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Why learn Data Science?
Today, data scientists are employed at early-stage startups, Fortune 500 companies, government and nonprofit organizations, and virtually anywhere in between. Numerous activities fall within the umbrella of ‘data science,’ from business analytics to database maintenance to machine learning. These roles are amplifying (and, in some cases, replacing) traditional jobs across industries like insurance and government, taking on big initiatives from cyber security to statistical analysis.
From self-driving cars to dynamic business insights for the world's leading companies, data scientists are changing the world. If you enjoy mathematics and love using data to make decisions, a career in data science could be for you.
Our data science course curriculum
You’ll also learn to analyze a variety of types of data, build reproducible data analytics and data-powered systems, and understand how to communicate and build on your insights. Plus, you’ll gain fundamental computer science skills and have the chance to build and contribute to real products with a team of students that you can showcase in your portfolio.
Day 1
All Data Science learners are required to attend Lambda School's orientation and are encouraged to complete the precourse work
Data Wrangling and Storytelling, Statistical Analysis, Tests, and Experiments, Linear Algebra
Linear Models, Model Comparison, Applied Modeling, Data Visualization
Software Engineering, SQL and Databases, Productization and Cloud
Natural Language Processing, Neural Network Foundations, Cutting-edge models and architectures
Intro to Python and OOP, Algorithms, Data Structures, Graphs, Hash Tables, and Coding Interview Tips
Participate in our in-house apprenticeship by building a real-world project in a small team
Continuing education and ongoing Job Search Support with your Career Coach
Career services
When it’s time to start job hunting, you won’t be navigating the process alone. Here are three ways we support your career development at Lambda School:
Get one-on-one mentorship from our experienced career coaches who can help you prepare for interviews, build your network, source and apply for jobs, and negotiate your salary.
Get connected to data science job opportunities in our hiring network that match your needs and skillset. You’ll also join our nationwide alumni network who can introduce you to their networks and help you get your foot in the door.
Work for a real company for four weeks and get paid by Lambda School for your time. At the end of the fellowship, your company has the opportunity to hire you full-time.
Of those hired graduates, 94% were hired within 180 days.
Meet some of our data science instructors and coaches
Sai Nivedita Chandrasekaran (Nivi) is a part-time data science instructor. She is currently working on her own project. Prior to this, she worked as a data scientist at Sears. Nivi has received a PhD from the University of Kansas and an MS degree from New Jersey Institute of Technology.
Rachel manages the career coaching team at Lambda School, which supports all graduates in landing high-paying tech roles. Before Lambda, she built up the career and placement function at the Data Science Institute at Columbia University. Her past life is in technical recruiting, by way of Axiom Law & HBO. Connect about anything job search, podcast, or sweet-tooth related.
Nicholas dela Fuente is a full-time data science instructor and data engineer. He has worked in the field of data science for six years and got his undergraduate degree in physics and economics. Prior to this, he worked as a data scientist at Mayo Clinic doing research on brain plaques.
Brian (Lingchuan) Hu is currently a lead data scientist in Data Analytics Spoke in the Chief Administration Office (CAO) at USAA, a fortune 100 company that provides a full spectrum of financial services to the customers. Brian leverages a variety of machine learning techniques to build data science solutions for the various departments within CAO, with the ultimate goal of increasing operational efficiencies, reducing expenses as well as minimizing the operation related risks.
Previously he was a lead modeling analyst at Enterprise Modeling team within Treasury, CFO. He leads multiple model development projects including model development and implementation for capital and regulatory purposes (Economic Capital, Bank/Enterprise Stress Testing). Brian also helped lead many other projects, including (Enterprise Finance) COE model standard and guideline development. Prior to that Brian worked as a Sr. Quant Risk Analyst at Modeling Risk Management. He worked on a variety of model validation projects to identify key risks for financial models used in USAA, including P&C models, operational risk models, investment models, market risk models and member demographic models. He also contributed to several external validation projects.
Prior to joining USAA, he worked 3 years as Sr. quantitative risk modeler in the CCAR (Comprehensive Capital Analysis and Review) department, Chief Risk Office at M&T Bank. He was involved in building a variety of stress testing models, including commercial and residential loan credit risk (PD, LGD, EAD) models, operational risk model as well as PPNR models.
Brian holds a Ph.D. in Biostatistics from the University of Texas Health San Antonio, and Master of Science in Computational Finance from University of Washington.
Vignesh is a one of Lambda School's part-time data science Instructors. He is also a full-time data science at Data Society. Previously, he was a senior quantitative analyst at Bank of America and a quantitative analyst at the Federal Reserve Bank of New York. Vignesh received an M.Eng. in Systems Engineering from the University of Virginia and a B.B.A. from Emory University’s Goizueta Business School.
Lambda School strives to provide a world-class support experience to all applicants, learners, and alumni! Danny Stone has 10+ years in the customer service world, ranging from financial services, entertainment, and technology. He joined Lambda School in August 2019 and works closely with all departments in the school. Danny's service methodology is to provide top-of-the-line support and to always strive to go above and beyond. In his spare time, Danny loves spending time with his wife, playing video games, watching movies, and taking road trips.
