We require all students to be on a MacBook capable of running the most recent operating system and with at least 4 GB of RAM for our web development program and 8 GB of RAM for our data science program. This is not something you need for the admissions process but you would be responsible for it on the first day of class. You do not need to buy any books or software though! Our custom curriculum is all online. The other cost to consider is transportation. Most students buy monthly passes to nearby garages.
We have had students use Chapter 30, 35, and 33, as well as Vocational Rehabilitation Benefits to help cover their tuition costs for our web development and data science programs in San Antonio. After acceptance, you’ll work with our Financial Aid & Enrollment Manager who is our in-house School Certifying Official to see what benefits you have available to you and how those can fit into your tuition plan.
No, Pell Grants are designed for conventional educational institutions like colleges. We’re not college!
Visit our Scholarships page for more information on eligibility and application! We award scholarships about two weeks before a class begins so you must be on the roster by then to be eligible.
After acceptance, you’ll be connected with our Financial Aid & Enrollment Manager who will help you explore the various options available to you including loans, grants, VA Benefits, and scholarships.
Yes. We take a $1,000 deposit to lock in your space in the program. This is your registration deposit. If you end up not joining the class, this is refunded to you. If you do join the class, this goes towards your tuition payment.
There’s no one-size-fits-all answer here, but generally, data scientists spend about 70% of their time on data wrangling, which is the phase of the pipeline that focuses on gathering, cleaning, and preparing data for use. Another 30% of their time is spent on model development, and the remaining time is spent on post-deployment efforts like upkeep, visualizations, storytelling, etc.
You’ll graduate with a full technical portfolio and professional portfolio. You’ll have a busy GitHub, Kaggle, and Data.World profile, as well as a number of projects from the classroom like visualizations, cleaned data sets, reports, presentations, models, and more. You’ll also complete a real-world capstone project, which will be great to present to employers.
We’re focused on helping graduates find jobs as data scientists! But depending on your background and what you like, you can also find work as a data engineer, data analyst, machine learning engineer, and related roles.
Data science is everywhere, including cyber security, SaaS, banking, and retail. Big companies in San Antonio like USAA, Accenture, HEB, and Booz Allen Hamilton work in this realm, as do smaller agencies like Quickpath Analytics.
Most graduates will work as entry to mid-level Data Scientists. Depending on background experience and interest, they may also focus on specific sections of the data pipeline, like Data Engineering or Machine Learning Engineering.
Upon successful completion of the program, you’ll receive a Certificate of Completion. We believe (and our partner employers agree) that what matters is what people can do — not what grade, diploma, or label they have. Programming is more like architecture or design, where people come to interviews with a portfolio. Codeup is about you developing the ability to actually make stuff with code. It’s your responsibility to invest in yourself to grow those skills. We put our money where our mouth is, as we refund 100% of the program tuition if you do not get a job within 6 months. Grades on quizzes, projects and written code are used to monitor your progress through the curriculum, but don’t matter beyond the program.
Each student will graduate with a working, well-engineered project completed. This might be writing a Twitter clone or doing the same for another well-known website. If you were sponsored by an employer, you may produce a project of value for them. We work with you to identify an appropriate capstone project.
Developer Day is when Web Development graduates’ job hunts begin! You’ll start working on locating employment after Developer Day while continuing with our Postwork. This is a set of challenges that you do while interviewing and applying for positions. We welcome you to come to Codeup to work on the Postwork with your fellow grads.
Students work at a range of companies, from small startups to large corporations. Our biggest hiring partners are USAA, Accenture and HEB, but we have plenty of grads go to smaller companies out of Geekdom and around downtown.
Most graduates become entry-level professional programmers with titles like Web Developer, Front-end Developer or Software Engineer. Others get tech roles such as Quality Assurance, Documentation Engineer or Support Engineer. Some graduates use their newfound knowledge to take tech-related roles like Sales Engineer or Project Manager.
Many applicants have told us they want to start their own business. If a student decides to start or operate their own business and/or do consulting, they are no longer eligible for the tuition reimbursement guarantee.
We do two things:
1) We “teach you how to fish.” We work with you on how to manage your career at a high level and also drill down on the mechanics of marketing yourself to employers. This includes things like creating resumes, building online profiles, and managing social media. The benefit of this arrangement is that you can use this information for the rest of your career.
2) We “help you find fish now.” We have dedicated staff members whose job is to find currently available job positions and to connect our graduates with potential employers.
Email us at email@example.com or give us a call at 210-802-7289! You’ll talk with our Employer Partnerships Team so we can best fit your needs. You’ll be first in line to see our graduates, and we’ll prominently display your logo on our website alongside our other partner employers.
The value of Codeup spans technical knowledge of web development/data science, a close family of your Codeup classmates, a network of technology professionals to connect with, and career preparation. Visit Codeup.com/mystory to learn more about life after Codeup and the opportunities you’ll find!
The average salary for data scientists across experience levels in San Antonio is about $110,000. At an entry-level from our program, we project initial earnings to range between $65-$80K, depending on background experience.
You’ll graduate with our Certificate of Completion, which is like our diploma.
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
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.
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.
The average salary of a Web Developer in San Antonio makes around $75,000. As an entry-level Web Developer, the average starting salary will be around $50,000.
We will talk about development approaches, good practices, and more. Our instructors (and our founders!) have been on real-world software engineering teams, so we know our stuff. Finally, we will work with you on interview and presentation skills so you can wow potential employers.
This isn’t HVAC a repair. Programming is a world in constant flux. What’s used in industry today often wasn’t even invented a decade ago. What is used today will not be popular ten or even five years from now. Instead of worrying about a particular stack, we focus on turning you into a well-rounded professional software developer. You’ll be set to go out, learn and work on whatever technology an employer throws at you. That being said, we constantly improve our curriculum to respond to industry trends and demands. We are in close communication with our employer partners to teach updated technologies!
We have two campuses: San Antonio and Dallas. Our San Antonio campus is located at 600 Navarro St – we have two floors with five classrooms. Our Dallas campus is part of the Novel Coworking space located at 701 Commerce Ave – we have one classroom and 2 offices on the first floor!
We keep the ratio of students to instructors as low as possible. Usually, each cohort of 20-28 students has 2-3 instructors.
It is best that you do not work during any of our Codeup programs. Instruction time is from 9am-5pm daily. We have morning (8am-9am) and afternoon (5pm-6pm) study hall with instructors on-hand everyday of the week. Then, there is the homework and labs. Our job is to make you a kick-butt Developer or Data Scientist in a short period of time, so that means it is going to be intense. We won’t tell you what you can or can’t do, but we highly recommend limiting outside engagements during the program. Work and personal commitments tend to be the biggest interruptions to successfully completing our program!
Students have access to our space between 6 AM and midnight. Most students arrive to campus between 8 am and 9 am in order to be ready for when class starts at 9 am. You’ll spend about half of class time in lecture and the other half in supervised, supported project time. We break class for an hour for lunch at 12:30 pm and then class resumes at 1:30 pm. At 5 pm, you’re done with class for the day but most students stick around to keep practicing and working on projects.
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 reqs that allow for, if not prefer, python. Python has a robust set of data science libraries like pandas, matplotlib, sk-learn, and seaborn.
Supervised and unsupervised are two groups of machine learning methodologies. In supervised learning, a data scientist teaches the algorithm what conclusion to arrive at using a known set of possible outputs. In unsupervised learning, a computer identifies patterns without human guidance. More often than not, data scientists work with supervised learning algorithms.
Whenever you see “data” in a job title, you’re working along the data pipeline ranging from capturing high volumes of data to building machine learning automations. A data scientist spans this spectrum, while other roles focus on one phase or another. A data engineer, for example focuses on capturing and storing data sets for others to work with. A machine learning engineer only works with automation and model deployment. A data scientist might work on data collection, data processing, future event prediction, machine learning, and more. Check out this graphic for a visual understanding!
Data scientists do complex work, which non-technical co-workers might struggle to understand. A data visualization is a visual representation of data that is easy to digest.
The data science process has about 7 steps: 1) data wrangling (getting and cleaning data); 2) exploratory data anlysis, statistical inference and data visualization; 3) feature engineering; 4) model development (training, evaluating, optimizing, testing); 5) model deployment; 6) delivery of results (report, story, visualization); 7) model maintenance. You may work on this whole process or a piece of it, but should understand what happens at each step.
