Data Science

Learn the Technology

We’ll teach you the languages, tools, and techniques you’ll be using as a data scientists in the real world. This bootcamp focuses on…

• Critical thinking and project selection
• Python and open source libraries for data science
• Visualization tools to explore data sets for further processing
• Data wrangling techniques to prepare and refine raw sets
• SQL queries and useful syntax for access to data
• Machine learning algorithms
• Cloud based Jupyter notebooks and other deployment tools
• GITHUB, Slack, Agile development tools

Full-time bootcamp schedule

June 2021
Dates: June 7 – August 27
Times: Mondays-Thursdays 8am-5pm
Application Deadline: May 14, 2021

September 2021
Dates: September 27 – December 17
Times: Mondays-Thursdays 8am-5pm
Application Deadline: September 3, 2021

Location: During modified operations due to the pandemic, this bootcamp is currently 100% virtual.

Program

Pre-bootcamp (before the program starts)
Pre-work will be assigned to you before the bootcamp starts. All the resources used in the pre-work are accessible online or will be provided to you. During pre-work, you will set up your system accounts, meet with the Bootcamp Success Manager, prep your software environment, work through multiple tutorials on DataCamp*, and will make other final preparations. Pre-work is mandatory and must be completed prior to orientation, which is generally a few days before bootcamp begins. The sooner you start and the more time you spend on your pre-work, the more prepared you’ll be. We recommend that you give yourself at least a month to complete this work prior to the start of the bootcamp.

*This class is supported by DataCamp, the most intuitive learning platform for data science. Learn R, Python and SQL the way you learn best through a combination of short expert videos and hands-on-the-keyboard exercises. Take over 100+ courses by expert instructors on topics such as importing data, data visualization or machine learning and learn faster through immediate and personalized feedback on every exercise.

Data Science Fundamentals (Weeks 1-4)

• Learn project selection and use case development – critical thinking
• Overview of the Python computer language
• Learn and practice cloud-based processing using Jupyter notebooks
• Learn about data sources and collection methods
• Conduct extensive exploratory data analysis
• Survey of data visualization tools
• Practice using the probability and statistics needed by Data Scientists

Statistical and Machine Learning (Weeks 5-9)

• Learn and practice database queries with SQL
• Clean up dirty data sets (data wrangling)
• Learn and practice regression techniques (linear, logistic, regularized)
• Supervised learning techniques: K-nearest neighbors, decision trees, random forests, and boosting
• Unsupervised learning techniques: Clustering, dimensionality reduction
• Deep learning: Image identification using Convolutional Neural Networks
• Learn performance improvement techniques: regularization, avoiding over-fitting, data augmentation
• Text processing techniques: Natural Language Processing

Capstone Project (Weeks 10-12)

• Immerse yourself in your team capstone project
• Create clean, functional, and documented code for your Github resume
• Demonstrate your team capstone projects to employers, staffing agencies and others in the tech community

Full-time, Immersive Schedule

• Monday – Thursday: 8 a.m. – 5 p.m.
• Friday: 8 a.m. – 3 p.m.

Pre-requisites

• A data scientist has a multidisciplinary blend of skills. It’s much more than knowing how to program or understanding statistics. Knowledge of a business domain is helpful to solve business problems with data science. As such, we recommend at least 2-5 years of relevant business experience area well enough to:
  • Solve significant problems in their area
  • Write papers or blog posts about their work
  • Speak about their work at a conference of their peers
  • Recognize results in a model that are either invalid or trivial (this is the important one for our purposes!)
• Basic knowledge of statistical concepts, probability distributions, and linear algebra will be required. To meet this pre-requisite, we ask that you take our short assessment on linear algebra and probability & statistics.

These resources can help you review for the assessments:
Probability/Statistics: Link
Linear Algebra: Link – Andrew Ng – Lectures 3.1-3.6

• Coding experience will be required. If you do not have coding experience, contact us for resources to help you get up to speed.

Some exceptions to pre-reqs can be made. Apply if you’re interested, and we can discuss

Cost

The total bootcamp tuition is $9,995.

Participants receiving third-party funding may not have to pay a deposit or any tuition. Learn more about financial assistance and the payment process for the bootcamp. *Prices subject to change.

Reserve Your Seat Now: A $1,500 non-refundable deposit is required prior to the application deadline in order to reserve your seat. The remaining course fees must be paid in full by the application deadline.