Our programs offer training in the main technological areas in demand today: Software Engineering, DevOps, Cloud, Artificial Intelligence, Machine Learning, Web, Mobile, and Full Stack Development.

Data Scientist

About The Program

Transforms data into knowledge through quantitative and programming methods together with her expertise, creating value for your company

Data scientists are a new breed of analytical data expert who have the technical skills to solve complex problems – and the curiosity to explore what problems need to be solved. They’re part mathematician, part computer scientist and part trend-spotter. And, because they straddle both the business and IT worlds, they’re highly sought-after and well-paid. Who wouldn’t want to be one?

A lot of current jobs are being substituted by Data Scientist, which are analyst with super powers. Set your skills up to date and open the doors to keep growing in your job.

Typical job titles: Data Scientist, Data Engineer


Python, R, Jupyter, Pytorch, Pandas, Tensor Flow, Keras, Seaborn, SQL, noSQL, Splunk, Tableau, Data visualization

Get Into Top-Tier Development Jobs

Job descriptions vs what you’ll do at Code U

TECHNICAL SKILLS Python, Pytorch, R, SQL and noSQL databases, Splunk, Tableau or data visualization tools, Jupyter, Panda, Python, Pytorch, R, SQL and noSQL databases, Splunk, Tableau or data visualization tools, Jupyter, Panda
SOFTWARE EXPERIENCE Experience building and developing data models, familiarity with the software development cycle, ability to handle complex data sets including collection, storage, extraction, and visualization Build multiple data models with large and complex (and unstructured) data sets, collecting, storing, and displaying data with the goal of impacting business decisions, reflective of real data science projects
SOFT SKILLS Problem solving, creativity, strong written and verbal communication, get-it-done attitude Structured problem solving, creativity, strong written and verbal communication and collaboration skills, get-it-done attitude

Program Options Available

Full-time and part-time programs available remotely.


Our full-time available dates.

(30-40 hours/week)

September 17, 2020 - Online

Duration: 7 months

September 17, 2020 - On campus

Duration: 7 months


Our part-time available dates.

(15-20 hours/week, Flextime)

September 17, 2020 - Online

Duration: 10 months

September 17, 2020 - On campus

Duration: 10 months


What you’ll cover throughout your learning journey. Direct entry to Seasons is available.


Basic software engineering principles, variables, functions, loop statements, if statements, basic algorithms and data structures.

Python, IDE, Terminal


Cover fundamental computer programming concepts and learn the basics of C. Build a solid foundation in back-end programming including pointers, arrays, strings, algorithms, hash data structures, software architecture, blockchain basics and more.

C, IDE, Assembly


Learners move on to Python and the fundamentals of machine learning, covering regressions, training sets, structured vs unstructured data, and data collection, display, and storage. Learners also cover some of the cloud-based tools available for ML.

Python, Pytorch, Jupyter


After getting a handle on Python, learners advance deeper into machine learning, large/complex data sets, business principles and the use of data to improve key business outcomes, and how data can be a strategic asset to a business. Learners complete multiple real-world, larger projects.

Python, Panda, Tensor Flow, Keras, Jupyter


Learners complete a final program project that aligns with the industry in which they want to get a job. The project must be about 3 months in duration and of significant technical difficulty. Learners will also contribute to open source projects from Kaggle and simultaneously complete 40 technical interviews.

Python, Panda, Tensor Flow, Keras, Jupyter

A Week at Code U

Get to know how your week at Code U looks like.


14:00 - 22:00

Self Study


14:00 - 22:00



14:00 - 22:00



14:00 - 22:00

Q and A session


14:00 - 22:00



9:00 - 13:00

Optional group study

Learning Top Skills is Tough

Learning skills is like learning a sport, a musical instrument, or cooking: it takes time, learning by doing, trial and error, and lost of practice. NBA players don’t get good by watching lectures or videos. Skills-based learning at CODE U is TOUGH.


The key to our programs is to not give up. No matter how difficult the problem is in front of you, do not give up. Great engineers do not give up but instead apply structured problem solving.

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How Learning Works

What you will be doing throughout the program.

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Each season has a series of projects to complete that last 1 day to up to 3 months. These are problems and challenges to build software based on certain requirements and restrictions.

One example of a project would be to build a task-management software with tags, permissions, and a basic user interface.

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Each week, participants will have 1-5 coding exercises to complete. These are accessed through our software and your code is auto-graded to ensure it’s is up to speed and functioning. This is part of the learning process. We have over 800 exercises in our library with thousands of test cases!

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We use role play to develop soft skills such as job negotiations or conflict resolution. We also use role play in technical interview practice where participants will both be the interviewee and the interviewer. This dual-sided perspective is unique to our program & helps build better interviewees.

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Our system is gamified, meaning that you will earn and spend “Qpoints.” As you complete peer code reviews, you earn points and as you submit your projects for review, you will spend Qpoints.


What To Expect

At Code U, you are responsible for your learning, just as you would be responsible for your work in a job. Problem-based learning involves finding, trying, and building solutions. With no single source of truth and no answers provided, it’s up to you to figure out how to make your code work, when and how to ask for help, and how to successfully build software in a team.

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What Sets Us Apart

Silicon Valley Standards

We train to standards set by Silicon Valley for full stack developers. This means the level is much higher than that of bootcamps, and higher than that of CS degrees. Your specialty is being an elite developer at a world-renown level.

Technical Skills & Knowledge

Thanks to the depth and breadth of our program curriculum, you acquire a level of technical skills and knowledge that learners in other programs or bootcamps simply never acquire.

Strong Back-end Skills

The vast majority of bootcamps don’t cover data structures or algorithms. CS degrees don’t cover hands-on application of theory or actually developing software architecture. We cover both and your strong back-end skills and experience with databases, data structures, and algorithms will set you apart from other candidates.

Depth of Technical Portfolio

Learners develop a technical portfolio that has depth and shows the extent of their technical skills and ability to handle databases, deployments, and development. Neither bootcamps nor CS degrees offer this.

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Career Support

Our entire program is designed to make you a great candidate. During the final Season, you will complete 40 technical interviews, gaining experience and practice for real technical interviews.

Strong Software Foundations

You gain strong foundations with advanced algorithms and data structures as well as databases and coding norms.

Strong Technical Portfolio

Thanks to our deep project-based learning approach, you naturally generate a technical portfolio that shows what you can do.

Proven Soft Skills & Problem Solving

Employers want people with strong, structured problem solving skills. We help you develop such skills and how to think when approaching problems and team projects.

Confidence in Interviewing

Because you practice so many interviews and have a strong foundational base in data structures and C programming, you can have confidence when you go into technical interviews.