Data Science
Data Science
An intensive online data science course for a career in applied statistics and machine learning. Apply now
Python
SQL
Data Visualization
Machine Learning
Linear Algebra
Databases
Statistics & Modeling
Natural Language Processing
Are you ready for an exciting career in data science?
With 26% annual growth, Data Science continues to top emerging job lists year after year. Building on centuries of statistics and mathematics, Data Science uses computational techniques to help the most innovative companies in the world scale. From self-driving cars to dynamic business insights for Fortune 500 Companies, Data Science is changing the world. If you enjoy mathematics and love using data to make decisions, a career in data science could be for you.
Our rigorous coursework combined with hands-on product experience will help prepare you to become a confident data scientist, but we know that there’s more to getting hired than technical knowledge.
Our curriculum also includes intensive professional development starting on Day One. You’ll meet 1:1 with your career coach and job search trainer throughout the program to polish your resume, practice your interviewing skills and source job opportunities, plus you’ll get access to our nationwide alumni network who can help you build your professional network.
Common job titles of Lambda School data science graduates include data analyst, data scientist, and machine learning engineer. Graduates have been hired at Fortune 100 companies, as well as the world’s top startups.
Common job titles of Lambda School data science graduates include data analyst, data scientist, and machine learning engineer. Graduates have been hired at Fortune 100 companies, as well as the world’s top startups.
Data Science Units
0
Lambda Launch
Orientation: Remote Working, Class Structure & Expectations, Required Technology and Support
Orientation: Remote Working, Class Structure & Expectations, Required Technology and Support
1-4
Statistics Fundamentals
Data Wrangling and Storytelling, Statistical Tests and Experiments, Linear Algebra
Data Wrangling and Storytelling, Statistical Tests and Experiments, Linear Algebra
5-8
Predictive Modeling
Linear Models, Model Comparison, Applied Modeling
Linear Models, Model Comparison, Applied Modeling
9-12
Data Engineering
Software Engineering, SQL and Databases, Productization and Cloud
Software Engineering, SQL and Databases, Productization and Cloud
13-16
Machine Learning
Natural Language Processing, Neural Network Foundations, Cutting-edge models and architectures
Natural Language Processing, Neural Network Foundations, Cutting-edge models and architectures
17-20
Computer Science
Intro to Python and OOP, Algorithms, Data Structures, Graphs, Hash Tables, and Coding Interview Tips
Intro to Python and OOP, Algorithms, Data Structures, Graphs, Hash Tables, and Coding Interview Tips
21-24
Labs
Participate in our in-house apprenticeship by building a real-world project in a small team
Participate in our in-house apprenticeship by building a real-world project in a small team
Job Search
Continuing education and ongoing Job Search support with your Job Search Trainer
Continuing education and ongoing Job Search support with your Job Search Trainer
Data Science Course Schedules
Classes are live and online. You must have 95% attendance in order to graduate. Every day is unique, but below is an example of what a day might look like.
Pick your time zone and make sure one of the 3 options below fits your schedule.
(This schedule below is illustrative; actual schedule differs unit by unit, but start and end times for each module remain consistent.)
Pick your time zone and make sure one of the 3 options below fits your schedule.
(This schedule below is illustrative; actual schedule differs unit by unit, but start and end times for each module remain consistent.)
