Data Science Immersive

full-time 14 Weeks

Mon - Fri, 10:00 am - 5:00 pm

Start: January 13, 2020

End: April 17, 2020

Location: New York

295 Madison Ave., 35 FL

full-time 14 Weeks

Mon - Fri, 10:00 am - 5:00 pm

Start: February 10, 2020

End: May 15, 2020

Location: New York

295 Madison Ave., 35 FL

Our full-time Data Science provides the skillset to become a data scientist or go into a related role such as Data Analyst, Data Engineer and Data Architect after our program.

Curriculum

The Python programming language is emphasized in our course.  We cover topics such as data acquisition, data analysis, Pandas, statistics, visualization, prediction and machine learning, natural language processing, data wrangling, statistical modeling, regression, Hadoop, SQL, NoSQL and more.

Structure

The course consists of four phases:

  • Phase 1: Python and database fundamentals
  • Phase 2: Statistical applications
  • Phase 3: Machine learning and Big Data
  • Phase 4: Two weeks of final project work
Instructor

Rebecca Sealfon, named one of the “Top 50 Female Full Stack Developers In New York City” by RecruitLoop leads the program.  Rebecca was formerly an engineer at Google.

Industry Focus

Students may focus on data science applications in specific industries such as finance or medicine.  This focus comes out in student project work.  All students build a portfolio of projects to showcase to potential employers while they are enrolled.

Career Services

Throughout the program, our career services team works closely with students to help place them at a top company upon graduation. Career coach activities include: resume and LinkedIn profile help, interview prep, mentor matching, skills workshops and more.

Pre-requisites

No prior data science experience is required.  However, all students will be required to go through an admissions process and complete pre-work.  Students who take the introductory Python Foundation workshop maybe exempt from pre-work.

Apply

Applications are accepted on a rolling basis for all programs.  For additional dates, please see  class calendar*

Questions? Schedule a call with admissions.