Key Information
Python for Data Science Bootcamp
Python for Finance Bootcamp
Financial Modeling Bootcamp
$1495 30 Hours
$1895 30 Hours
$895 21 Hours
Overview
Pick up Python fundamentals and quickly transition into analyzing real-world datasets. You will learn to how to clean and combine data, as well as generate useful statistics and visualizations. The final sessions will be focused on using linear regression to extrapolate from data and make predictions.
Upskill and take your finance skills to the next level with this Python for Finance class. You'll learn to analyze large amounts of financial data using Python, create visualizations, and start using statistics for predictive modeling. 
Learn essential finance & accounting concepts while building a comprehensive discounted cash flow (DCF) model in Excel. This financial modeling class blends finance, accounting and Excel concepts into an intensive 3-day course. 
Prerequisite
Open to Beginners
Open to Beginners
Prior financial experience is helpful, but not required. Those without a finance or accounting background will receive a short guide prior to the course (request upon registration) to acclimate themselves to terminology. Excel proficiency equivalent to Intermediate Excel for Business is required, including VLOOKUP, Pivot Tables, and IF statements. Our Financial Analyst Training Program includes beginner and intermediate Excel along with this 3-day bootcamp.
Location
185 Madison Ave, NYC or Live Online
185 Madison Ave, NYC or Live Online
185 Madison Ave, NYC or Live Online
Scheduling Options
Weekdays & weeknights
Weekdays & weekends
View schedule at training-nyc.com
Next Start Date
October 12–16, Monday to Friday, 10–5pm
October 10–31, Saturdays, 10–3pm
View schedule at training-nyc.com
Certification
Receive a Certificate of Completion
Receive a Certificate of Completion
Receive a Certificate of Completion
Free Retake Within 1 Year See our class policies for more details
Workbook Included
Discounts See our discounts policies for more details
  • Shorter courses such as this are already affordably priced and are not eligible for discounts.
  • Shorter courses such as this are already affordably priced and are not eligible for discounts.
  • Take 10% off this course if you’ve previously taken any 12+ hour course.
  • Take $100 off this course if you’re an individual paying for yourself (not reimbursed by a company).
Payment Plan See our payment plan FAQ for more details
Target Audience
  • Individuals looking to break into the field of data science with Python
  • People with minimal coding background who want to move into more data-centric work at their current workplace
  • People who work with data in tools like SPSS, STATA, or MATLAB and would like to transition into using Python and SQL.
  • Developers with experience in other arenas, who would like to work in data science
Anyone

Participants with prior knowledge of Excel looking to add fluency in financial and accounting concepts and financial modeling skills, including:

  • Those working in or seeking a position in finance, including investment banking, hedge funds, private equity, real estate, and FP&A
  • College and graduate students looking to supplement academic coursework with practical applications of financial modeling and prepare for technical interviews 
  • Those working in or seeking a position in the finance division of a non-financial company to gain skills in advanced Excel, corporate finance, accounting, and cash flow modeling
What You’ll Learn
  • Foundational programming concepts including loops, functions, and objects
  • Handle different types of data, such as integers, floats, and strings
  • Control the flow of your programs with conditional statements
  • Reuse and simplify code with object-oriented programming
  • Analyze tabular data with Numpy and Pandas
  • Create graphs and visualizations with Matplotlib
  • Make predictions with linear regression, using scikit-learn
  • Foundational programming concepts including loops, functions, and objects
  • Handle different types of data, such as integers, floats, and strings
  • Control the flow of your programs with conditional statements
  • Reuse and simplify code with object-oriented programming
  • Analyze tabular data with Numpy and Pandas
  • Create graphs and visualizations with Matplotlib
  • Make predictions with linear regression, using scikit-learn
  • Financial Concepts, Market Capitalization, & Enterprise Value
  • Financial Accounting including accrual versus cash accounting
  • Discount Cash Flow (DCF) Modeling: Assumptions, Projecting Cash Flows, Sensitivities, Auditing
  • Excel Techniques including Data Validation, CHOOSE, Data Tables, Goal Seek and more
  • Leveraged Buyouts (LBO) Modeling
  • Real Company Analysis
  • Setup the Financial Model and model projections
  • Corporate Valuation and derive a value per share
  • Analyze the Model Output