8:00 - 9:00 am
Warm up
Personal time to review the day's materials before instruction begins
9:00 - 11:00 am
Guided Project
Build a project while following the instructor's guidance
11:00 - 12:00 pm
Lunch Break
12:00 - 3:45 pm
Project Time
Build on your own and get help along the way from peers and teachers in Slack
3:45 - 4:15 pm
Project Wrap
Take a daily survey about your progress
4:15 - 5:00 pm
Stand Up
Meet daily with your Project Manager and 6 to 8 students for support
6:00 - 6:30 pm
Warm up
Personal time to review the day's materials before instruction begins
6:30 - 8:30 pm
Guided Project
Build a project while following the instructor's guidance
8:30 - 9:00 pm
Project Time
Build on your own and get help along the way from peers and teachers in Slack
4:00 - 4:30 pm
Warm up
Personal time to review the day's materials before instruction begins
4:30 - 6:30 pm
Guided Project
Build a project while following the instructor's guidance
6:30 - 7:00 pm
Project Time
Build on your own and get help along the way from peers and teachers in Slack
9:00 - 10:00 am
Warm up
Personal time to review the day's materials before instruction begins
10:00 - 12:00 pm
Guided Project
Build a project while following the instructor's guidance
12:00 - 1:00 pm
Lunch Break
1:00 - 4:45 pm
Project Time
Build on your own and get help along the way from peers and teachers in Slack
4:45 - 5:15 pm
Project Wrap
Take a daily survey about your progress
5:15 - 6:00 pm
Stand Up
Meet daily with your Project Manager and 6 to 8 students for support
7:00 - 7:30 pm
Warm up
Personal time to review the day's materials before instruction begins
7:30 - 9:30 pm
Guided Project
Build a project while following the instructor's guidance
9:30 - 10:00 pm
Project Time
Build on your own and get help along the way from peers and teachers in Slack
5:00 - 5:30 pm
Warm up
Personal time to review the day's materials before instruction begins
5:30 - 7:30 pm
Guided Project
Build a project while following the instructor's guidance
7:30 - 8:00 pm
Project Time
Build on your own and get help along the way from peers and teachers in Slack
10:00 - 12:00 pm
Warm up
Personal time to review the day's materials before instruction begins
12:00 - 1:00 pm
Guided Project
Build a project while following the instructor's guidance
1:00 - 2:00 pm
Lunch Break
2:00 - 5:45 pm
Project Time
Build on your own and get help along the way from peers and teachers in Slack
5:45 - 6:15 pm
Project Wrap
Take a daily survey about your progress
6:15 - 7:00 pm
Stand Up
Meet daily with your Project Manager and 6 to 8 students for support
8:00 - 8:30 pm
Warm up
Personal time to review the day's materials before instruction begins
8:30 - 10:30 pm
Guided Project
Build a project while following the instructor's guidance
10:30 - 11:00 pm
Project Time
Build on your own and get help along the way from peers and teachers in Slack
6:00 - 6:30 pm
Warm up
Personal time to review the day's materials before instruction begins
6:30 - 8:30 pm
Guided Project
Build a project while following the instructor's guidance
8:30 - 9:00 pm
Project Time
Build on your own and get help along the way from peers and teachers in Slack
11:00 - 12:00 pm
Warm up
Personal time to review the day's materials before instruction begins
12:00 - 2:00 pm
Guided Project
Build a project while following the instructor's guidance
2:00 - 3:00 pm
Lunch Break
3:00 - 6:45 pm
Project Time
Build on your own and get help along the way from peers and teachers in Slack
6:45 - 7:15 pm
Project Wrap
Take a daily survey about your progress
7:15 - 8:00 pm
Stand Up
Meet daily with your Project Manager and 6 to 8 students for support
9:00 - 9:30 pm
Warm up
Personal time to review the day's materials before instruction begins
9:30 - 11:30 pm
Guided Project
Build a project while following the instructor's guidance
11:30 - 12:00 am
Project Time
Build on your own and get help along the way from peers and teachers in Slack
7:00 - 7:30 pm
Warm up
Personal time to review the day's materials before instruction begins
7:30 - 9:30 pm
Guided Project
Build a project while following the instructor's guidance
9:30 - 10:00 pm
Project Time
Build on your own and get help along the way from peers and teachers in Slack
You could be a
data analyst.
machine learning engineer.
business analyst.
data engineer.
IT system analyst.
data analytics consultant.
digital marketing manager.
Data Science Tuition Options
Pay $0 upfront + ISA
Our Income Share Agreement is $0 upfront + 17% of salary for two years, $30k USD maximum total payment. Must be a US citizen, Permanent Resident, or DACA recipient
Pay $30k upfront
Instead of an Income Share Agreement, students can opt to pay Lambda School $30k USD upfront for tuition.
How to Apply
Check out our Admissions page to learn everything you need to know about applying to Lambda School, including what we look for, requirements and the application process. Here's a quick overview:
Step 1
Apply to Lambda School
Create your student profile, tell us about your background, and choose your track.
Apply now
Create your student profile, tell us about your background, and choose your track.
Apply now
Step 2
Complete Assessments
Take our aptitude test (45 min). Applicants may be asked to provide additional information in the form of a video interview
Take our aptitude test (45 min). Applicants may be asked to provide additional information in the form of a video interview
Step 3
Complete Enrollment Checklist
Provide proof of your education background, sign the Student Policy Agreement, pay tuition or sign your ISA, and choose your start date. You’re in!
Provide proof of your education background, sign the Student Policy Agreement, pay tuition or sign your ISA, and choose your start date. You’re in!
