Data Science

Intensive online training 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

Upcoming Data Science start dates

Oct 26, 2020

Orientation:

10/21/20 - 10/22/20

Enrollment deadline:

10/14/20

Full-time

12 months

6 months

Monday - Friday

8 am to 5 pm PT

choice of Fri, Sat, or Sun

Apply

Oct 26, 2020

Orientation:

10/19/20 - 10/21/20

Enrollment deadline:

10/14/20

Part-time

12 months

6 months

Monday - Thursday

6 pm to 9 pm PT

choice of Fri, Sat, or Sun

Apply

Nov 30, 2020

Orientation:

11/18/20 - 11/19/20

Enrollment deadline:

11/11/20

Full-time

12 months

6 months

Monday - Friday

8 am to 5 pm PT

choice of Fri, Sat, or Sun

Apply

Jan 11, 2021

Orientation:

1/4/21 - 1/6/21

Enrollment deadline:

12/30/20

Part-time

12 months

6 months

Monday - Thursday

6 pm to 9 pm PT

choice of Fri, Sat, or Sun

Apply

Your new career in data science starts here.

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.

Build real products on real teams

Our live, online curriculum is designed with our hiring partners in mind. Classes are remote but interactive and have a rigorous structure so you’ll graduate with all the skills you need to make an impact on day one. Plus, you'll build a real product with a team of 6-8 students from other tracks.

Sprints

0

Lambda Launch
Orientation: Remote Working, Class Structure & Expectations, Required Technology and Support

1-4

Statistics Fundamentals
Data Wrangling and Storytelling, Statistical Tests and Experiments, Linear Algebra

5-8

Predictive Modeling
‍Linear Models, Model Comparison, Applied Modeling

9-12

Data Engineering
‍‍Software Engineering, SQL and Databases, Productization and Cloud

13-16

Machine Learning
‍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

21-24

Labs
‍‍Participate in our in-house apprenticeship by building a real-world project in a small team

Job Search Support
‍‍Continuing Education and ongoing Job Search support with your Job Search Trainer

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.)

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.

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.

Learn more about our Income Share Agreement

Admissions

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

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

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!

Ready to hustle?

Apply now and get free access to the precourse work.

Apply to Data Science