Data science is currently one of the fastest-growing and most exciting career paths in the world. It can be applied to virtually every industry and technology is constantly advancing to be able to analyze increasingly large sets of data. The demand for well-trained data scientists is only going to intensify in the years and decades to come. 

Today’s teens are coming of age in a technologically-focused world, which makes them the perfect choice for early exposure to concepts related to data science. While data science itself requires advanced degrees, high school students are more than capable of learning some foundational aspects like Python programming and statistics. Early and frequent exposure to these ideas will help give students a more solid background and help them become adaptable as new technologies and approaches to data science arise. Even if some students ultimately decide that they want a career outside of data science, this foundational knowledge is sure to give them a competitive edge on their job and college applications. 

Books for Beginning Data Scientists

Books can be a relatively inexpensive way to build foundational knowledge in a new topic. They allow students to keep notes that they can refer back to throughout their learning. They are also a good investment since even the most seasoned professionals sometimes need reminders of core concepts. Here are some data science books written specifically for beginners.

1. Data Science From Scratch by Joel Grus: This unconventional book allows the reader to take a lead data scientist position at a fictional company called DataScienster. Throughout the book, Grus walks you through typical problems you might encounter in this position and how to solve them.
   
   

2. Build a Career in Data Science by Emily Robinson and Jacqueline Nolis: If you want insights on the entire process of getting a career in data science, this book is a must-read. It explains the different types of available jobs and can help you decide if this career path is right for you.
   
   

3. Doing Data Science: Straight Talk from the Frontline by Cathy O'Neil and Rachel Schutt: This book is designed to make data science palatable to the general public. It uses real-world case studies and explains algorithms in an accessible way.
   
   

4. Python for Teenagers: Learn to Program like a Superhero by James Payne: This book is specifically geared toward high school students. It provides fun and easy-to-follow examples that guide them through the fundamentals of Python, which is the primary language used by data scientists.
   
   
5. Introduction to Computer Science by Perry Donham: Many data scientists have a background in computer science first. This book details the history of the discipline in the earlier chapters then moves on to discuss hardware, software, and cybersecurity. It is targeted toward high schoolers who have no technological knowledge.
   
   

If you want to learn more about some of the skills you’ll need to become a successful data scientist, there are additional resources you can take advantage of. YouTube offers a host of Python tutorials; even prestigious universities like MIT and Harvard have free lectures available on the platform. High school students who are interested in computer science may be interested in taking the Advanced Placement (AP) Computer Science course. The exam offered at the end of this course is the only College Board accredited test where students show off their knowledge by writing a computer program from scratch. 

Data Science Classes for High Schoolers

If learning data science as a high school student sounds exciting to you, check out NextGen Bootcamp’s data science courses for high schoolers. The school offers in-person data science classes at its campus in New York City in addition to its live online data science classes that can be attended remotely from anywhere in the world. NextGen provides small class sizes for students so they can get the individualized attention they need. Students are also able to retake their courses for free up to one year after the original course date. Courses at NextGen are taught by experienced industry professionals so you can be sure you’re being taught relevant and up-to-date information. 

NextGen offers a Java Programming Camp and a Python Data Science Summer Program in-person and online. Both courses are two weeks for the in-person versions and three weeks for the remote classes. They utilize project-based learning to ensure that students fully grasp these important concepts and retain information after the class is over. Both courses also offer students supplemental material to keep after the course is over. For students who want to learn both of these languages, NextGen Bootcamp also has a Computer Science Summer Certificate program, which combines these two classes. 

Data Science Career Paths

Data science careers are becoming more common in practically every industry. But what do data scientists do every day? They use their creative thinking and mathematics backgrounds to help businesses translate a huge amount of information into solutions they may not have otherwise been able to solve. This work can be applied to healthcare to track the spread of disease, the military where it can be used to identify potential threats to civilians, and even help airlines run more efficiently.

Two of the most common career paths within data science are artificial intelligence (AI) and machine learning (ML). The data that businesses produce is becoming increasingly more complex, and the amount of data is growing exponentially as well. Data scientists develop AI to analyze this amount of data because humans can no longer effectively manage this workload all at once. Artificial Intelligence Engineers are offered a wide range of salaries, but they are typically over $100,000 annually. ML is a subspecialty of the AI field. These engineers design software for businesses to help them make predictions based on the data they collect. A Machine Learning Engineer is by no means an entry-level career; in fact, people in these positions typically have a Master’s Degree or a Ph.D. The average annual salary for a machine learning engineer is about $112,000, but this has the potential to increase over time. Machine Learning Engineers with 20 years of experience can make over $160,000 per year.