Start your data
Whether it’s a small business or a large corporation, tech companies need people that can help understand and utilize their data to inform business decisions.
Our free data science lessons are a great place to start learning about interpreting and manipulating data, why it’s important, and how these skills are used to help organizations and businesses.
Try a free data science lesson.
These free lessons from Flatiron School are intended to give you a “feel” for the Flatiron School experience: no fluff, no filler, just delivering real value. Here are some of the fundamentals you can expect to learn from our free data science workshops.
Learn Python for free.
Here, you’ll learn about Python, one of the most essential data analysis programming languages.
It’s beginner-friendly, and you’ll learn more about how and why data scientists love utilizing Python. If you want to know more about how coding works with data analysis, you’ll want to try this one.
Intro to data visualization.
In “Intro to Word Clouds & Frequency Tables,” you’ll learn basic data visualization techniques, and practice data sets using word clouds and frequency tables to analyze song lyrics as your data set.
Learn more about how Python executes basic data visualization techniques.
Learn about binomial distributions.
This lesson is suited for intermediate users and up. It’s a bit too intense for beginners who don’t know much about data analysis. But, if you take our first two lessons, you’ll be ready to jump in!
Here, you’ll learn about designing and visualizing data experiments, the Bernoulli method, and using Python to analyze the results.
Career Prep Lite
Thinking about a career in tech, but not sure how to get there? No matter your background, Flatiron School career coaches can help craft your personal brand and get you interview ready.
This lesson is a sneak peak into the career coaching you could receive as a student at Flatiron School.
Day In The Life Of A Data Science Student
Thinking of enrolling in a data science course but not sure what to expect? In this post, we cover the typical day-to-day schedule of a full-time student.
Data Science Career Paths
In the modern digital age, data is now the currency of business, and data science career paths are in-demand. In this post, we’ve collected standard job titles, their typical requirements, average salary, and the required skillset to hold them.
According to LinkedIn’s 2020 Emerging Jobs Report, data science is booming. Data scientists are at the top of the list as the #3 emerging job field in the U.S., with 37% annual growth. So, yes, data science is worth learning because this career is in high demand. Top industries that hire data scientists include information technology, computer software, financial services, and medical research. If you like to know and predict why things happen, data science is the career for you. Data scientists study stories, insight, and patterns from large data sets to predict outcomes and make decisions.
It depends. To learn data science, you should have a background in math and feel comfortable with algebra, calculus, and statistics. If math feels easy to you, then it should be easy to learn data science. Here’s a rundown on the math involved in data science.
Interested in learning data science but your math skills are rusty? No problem. Check out these resources on how to brush up on your math skills.
Like with most technical roles, different roles rquire different skills.
Overall, Python is by far the most popular language used by data scientists. It’s often the go-to choice for a range of tasks for domains like machine learning, deep learning, artificial intelligence and other popular forms of technology.
Java, SQL, and Matlab are also commonly used by data scientists and some analysts.
Learn more about the best data science programming languages to learn here.
To start learning data science you should brush up on advanced math skills like algebra, calculus, statistics, and linear algebra. Next, get an intro to coding. Check out this list for some great resources on how to start learning data science.
While there are no required prerequisites to apply to our data science program and we welcome beginners, we do recommend students explore our free data science workshops before applying, as this program can be very difficult for beginners. It’s important for two key reasons:
- The easiest way to determine if you want to pursue a career in data science is to see if you like coding.
- We want to fill our community with people who see data science as a passion and who want to launch lifelong careers as data scientists. It’s much easier to show that you’re passionate and dedicated by taking the initiative to get started first. Even if you’ve only worked through a few lessons, showing a little effort and curiosity about data science speaks volumes in your application.
- How to retrieve data from outside sources and organize data using Python
- Create beautiful visualizations to present key findings
- Explore data and write down multiple hypotheses for further analysis of the data
- How to perform A/B tests
- Build machine learning API that outputs results of an analysis
- Apply and use Big Data
- Learn Presentation techniques to better share conclusions about approach and analysis to key stakeholder
The first step is to fill out a written application. Once you submit your application, you will hear back from our Admissions team regarding next steps. If your application moves forward, you will be invited to schedule a video call with a member of the Admissions team to better understand your learning needs, career goals, and whether the program is the right fit for you. Students may be required to complete an assessment as a part of the admissions process. After a technical interview, you will receive an Admissions decision within a few business days.