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FinTech Bootcamp
$4,995 114 Hours
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Overview
At the end of the certificate, students will feel comfortable trading in Excel spreadsheets for Jupyter notebook. Students will leave this course having worked on multiple projects using Python to pull, clean, analyze, and visualize financial data from all different sources. Additionally, students will learn how to use machine learning to build predictive financial models and export them into PDF or Excel. Lastly, students will gain an understanding of how to organize and find data in SQL.
Prerequisite
Open to Beginners
Location
185 Madison Avenue, NYC or Live Online
Schedule
View schedule at nobledesktop.com
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
  • 30 HoursPython Machine Learning Bootcamp
  • 18 HoursPostgreSQL Bootcamp
  • 6 HoursPython for Automation
  • 18 HoursPython for Finance Bootcamp
Financing See our Leif FAQ for more details
This program is eligible for 12-month financing through Leif.
Target Audience
Anyone
What You’ll Learn
  • Python: Handling different types of data, such as integers, floats, and strings
  • Python: Analyze tabular data with Numpy and Pandas and graph the results using Matplotlib
  • Python: Learn how to pull data from multiple sources 
  • Machine Learning: Learn how to analyze a financial statement using Python 
  • Machine Learning: Learn financial topics such as WACC, NPV, IRR
  • Machine Learning: Learn how to build predictive models for internal budgeting
  • SQL: Explore and alter data using a graphical user interface
  • SQL: Write queries to search through tables programmatically
  • SQL: Understand different data types and converting between them
  • SQL: Combine information across tables with join statements
  • SQL: Advanced techniques like subqueries and timestamp functions

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