Data Science is a method of drawing insights from data using math, statistics, programming, and business expertise. It usually involves big data sets and automation using machine learning.
Our ideal candidate is motivated, professionally polished, and a natural problem solver. They also have experience with math/statistics, computer programming, and business. However, that person is likely already a data scientist! If you’re hungry to learn, excited about data science, and have some background in any of the above, we think you could be a fit.
No! But a high school diploma or GED (General Equivalency Diploma) is required.
At a high level, we cover the data science pipeline/process, relevant tools & technologies, modern methodologies, example projects, and important questions. More specifically, we have 16 modules: Fundamentals, Statistics, SQL, Python, Regression, Classification, Clustering, Time Series Analysis, Anomaly Detection, NLP, Distributed Machine Learning, Advanced Topics, Storytelling, Domain Expdertise Development, Career preparation, and a Capstone Project. To view our full curriculum, click here.
Our admissions process includes assessments to gauge your understanding of basic statistics and Python programming. However, these skills are something you can build during the admissions process. If you’re interested in data science, we encourage you to go ahead and apply. From there, our Admissions Team will work with you to figure out where your skills currently are and how to prepare for the program.
Yes! As an alum or staff member, if someone you refer completes 75% of our data science program, we’ll give you $500. Make sure they put your name on their application, or you won’t get credit!
In an effort to continue cultivating inclusive growth within the tech industry, we are now offering an exclusive Women in Tech referral program to Codeup alumni. If a woman you refer completes 75% of our data science program, we’ll give you $1000. Make sure they put your name on their application, or you won’t get credit!
*Women in Tech referral program cannot be used in combination with any other existing referral or promotion
We interviewed dozens of employer partners and practitioners to build our program, and discovered something surprising: the ability to communicate your work is one of the most important skills for a data scientist! Of course, you need to be competent in math, stats, Python, and other tools/technologies. However, what separates a successful data scientist is the ability to make their work digestible, relevant, and actionable.
The data science toolkit is constantly changing, and varies shop by shop, but will likely include: Python (and packages like Sci-kit Learn, Pandas, and Seaborn), SQL, R, Tableau, Hadoop, Hive, Jupyter Notebooks, and Github, all of which you’ll learn at Codeup!
Both of these tools can get the job done, and you’ll get a different answer depending on who you ask. While R is historically dominant, Python has emerged as the programming language for data science, and you’ll see more and more companies with job listings that allow for, if not prefer, Python. Python has a robust set of data science libraries like Pandas, Matplotlib, Scikit Learn, and Seaborn, all of which you’ll learn at Codeup.
You’ll graduate with our Certificate of Completion, which is like our diploma. However, we believe (and our employer partners agree) that what matters is what people can do — not what grade, diploma, or label they have. What you’re really graduating with is a new skillset and a portfolio to show off to employers!