How to Prepare for a Data Science Bootcamp
A quick guide to preparing for a data science bootcamp. Follow these tips to get ready for a bootcamp and start your data science education.
A cutting-edge career in data science will allow you to work at the forefront of industries like manufacturing, healthcare, and FinTech. If you have an analytical mind and work well with mathematics, data science could be the career for you.
Data science is a multidisciplinary field that combines computer science and statistics to gain business insights. With companies amassing large amounts of data, the objective of a data scientist is to explore, sort, and analyze data. This is done by a combination of computer science, modeling, statistics, and math.
In order to enter the field, a fantastic option is to take a data science bootcamp. In just a few months, you’ll acquire essential data science skills. Certainly, these newfound abilities will allow you to work to garner actionable business insights for your ideal company.
What is a data science bootcamp?
A data science bootcamp is an immersive, project-based, in-person or online learning program. These courses are immersive — and often intensive — to transform your current skill set and help you quickly land a job in data science.
Typically, data science bootcamps help you build technical skills, network, and learn from data science experts. Since the goal is to help you get a job quickly, a quality bootcamp will have expert instructors, help you build a job-ready project portfolio, and provide dedicated career services.
Of course, not all bootcamps are created equal, so be sure to do your research.
For example, our 15-week data science bootcamp at Flatiron School helps you to:
Learn a comprehensive curriculum from experienced data scientists
Graduate with a project portfolio that wows potential employers
Study at your own pace with our flexible learning options
Get 1:1 career support to help you score a job you love
By the end of any in-person or online program, you will have the skills and experience to extract, transform, and analyze various data sets. Additionally, you’ll have the confidence — and help from supportive career coaches — to dive head first into a promising career in data science.
What prior experience or knowledge do you need before starting a bootcamp?
Depending on the bootcamp, you may have to meet certain standards for entry. However, there’s no need to panic. You don’t need an expert level of knowledge. Usually, a basic understanding of Spark, Python, or SQL and a familiarity with statistics will suffice.
Fortunately, you can prepare on your own if you don’t have this basic knowledge, and there are ways to brush up on your math skills.
What you need to start learning data science
A role in data science mainly involves math and programming. To expand, data scientists utilize math including calculus, algebra, and statistics. This permits them to use algorithms effectively in their models and iterate on the modeling process.
With this in mind, they are able to build predictive models that extract insights from a group of data using a programming language such as Python coupled with machine learning.
Before joining a bootcamp, consider developing or honing your own data science skill set. Get started by checking out these three steps to brush up on your math and programming skills, examine machine learning, and more.
You need to brush up on your math and statistics skills
While some of you may immediately fret about how much math you need to know, you may be pleasantly surprised to learn that you don’t need a college degree.
Prior to starting a data science bootcamp, you’ll need to know some basic math:
Calculus: It’s important to understand the principles of calculus
Linear algebra: Understanding the principles is essential to modeling efficiently.
Probability and statistics: If you don’t have a background in probability and statistics, you need to be willing to invest in learning it to become a practicing data scientist.
To clarify, if you avoid math at all costs, you probably won’t be successful in the data science field. However, if you’ve taken math in high school or introductory classes in college, you only need to refresh your skills. Invest some time to improve your familiarity with probability and statistics. Further, re-learn the principles underlying calculus and linear algebra.
Provided that you have some basic know-how and are willing to spend some time polishing your skills, the math should not get in the way of you becoming a professional data scientist.
You can take free intro to data science workshops
Still uncertain? Try out Free Data Science Prep Work to see if you like the topics. In our intro to data science lessons, you’ll gain a working knowledge of Python, visualization, and more.
You can decide if data science is right for you before committing to a course. In addition, a little preparation goes a long way. Taking advantage of our Data Science Prep Work will jumpstart your foundational knowledge, empowering you to start day one of a bootcamp with confidence.
How do you set up your professional data science environment?
Data science is growing both in terms of people and models inside organizations. To this end, collaboration (including accuracy and processing time) between team members is critical. Some common blunders are too theoretical of channels, missing code, or version conflicts. In light of these challenges, data scientists use a professional data science environment. This ensures that they use the same platform, storage, data and model pipelines, and configuration.
Whether you just want to get a feel for what data science entails or if you’re ready to upgrade your career, setting up a professional data science environment on your computer is key.
Start with your data science computer setup
Due to the fact that companies are dealing with large data sets, powerful computing is needed. On the job, you’ll work with your team in a data science environment that likely runs on a GPU to avoid processing lag.
Whereas deep data sets need big processing power, you can easily set up and run a professional data science environment on your own computer. This is especially true when you are just starting out in the field and also because you’ll usually use a remote server for any computing-heavy projects.
Data36.com suggests the best computers/laptops from data science are:
MacBook Pro 13″
Dell XPS 13 or Dell XPS 15
Dell Inspiron 15.6″
Lenovo Thinkpad X or T series
In the end, it doesn’t really matter which computer you choose. Nevertheless, you’ll want to take into consideration your preferred operating system (Mac, Windows, or Linux), portability, and how to set up your professional environment.
Set up a professional data science environment
With the purpose of getting some hands-on practice with popular data science libraries, you’ll need to set up a professional data science environment. What is a professional data science environment? It’s a platform that data scientists, business analysts, developers, and managers can all benefit from by performing many types of analysis and extrapolating.
Professional data science includes:
Python 3.x: Most data scientists use Python programming language to write their code.
Jupyter Notebook: Insert comments in between your code to show your thinking process and collaborate more easily with colleagues by using Jupyter.
Anaconda: The easiest way to install Python and Jupyter is through the Anaconda distribution.
Git: This version control tool will allow you to document the changes you make.
GitHub: Github is a website where data scientists can save their work and share it with team members or the public.
Set up a professional data science environment on your computer, and start analyzing!
What jobs can you get if you start a data science bootcamp?
As technology becomes a larger factor for everyday companies, companies are compiling more and more data. They need someone to analyze the stats and extract business-related insights that will help their companies thrive.
That’s where data scientists come in.
Data science is an in-demand skill that companies need to make smart decisions with data. As a matter of fact, it’s one of the top jobs according to Glassdoor’s 50 Best Jobs in America list. And, jobs in data science pay well, too. To illustrate, the average data scientist salary is $115,152* as reported by Glassdoor.
Possible jobs you can land in data science, as well as average entry-level salaries (in June 2021) in the US are:
Data Scientist: $90,721 /yr
Data Analyst: $40,031 /yr
Data Engineers: $113,740 /yr
Junior Data Scientist: $101,308 /yr
Data Architect: $35,496 /yr
Business Analyst: $54,254 /yr
Moreover, graduates from data science bootcamps are getting hired swiftly. See our 2020 jobs report for more information.
In short, the future is bright for upcoming data scientists.
In summary, data science is a great career for inquisitive, analytics-driven individuals. This in-demand field offers a world of career possibilities for those that are ready to dig in. What’s more, you get to enable businesses to make wise choices while getting paid a competitive salary.
Prior to taking a data science bootcamp, you should brush up on your math and programming skills. Also, don’t forget to check out our free lessons and set up your professional environment on your home computer or laptop.
Does a thrilling career in data science sound right up your alley? Apply Now for our bootcamp.
Disclaimer: The information in this blog is current as of 15 July 2021. For updated information visit https://flatironschool.com/.
Disclaimer: The information in this blog is current as of 15 July 2021. Current policies, offerings, procedures, and programs may differ. For up-to-date information visit FlatironSchool.com.
Posted by Tristina Oppliger / July 15, 2021
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