Data Science Part-Time Program

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

Part-time 2023 Data Science schedule
8 am – 5 pm, Fridays

April 2023
Dates: April 7, 2023 – September 15, 2023 
Application Deadline: Friday, March 17, 2023

January 2024
Dates: January 12, 2024 – June 21, 2024
Application Deadline: December 8, 2023

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 1-8)

• 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 9-16)

• 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 17-24)

• 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

Part-time Schedule

• Fridays 8am – 5pm and 8 hours asynchronous online throughout week. Time outside of class could be more than 8 hours depending on prior experience and project difficulty.

Pre-Requisite Knowledge & Experience

Data science is multidisciplinary, blending math, science, and business skills. It’s much more than statistics or programming alone. Experience in an industry, or business domain, is essential to know what questions to ask and what problems to solve with data. 

There are no pre-requisites for the Data Science bootcamp, however having some prior experience in the following areas would be beneficial. 

1. Having 2-5 years experience in a related field researching and writing papers/blogs, presenting research to peers, or validating data models. 
2. Experience applying statistical concepts, probability distributions, and linear algebra.
3. Coding experience, specifically Python, is preferred and encouraged. 

Useful Resources

Contact our team to access resources to prepare you for the Data Science including resources on probability, statistics, linear algebra, and Python. 

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.