By blending statistics, programming, and problem-solving, this skill set lets individuals analyze and interpret data to direct essential decision-making processes. Though it’s not as flashy or exciting as programming or coding, data science offers high schoolers plenty of career opportunities
In fact, teenagers interested in technology, math, and business jobs will benefit from learning data science early, even as soon as their pre-teen middle-school years. Tackling these early lessons can help open doors to exciting career opportunities and bolster their educational process. But with so many courses available, how can students choose the best one? Here’s some information to help make this decision-making process a little easier for teen students.
Why Should High Schoolers Learn Data Science?
In today’s incredibly competitive market, teenagers must plan their careers as early as possible. While they don’t have to make any permanent choices just yet (and still have lots of room for fun before graduating), laying the foundation for their success as adults should start in middle or high school. Thankfully, mastering data science concepts helps teens build toward a rewarding, exciting, and prosperous future. Just a few reasons they should learn this topic include:
- Diverse Market Options: Data science is remarkably diverse and is currently used in industries like healthcare, finance, sports, and marketing. As a result, just about anybody can benefit from learning this popular and rewarding set of skills.
- High-Earning Careers: Mastering data science helps students prepare for careers as diverse as AI, machine learning, and business analytics. These jobs are some of the highest-earning and most in-demand positions available today.
- Problem-Solving Skills: Learning data science equips students with tools to solve real-world problems and make data-driven decisions. As a result, they can find jobs in non-tech positions, including project management and executive decision-making.
- Soft Skill Development: Data science not only helps students develop essential tech-based abilities but also expands their soft skills, such as critical thinking, analytical reasoning, and planning. This knowledge is applicable in just about any field today.
Considerations for Choosing a Course
With dozens of potential learning opportunities available, high schoolers interested in data science should talk with their parents very carefully about what class makes sense for their needs. Put simply, these learners must consider many factors, including a program’s cost, scope, and difficulty, to ensure they pick the best option for their needs. The following examples are just a few elements they should seriously consider before signing up for a program.
Topics of Study
Data science offers a diverse range of potential study topics. These include Python, which is the most popular language for data science, alongside various tools and libraries. A suitable program will cover topics as diverse as Pandas, NumPy, and Matplotlib to solidify a teen’s skills.
Class Difficulty and Personal Coding Experience
Teens must honestly assess their understanding of data before signing up for a program. Do they need beginner-friendly courses to learn about essential, fundamental concepts, or do they somehow have enough experience to study advanced statistical concepts in their lessons?
Course Format
Within the training industry, classes typically break down into various formats. These include self-paced, instructor-led, or project-based learning sessions. Students should pick an option that feels right for their studying style to ensure they’re comfortable with their education.
Hands-On Projects
Any data science program worth taking should include high-quality projects that allow students to apply their skills to real-world datasets while building a portfolio of great work. Courses should also offer industry-recognized credentials or a completion certificate showing off their skills.
What High Schoolers Can Do With Data Science
Taking data science bootcamps in high school helps students lay the foundation for later educational success in this field. But do teenagers benefit immediately while learning this skill set? Absolutely! Since teens aren’t always known for their limitless patience, readers will be happy to know that mastering this subject provides concrete advantages to attendees before they get to college. After learning data science, students can use its many techniques to:
- Analyze sports statistics to predict outcomes, which can be a fun way to enjoy competition, especially for teens who may not be naturally athletic
- Use machine learning to advance into artificial intelligence, a field that suddenly took over the market in 2023 and which is likely to become even more prominent
- Work on climate change or social impact projects with data analysis, a process that may help them when preparing for intensive and interesting science projects
- Participate in hackathons and competitions like Kaggle challenges to build their resume, qualify for scholarships, win some money, and meet cool new people
Furthermore, learning data science now, while they’re still in high school, helps teenagers potentially skip early college courses. Earning credits for beginner-level data science programs in this way saves teens and their parents money and makes it easier to finish their education faster. Just as significantly, mastering data science early can help lay the foundation for non-tech careers, including marketing, healthcare studies, and other data-intensive industries.
Balancing High School and Data Science Learning Demands
The average teenager lives a busy life split between classes, social time, sports competitions, and various group activities. How can they make time for data science amid all this hustle and bustle? It’s a good question that, thankfully, has answers. Students can fit data science into their schedules by following a few simple suggestions. These steps make it simpler for learners from all walks of life to fit regular data science studies into their lives without much difficulty.
