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Key Information
FinTech Bootcamp
$4,995 114 Hours
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Overview
Get the skills you need for a career in finance technology with the FinTech Bootcamp. Learn Python programming, data science, financial analysis, data visualization, and machine learning to become a Financial Analyst, Data Scientist, or Data Analyst.
Prerequisite
Open to Beginners
Location
185 Madison Ave, NYC or Live Online
Schedule
Next start date: Mar 9–Jul 20, Saturdays
Other scheduling options: Saturdays, weekdays, or evenings
View full schedule
Certification
New York-licensed Certificate Program
1:1 Mentoring Included See all courses that offer 1–on–1 mentoring
Free Retake Within 1 Year See our class policies for more details
Workbook Included
Courses Included (Certificates & packages only)
  • 30 HoursPython for Data Science Bootcamp
  • 18 HoursSQL Bootcamp
  • 6 HoursPython for Automation
  • 30 HoursPython Machine Learning Bootcamp
  • 30 HoursPython Data Visualization & Interactive Dashboards
Payment Plan See our payment plan FAQ for more details
This program is eligible for our “pay-as-you-go” payment plan.
Financing See our Leif FAQ for more details
This program is eligible for 12-month financing through Leif.
Target Audience

The FinTech Bootcamp is for professionals looking to break into the field of financial technology and learn important skills such as Python programming, financial analysis, and machine learning. This program is best suited for:

  • Individuals looking to start a career as a Financial Analyst or Data Scientist
  • Anyone interested in working in FinTech or a related field
  • Finance professionals looking to broaden and advance their skills
What You’ll Learn
  • Methods for analyzing financial data using Python and SQL
  • Different types of data, such as integers, floats, and strings
  • How to analyze tabular data and graph the results
  • How to create visualizations and dashboards with Python
  • How to use Python to analyze a financial statement
  • Financial topics such as WACC, NPV, and IRR
  • How to build predictive models for internal budgeting
  • How to work with data using a graphical user interface
  • How to search through tables programmatically
  • Advanced querying techniques like subqueries and timestamp functions

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