When deciding whether to enroll in a data analytics bootcamp, one key factor you’ll have to consider is whether to opt for full-time training or study on a part-time basis. Most educators offer bootcamps in both formats to accommodate various scheduling commitments. Both types of training have their own benefits and drawbacks that each learner must weigh for himself or herself. The following article will take a closer look at some of the perks and drawbacks of part-time bootcamp study, as well as ways to make this learning process as effective as possible.
Why Learn Data Analytics Part-Time?
One important decision all learners will need to weigh when they opt for data analytics training is whether they want to complete their classes on a part-time or full-time basis. This decision is typically based on the student’s availability and scheduling constraints. For those who work full-time or have busy personal lives, part-time coursework may be the only way to acquire professional data analytics training without sacrificing other commitments. Part-time classes are often available on weekends or weeknights, which will not disrupt traditional work schedules. Other learners who have more flexible schedules may prefer a full-time study approach, which will allow them to fully immerse in their studies and complete their training at a much faster pace.
For those who have schedules that permit part-time data analytics study, this type of training has many benefits. Students have the opportunity to spend a longer period of time with the content they’re learning, which can be a benefit for many learners. Because part-time data analytics bootcamps take much longer to complete, students can spend months (rather than weeks) exploring the tools they’re learning and reinforcing difficult concepts. Since data analytics is a broad and complex field that requires knowledge of statistics, data visualization software, computer programming languages, relational databases, and spreadsheets, having extra time to practice each skill individually is an effective way to maximize retention and ensure that the content you’re learning can be applied in a professional setting later on.
Drawbacks to Learning Data Analytics Part-Time
Although there are many benefits to enrolling in part-time data analytics training, this learning format also has several drawbacks to consider. The first is the length of time it will take to complete coursework. Students who select full-time training complete their studies much faster than those who opt for part-time instruction. Certificate programs may take only weeks to complete on a full-time basis, whereas they may require several months of part-time study to finish. Bootcamps, too, can take several weeks or months to finish on a part-time basis. This means that learners who need to acquire training for their current job or learn a particular application to finish a work project may have to wait months to acquire this training in a part-time bootcamp or certificate program. While this additional time can provide a valuable window for students to learn the tools they’re working with, part-time study may not be the best option for those interested in learning to analyze data within a shorter timeframe.
Another possible drawback to part-time data analytics training is remaining motivated and focused for an extended period. While extra time to devote to studying is a benefit for some learners, it can also pose challenges for some, especially those who are juggling their studies with work or personal commitments. Those who opt for part-time coursework will also have to wait longer to use the skills they’re gaining than those who select full-time study. This may present challenges for those whose current jobs require this knowledge for an ongoing or upcoming project.
Is a Part-Time Data Analytics Bootcamp Right for You?
There are several important considerations you’ll likely need to weigh to decide if part-time data analytics training is the best learning format for you. The first is what sort of flexibility your work and personal schedules afford. For those who have full-time jobs or busy personal lives, full-time coursework may not even be an option because it may require weeks of full-day study that would interfere with these commitments. For these individuals, part-time study would be the best choice since training could take place on weekends or weeknights. Another factor to weigh is how quickly you need to obtain data analytics training. If, for example, you must quickly learn how to create PivotTables in Excel for a current work project, it may not be feasible to wait several months for coursework to progress to spreadsheet training. Instead, you may be better off choosing a part-time program or a skills class. For learners who have the time and motivation to space their studies out over weeks or months, however, part-time data analytics classes are an excellent way to receive hands-on training and have the time and space to put your skills to use.
Ways to Make Learning Data Analytics Part-Time Easier
Students who prefer to study data analytics on a part-time basis can take advantage of many educational resources to help streamline studies and ensure they get the most out of their training. Because of how many organizations and individuals now collect data, many free online learning resources are available that can be used alongside part-time bootcamp study to help maximize your efforts. You can select from YouTube channels that provide short video instruction on specific data skills such as printing Excel worksheets or querying a database with SQL. These videos only take a few minutes to watch and can help you fill a skill gap for a current project. Since there’s no cost associated with these resources, they provide a low-stakes way to learn how to work with data. Additionally, free data analytics learning resources like blogs and tutorials are posted by providers like Noble Desktop for students who want to read specific articles pertaining to data analytics topics. Noble’s Learn Hub page includes more than 150 posts on topics like popular software tools for Data Analysts and the most common data analytics methods.
Noble and other trainers around the globe also post free videos explaining key data analytics concepts and skills. In addition to offering learners a free example of the type of course content they would expect from the provider if they signed up for a full course, this content offers a great starting point for those who are new to working with data. In Noble’s free introductory data science webinar, students get an hour-long overview of how to analyze datasets and how Python is used in data science. Since no instructor is present in free online data analytics content, some learners may not be able to fully grasp more complex data concepts or skills from this content alone. This is why some bootcamp participants choose to use them alongside their live training rather than as a substitute for it.