Starting Small
Data science can feel overwhelming to learn, and many teenagers may suffer from “analysis paralysis” or difficulty knowing where to start their studies. Beginning with small projects using real-world data helps them focus a little more successfully and may minimize their agitation.
Set Schedules
Typically, it’s wise for teens to create a set schedule for their data science practice. Consistency is critical, and setting aside even a few hours per week can help them master this topic. Honestly, 30 to 60 minutes daily might be all they need to learn expert-level data science skills.
Try Self-Paced Classes
Some teenagers struggle to follow specific learning schedules and may need to study data science around their daily routines. These high schoolers should consider using self-paced courses that allow for extra flexibility, including the ability to complete lessons when they want.
Join Clubs
Teens who struggle to stay focused when studying independently should seriously consider joining coding clubs or online communities for extra motivation. These groups make it easier for social teens to stay focused and also help correct mistakes to offer even better learning support.
Jobs Available After Learning Data Science
Though a single data science bootcamp isn’t enough for teen learners to master this subject, it does help lay the bedrock for their future training. For example, studying early techniques in high school makes it easier for teens to use them in college and improves their abilities. In this way, foundational knowledge can help teenagers progress toward expertise and ensure that they’re satisfied with their learning. A few data science careers students can explore include:
- SQL Developer: An SQL Developer uses this powerful coding language to manage databases and applications. Salaries will vary based on a teen’s region.
- Computer Scientist: As a Computer Scientist, individuals work with computers and data tech and may focus on researching new concepts. Salaries average at $145,000 a year.
- Data Scientist: A Data Scientist works heavily with information technology and can help companies make informed decisions. Earnings typically average at $108,000 annually.
- Data Analyst: Job duties for a Data Analyst include gathering, reviewing, and visualizing large amounts of information to ensure that users understand its application.
- Database Administrator: Working with SQL, Python, and other tools, a Database Administator ensures proper operation. They may earn around $117,000 every year.
- Machine Learning Engineer: A career as a Machine Learning Engineer focuses on creating computer programs to enable machines to gather data and act appropriately.
Benefits of Taking a Data Science Bootcamp
While there are other types of data science learning experiences for high schoolers, bootcamps offer the high-quality support students need to master this topic. Their intensive design works teens through beginner-level lessons, moves them up through intermediate concepts, and helps them master advanced subjects as well. A structured bootcamp provides teenagers with a myriad of unique advantages that help them transition into a successful career, including:
- Guided learning with real-world case studies that help teenagers build their skills, advance their techniques, and transition to more professional-level expertise
- Mentorship from industry experts, typically teachers who’ve worked in data science for their whole careers and who can provide powerful support for high schoolers
- Networking opportunities with professionals through various events, forums, projects, and other activities that help build a strong career network for high schoolers
- Project-based experience that enhances college applications and potentially helps students qualify for even better financial aid opportunities
Why Taking a Data Science Course is Better Than Learning for Free
High schoolers interested in data science may discover free resources like forums, YouTube videos, and free seminars that provide practical but non-comprehensive educational help. At best, these diverse tools can complement data science bootcamps because they answer complex questions that might be missed in classes. However, they don’t rise above a support role because paid courses are far more comprehensive and effective for learning new skills.
For example, they offer accountability because teens will be less tempted to quit if real money is involved. That helps keep students engaged, particularly through structured lessons that cover concepts step by step using hands-on projects that offer practical experience with real-world datasets. Finally, they get detailed instructor feedback that helps improve their understanding and debugging skills and ensures they feel comfortable working with data science tools.
Financing Options for Data Science Courses
Teenagers might find data science bootcamps that cost thousands of dollars to attend, which might be hard for them to justify. After all, they may only have a low-key, part-time job that makes is tough to invest that kind of money. Or they might need support from their parents and find it hard to ask for help. Thankfully, students can explore a myriad of unique financing options that cut back on their expenses and which may work well for their payment needs, including:
- Scholarships: When available, scholarships offer teens financing that doesn’t have to be repaid, which makes these payment options very competitive in bootcamps.
- Financial Aid: Loans and other types of financial aid help teenagers pay for their courses but must usually be paid back after the class and with interest to boot.
- Payment Plans: High schoolers who don’t qualify for loans or scholarships may find payment plans (usually 3-5 installments) work well for their financing needs.