Machine learning is what it says – your machine learns as it works! ML algorithms allow your computer to generalize decision-making beyond the specific data set it has worked with, and allows for broader automation.
In its simplest term, this is a family of machine learning methods based on learning data representation, as opposed to task-specific algorithms. Deep learning allows an automatic feature detection in place of manual feature engineering.
Big data differs from in-memory data, in that it is too large and complex to manage on a local computer. It’s defined by the big V’s: Velocity (data that’s collected at great speed), Volume (large amounts of data), Variety (different forms of data), and Veracity (uncertain quality of the data).
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.
We interviewed dozens of employer partners and practitioners building this program, and discovered something surprising: ability to communicate your work is one of the most important skill sets for a data scientist! Of course you need to be competent in math, stats, python, and other tools/technologies. But what separates a successful data scientist is the ability to make their work digestible, relevant, and actionable.
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.
Nope! We care more about skills and attitude than a piece of paper!
Our ideal candidate is motivated, professional, and enjoys solving problems! We want people who are hungry to learn, ready to work hard, and excited to work as developers!
The admissions process can take around 2-3 weeks. This varoes as each candidate may be working on a different timeline. Keep in mind that you’ll also want to give yourself time to work on your tuition plan and pre-work assignments so we suggest trying to apply about a month and a half before your desired start date.
No! We take candidates from all different types of backgrounds: recent high school or college graduates, transitioning military, career changers, and many more. However, you must be 17+ years of age.
We don’t provide housing but have many students who attend Codeup from out of town. They usually look for 6-month leases, Airbnbs, or extended stay hotels.
Nope! We do have students who come through with coding experience and Computer Science backgrounds. However, we also have students who are really successful without having prior technical experience! That is why we have the admissions process that we do – to be sure our program is a good fit for you. We want to be sure you’re set up for success! To further ensure that, after acceptance students complete about 30 hours of pre-work to prepare you for the technical part of the program.
Web development and Data Science are both in-demand fields, but they’re very different! If you’re considering coming to Codeup, we recommend you think about these two questions: 1) what is your technical background? Our web development program doesn’t require any background, and has a faster ramp-up to admission, while Data Science requires background experience in math, stats, and programming. 2) What do you want to be working on daily? While some parts of the jobs will overlap, like writing in a programming language, most everything else is different. Web development will train you to build websites and applications, while Data Science will train you to draw insights from data sets. Still not sure? Talk with our Admissions Team!
Yes. Students must provide their own Apple laptop capable of running the most recent operating system, with at least 8GB for both programs, and the laptop can be made no earlier than 2015. It doesn’t need to be brand new – many of our students have good luck with refurbished options. You do not need a laptop for the admissions process, you’d just need it by your first day of class.
We do not. We are a career accelerator looking to help adults transition into careers in tech. To enroll, students must be at least 17 years old. Our average student age is around 30 years old. However, we definitely encourage kids and teens to start exploring tech early! We’re active partners with Youth Code Jam in San Antonio and there are many other great organizations who are dedicated to helping kids learn technical skills.
No. Both of our programs are full-time and in-person. We believe learning a new skill in an immersive, full-time environment is the most effective way to jump into a new career. Both software development and data science are challenging topics, and to be successful, you’ll need a brain that’s not exhausted from a long day at work. Part-time options simply aren’t as effective as our full-time programs, which asks students to turn their learning into a full-time job.
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.
After applying online, be on the lookout for an email with the subject line “Codeup Admissions: Next steps”. After working through the admissions process, you’ll receive a phone call from an Admissions Manager letting you know if you’ve been accepted. If at any point you’re not sure of your application status, please don’t hesitate to reach out to firstname.lastname@example.org!
Not exactly. For both our web development and Data Science programs, we have a rolling admissions process and accept qualified applicants on a first-come, first-serve basis. Once a class is full, we’ll start accepting students onto a waitlist. If you’re accepted but the class is full, your acceptance rolls over to the next start date. We also want to be sure you’re prepared and set up for success in class, including having time to get your tuition plan in place and working through our pre-work assignments. This means we generally do not accept new students into a class within two weeks of the start date. If you’re interested, start your application today! Apply today