Another way to ensure you’re getting the most out of a part-time data analytics bootcamp is to take full advantage of the supplementary resources in place to help with your learning. For example, some programs include access to educational resources that are designed to help students get the most out of their coursework. Certificate programs often provide learners with access to 1-on-1 mentoring sessions that are a great opportunity for them to revisit completed course concepts and receive additional support and clarification. Since these programs are available in a live format, learners also should take advantage of having access to an instructor in real-time. Those enrolled should ask questions as they acquire new skills and work with data analytics software. The more actively participants engage in their learning process, the more they’ll benefit from their part-time training.
If you choose to study data analytics part-time, adhering to a schedule is always a good practice. You’ll have longer to complete assignments and work with the tools, software, and applications you’re studying, which is an excellent way to optimize retention. For some, though, having this extra time may not equate to more practice if they don’t follow a set schedule. Devoting 15 or 30 minutes each day to practicing one skill such as writing macros in Excel or using SQL to query relational databases is likely to be a much more effective learning path than trying to cram coursework into one long chunk each week. If you consider this longer training format as an opportunity to spend regular time practicing and developing your skill set, you’re likely to see immediate and long-term results.
Choosing the Best Part-Time Data Analytics Classes or Bootcamp
When selecting a part-time data analytics bootcamp, there are several considerations that are unique to this type of training that you will need to weigh. First are general factors. Since part-time coursework can take weeks or months to complete, will you be able to consistently carve out the time to devote to your studies and to complete the assignments? Part-time study spans a longer timeframe than full-time study, which means you’ll have more time to complete work and practice skills. However, this type of training requires you to be self-motivated to continue your studies outside of the classroom.
In addition to time commitment, cost is another essential factor to consider when deciding which bootcamp is right for you. Some bootcamps are shorter than others and focus on one data analytics tool such as Excel or Tableau. These programs are often much more affordable than more comprehensive bootcamps or certificates that cover a range of data analytics tools and skills. For some, spending $1,000 on a bootcamp focused on Excel may be a more financially viable option than paying $15,000 for a longer and more comprehensive program.
Another factor to consider when you choose a data analytics bootcamp is whether the program will provide additional support beyond live class instruction. This is especially important if you’re looking to put your data analytics training to use professionally, either in your current job or to pursue another data-related career path. If you’re enrolling in a part-time bootcamp to break into a new data-related career, for example, a program that provides personal mentoring or other professional development services like resume reviews and access to networking events is a good investment because it can help you get a job.
Finally, for some learners, it’s important to find data analytics part-time coursework that is close to home. If you live near a major city, odds are you will be able to find a designated training facility that provides hands-on data analytics instruction. However, if you lack reliable transportation or live far from training centers, live online bootcamps may be a better option. Some educators provide both in-person and live online study options, whereas others may only offer one or the other.
Learn Data Analytics with Noble Desktop
If you’re looking to learn data analytics or build on your existing skills, Noble Desktop provides both full-time and part-time training options for learners at all levels. You can search for in-person data analytics classes nearby to find the learning match that’s best for you. In the following paragraphs, several popular course options for aspiring data professionals will be explored, as well as the requirements for each program.
If you’re ready to fully immerse yourself in your data analytics training, Noble Desktop’s Data Analytics Certificate is an excellent choice. This hands-on class provides training in a range of data analytics software and tools. In this intensive certificate program, students become familiar with analyzing and visualizing data in Excel and using Python scientific libraries. Participants use SQL to retrieve data from relational databases and explore how Tableau is used to visualize data findings. All participants receive eight 1-on-1 mentoring sessions as part of tuition, which can be used for professional development or to revisit complex course material. Both part-time and full-time study options are available.
Those interested in a shorter class that teaches Python data skills can instead opt for Noble’s Python for Data Science Bootcamp. Participants use Python to create programs, visualize data, and create machine-learning models with statistics. Instruction is provided on core Python concepts such as how to write statements and expressions, understand different data types, create variables, and use lists. During the second part of this bootcamp, topics like dictionaries, control flow tools, loops, and conditional statements are taught. Part three of the coursework covers how to use NumPy and Pandas to clean data and work with Matplotlib, Pandas, and NumPy to transform data findings into advanced visualizations like bar charts and histograms. All students receive a supplementary 1-on-1 mentoring session.
Tableau Certification Program is a great option for anyone interested in acquiring data visualization training to pass the Tableau Desktop Specialist certification exam. As part of this program, students complete two shorter classes: Tableau Level I and Tableau Level II. Six hours of private tutoring is also included in Tableau. Those enrolled learn about Tableau’s interface and how this program is used to create a range of charts. Students also study how to create dashboards and map data. In the private training sessions, participants can revisit difficult course material or ask questions about content that will appear on the exam. Tuition includes the Tableau Desktop Specialist exam sitting fee and a free exam retake (if necessary), as well as test proctoring. Those who pass the test at the end of this program earn professional Tableau certification, which can be included on the student’s resume to demonstrate their expertise with this tool. Those who are not interested in sitting for the exam can opt instead for an additional hour of private tutoring.
All Noble classes are available live online and in-person in New York City. Tuition includes a free course retake for a full year. Zero-percent financing options are available to qualifying students.