- Free Trials: Some schools or websites offer free trials that help students try out their courses and figure out if data science feels right for their career prep.
Skills High Schoolers Learn in Data Science Courses
During their intensive data science bootcamp, students will gain expertise in many different skills that will help prepare them for exciting and rewarding careers. These include beginner-level concepts that lay the foundation for intermediate topics, as well as the more advanced ideas needed to become an accomplished data science professional. Here are a handful of new techniques and concepts students can expect to master in their data science programs.
Python Programming
Python is not only the most widely used language in data science but also the most popular in the world. Its easy syntax makes it a great first coding language, particularly for serious data scientists interested in expanding into related fields, such as game production and web design.
Data, Preprocessing, and Analysis
Once students know Python, they can start using it to prepare data for statistical analysis. For example, they’ll understand how to process their information, eliminate outliers, and understand trends and patterns that create a coherent and reasonable look at data in powerful ways.
Data Visualization Processes
Knowing how to process and analyze data is critical, but teens should also understand how to visualize it for easier understanding. They’ll master using tools like Matplotlib and Seaborn to create charts and other visual elements that help highlight data relationships and scope.
Machine Learning Basics
Mastering machine learning helps students train simple predictive models based on comprehensive data sets. Just as significantly, it can help them jump into artificial intelligence markets. This industry offers lots of unique job opportunities in exciting and high-earning fields.
How Easy Is It to Learn Data Science?
Data science is approachable for high schoolers with a strong foundation in math and logical thinking. Courses designed for beginners make it easier to learn step by step by building on entry-level concepts into more intermediate and advanced ideas. Note that mastering earlier ideas doesn’t equate to professional competency. A single bootcamp doesn’t prepare a student for a job but does give them the techniques needed to build a more professional understanding.
How Long Will It Take To Learn Data Science?
Basic data science proficiency could take anywhere from three to six months for students who study between 5 and 10 hours a week. More intermediate understanding may take up to a year, while advanced usage may require two years or more. Note that regular practice can improve a student’s learning speed. For instance, data science projects solidify their knowledge and make it easier to prepare for college courses or advance to entry-level positions after graduation.
Best Data Science Courses for High Schoolers
Teenagers fascinated by the world of data science may find dozens of potential courses available near them and online. These many programs provide high-quality training, hands-on projects, great professors, networking opportunities, and mentorship. As a result, it can be tricky for some learners to narrow their options down to courses that feel right for them. Here are a couple of schools and classes that provide high-quality data science education for teenagers.
NextGen Bootcamp
NextGen Bootcamp was founded in 2016 to bring coding education to a young audience. The founder, Zach Cohen, believed that middle school, high school, and college students deserved an effective way to master programming. Since its earliest days, this once-small program has expanded to become an industry leader in high school education. Live online learning sessions, 1-on-1 mentoring, and skilled professors make NextGen an incredibly effective tool for teens.
FinTech Summer Program Live Online
FinTech Summer Program Live Online covers topics as diverse as Microsoft Excel, stock market investing, Python programming, finance, and general data science to help teenagers prepare for the FinTech market. The first half focuses heavily on teaching basic concepts, while the second expands to Python coding, Pandas, Matplotlib, and Sci-Kit Learn. Taking place entirely online, this class offers students nationwide with the chance to master complex data science ideas.
Python Data Science & AI Machine Learning Live Online
Python Data Science & AI Machine Learning Live Online focuses on helping teens master essential foundational Python skills, concepts, and coding techniques to transition into data science education. They’ll work online with expert instructors in small classes in a rewarding, real-time environment. As they craft real-world projects for their portfolio, they’ll study topics like Pandas, Madplotlib, Sci-Fit Learn, and machine learning to expand their skills even further.
Horizon Inspires
Horizon Inspires, founded in 2016, helps high school students create research projects to expand their education and prepare for later training. Available in person in Jersey City, Washington D.C., and Beijing, China, this school also offers online sessions for students worldwide. With a curriculum focused on providing hands-on projects, access to research projects, and competitive tournaments, Horizon Inspires offers many advantages for teens.
AI, Machine Learning, and Data Science
AI, Machine Learning, and Data Science offers a comprehensive introduction to machine learning, a critical skill for data science and artificial intelligence. Students will learn about Python programming, data science mathematical principles, various algorithms, and the theories driving these concepts. Students choose from an intensive research topic list and collaborate with their professor online to finish it to perfection before graduation.