed and the amount of time they wish to devote to acquiring data science skills. The only requirements are a computing device and access to the tools needed to study data science such as Python, SQL, R, data visualization software, or any other required tools the educator uses during training.

Because so much free material is posted online, it’s imperative for learners to do a bit of research before selecting a tutorial. Similar to for-pay on-demand content, exploring the provider is a good place to start. Additionally, reviewing the course outline or educational goals of the training can also be helpful. Often, educators post online reviews from those who recently completed their free online data science training. Ensuring previous students had a positive experience and that the content is current will lead to a better learning outcome. Making sure content is up-to-date is also important since some material may have been posted ten or more years ago and has not been updated since.

Since no financial commitment is involved with free data science resources, learners can select one or multiple study options as necessary. If the course content doesn’t feel like it’s a good match and is too advanced or too basic, participants can discontinue study at any time without losing money. Other learning options such as in-person classes and live online training, do not provide this flexibility. Those who decide to cease their studies during a live bootcamp or certificate program, for example, may not be entitled to any amount of a refund. This is why for some learners, free data science tutorials provide a good starting point to see if the field is a good match for their interests. 

Since free online data science tutorials are recorded at an earlier time, they do not provide learners with access to a cohort of students or a live instructor. This is why those seeking advanced study may need to invest in a more structured learning format at some point in their training. 

Explore Data Science Certificates & Certification

For those who are interested in taking their data science skills to the next level, a certificate or certification is an excellent professional option. Earning a certificate or certification in data science is a great way to increase your job opportunities as well as earning potential. A recent study found that those who have a certificate in their field, on average, make up to 20% more than those who lack this credential. Not only can certificate study or certifications lead to higher salaries, but they ensure that participants have a verifiable skill set that can be used professionally in many career paths. This is why employers often seek out those who have earned these qualifications or may choose a candidate who is certified in data science over one who is not.

Although certifications and certificates sound similar nominally, they differ in the process involved in earning them. Certifications generally involve studying for an exam in data science or a related field. A third party proctors this test. Those who pass it have shown that they have mastered the subject at hand. On the other hand, certificates are usually completion-based programs. Students take a training course that focuses on a specific data science skill such as machine learning, or can opt for a certificate with a broader focus on data science in general. Those who successfully complete the coursework in their program earn a certificate, which can be included on a resume to indicate to potential employers that this individual has earned a mastery of data science.

Certification exams do not typically require participants to complete a training course as a prerequisite to sitting for the test. However, to gain the necessary training to pass the exam, many students opt to enroll in a course that covers the concepts taught in the exam. For learners who may already have acquired this training elsewhere such as through their current profession, they can choose to sign up for the test without having to complete any previous coursework. On the other hand, earning a certificate is based on completing designated coursework and may or may not include an exam at the end of the class. Certificate programs often offer students other perks beyond data science training. Some provide one-on-one mentoring, career counseling, or professional development services in which students can receive individualized help with their LinkedIn profiles, resumes, interview prep, or other career-related services.

For most professional data science or data analytics roles, professional certification isn’t required. However, those who seek certification can benefit from this training and use it to gain the attention of employers. Certificates and certifications also indicate a student has achieved a certain level of data science understanding. 

Within the field of data science, a range of certifications are available in specific topics. For those interested in tech or data-specific certifications, Google-Certified Professional Cloud Architect is available for individuals who will be handling large stores of data. TheAmazon Web Services Certified Solutions Architect is another popular data science certification. Those who earn this certification are able to create and deploy secure systems on various AWS technologies. The AWS Certified Developer—Associate certification is also available, which is geared toward those who create and manage apps on AWS. For those seeking professional roles where Python will be used, the Certified Associate in Testing with Python is available, as is the Certified Associate in Data Analytics with Python. Professionals who will be working with Power BI at their job may pursue the Microsoft Certified: Power BI Data Analyst Associate certification.

In addition to data science certifications, various certificates are also available. Students can opt for in-person training at the educator’s facility, which is usually located in a major city. In addition, live online certificate study is also available from many top providers. This option allows students to complete coursework remotely from any location with a strong internet connection. Both study options allow students to connect with an instructor in real time and receive in-the-moment support and guidance as they learn data science. Noble Desktop’s Data Science Certificate Program offers training in a range of data science skills such as Python, SQL, machine learning, and data visualization. Digital Workshop Center’s Data Science Certificate teaches students how to work with R programming, as well as how to apply statistical concepts to the business sector. NYC Career Centers Data Science Certificate is available for those who want to master a range of tools needed to pursue a career in data science. Students receive instruction on core Python programming skills, querying databases with SQL, analyzing data, and creating machine learning models.

Ultimately the decision whether to seek professional data science certification or enroll in a certificate program will depend on an individual’s learning needs, career goals, and the job requirements for any professional roles they wish to explore.