Marygrace came to Lambda School after 8 years of working in traditional university settings with learners of all ages and backgrounds. She earned a Master's degree in Education at San Francisco State University, and has a deep interest in equity in education. Who has access to the tools and skills to build a better life? How do we address inequities and build a world where all can thrive? Lambda School fits perfectly in this view - creating opportunities for folks to change their life circumstances. In her spare time, she hangs out with her spouse and two kids, plays computer games, and crochets.
Course schedule
- 8 hours of mandatory live instruction
- Daily projects, due at midnight PST
- Daily warm-ups, due at 9am PST
- Friday sprint challenges, due at 5pm PST
- Optional support hours every day
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Upcoming data science course start dates
Oct 25, 2021
Apply by
10/8/21
Enroll by
10/13/21
12 months
Orientation:
Wed, 10/20/21
Class length:
6 months
Jan 10, 2022
Apply by
12/10/21
Enroll by
12/15/21
12 months
Orientation:
01/05/2021
Class length:
6 months
Jan 10, 2022
Apply by
12/10/21
Enroll by
12/15/21
12 months
Orientation:
01/05/2021
Class length:
6 months
Admission Requirements
Data Science Admissions Process
Next, you’ll agree to the Lambda School Privacy Policy, which tells us that you understand how we might use your information and how we protect your data.
Once you fill out all the required fields and hit “Submit,” you’ll be redirected to the Lambda School Admissions Dashboard. There, you'll fill in your personal information, tell us about your background, and agree to the attendance policy – Lambda School is an immersive experience and we require 95% live class attendance to graduate.
Then, you'll select whether you’ll pay tuition upfront or sign an Income Share Agreement (ISA). You can learn more about the ISA by watching this 1-minute ISA intro video, or by checking out our Frequently Asked Questions page.
Lastly, you'll choose which program you want to enroll in. Not sure? Take this short quiz to get matched to your perfect course.
After you complete your application, it will be sent to our Admissions Team for review. Applications to Lambda School are assessed on a rolling basis. If you’re selected to proceed with the application process, we’ll send you an email in 1-2 days.
Now we'll ask you to complete a brief assessment called the Criteria Cognitive Aptitude Test, which helps us predict your ability to be successful at Lambda School and in your future career.
The CCAT consists of 50 questions, and you will have 15 minutes to complete the test. It's normal not to finish all 50 questions in the time allotted, so take a deep breath, do your best, and find a quiet place to work before you begin. You can find a free downloadable CCAT study guide here.
Data Science Skills Challenge
Data Science applicants are also required to complete a Data Science Skills Challenge at this stage which must be passed with a score of 11/15. You will have 45 minutes to complete the challenge. See our DS Challenge study guide for help preparing!
Verify Your Education
If you live in DC, CA, or TX, we'll need to verify your educational background. You can upload one of the following:
1. College Transcripts
2. High School Diploma
3. GED Certificate
Alternatively, you can take the Wonderlic basic skills test. More information about ATB tests can be found here: https://wonderlic.com/atb-testing-state-level/.
Choose Your Start Date
First, you need to choose your desired start date via the link in the email. This link will send you to a confirmation form, where you’ll let us know when you’d like to begin your Lambda School course, and you'll be asked to share some optional demographic information with us.
Along with the email asking you to choose your start date, you will be prompted to read through the Lambda School Catalog (this will be sent to you in an email) to make sure you understand and are willing to adhere to our policies. You can check the Catalog out ahead of time at lambdaschool.com/catalog to learn more about Lambda School’s style, structure, and ethos.
Sign the Enrollment Agreement
After you’ve reviewed the Lambda School Catalog and chosen your start date, you’ll be sent the Enrollment Agreement to review, initial, and sign.
Confirm Tuition Payment Method
If you elected to pay $0 upfront and sign an Income Share Agreement (ISA), or if you sign a California retail installment contract, when you filled out your application, you’ll be directed to sign the appropriate contract. If you selected the $30k upfront option, you'll receive an invoice via email.
If you need to change your payment method, feel free to reach out to us to discuss your options.
All of the above must be completed by our enrollment deadline for the class of your choice.
During Lambda Launch, you’ll learn effective strategies for remote learning, be briefed on our academic expectations, get a crash course on how to use the software and tools needed for your program, and receive instructions for how to get help. Other than completing your precourse work, attending this orientation program is the best way you can prepare yourself to succeed at Lambda School.
Please note that Lambda Launch attendance is mandatory, and failure to attend may result in your start date being delayed.
Completing the precourse work is not only mandatory, it's essential for your success at Lambda School. The Lambda curriculum moves quickly and learners who do not have prior coding experience may fall behind without self-study prior to day one.
The precourse work will take you about 15 hours to complete, so please plan accordingly so you can ensure that you've completed all of the requirements before Lambda Launch begins.
Ready? Get started with Step 1 and start your application:
