Key Information
Python for Data Science Bootcamp
Python for Finance Bootcamp
Financial Modeling Bootcamp
$1,495 30 Hours
$1,295 18 Hours
$995 18 Hours
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.
Master the major Python financial libraries to gather and manipulate financial data. Use APIs to fetch financial, company, and economic data. Analyze financial statements from the SEC website, including ratios derived from the income statement and balance sheet. Build risk management models and apply linear regression to predict stock prices.
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. 
Open to Beginners
Python / Data: Participants should be familiar with concepts from Python for Data Science Bootcamp, including built-in data types, data structures, Pandas, and Matplotlib. Finance Background: Participants should be familiar with financial concepts such as NPV, IRR, financial statements, and stock fundamentals. Those without a background in finance should contact us after registration to access a free on-demand supplemental guide. 
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.
185 Madison Ave, NYC or Live Online
185 Madison Ave, NYC or Live Online
185 Madison Ave, NYC or Live Online
Next start date: January 9–13, Monday to Friday, 10–5pm
Other scheduling options Weekdays or weeknights
View full schedule
Not currently scheduled
Next start date: January 10–12, Tuesday to Thursday, 10–5pm
Other scheduling options Weekdays only
View full schedule
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
Payment Plan See our payment plan FAQ for more details
Financing See our Leif 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

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
  • Gathering financial information with Python
  • Financial APIs
  • Analyzing 10k from the SEC website
  • Time value of money with Python
  • Risk management with Python
  • Calculating VAR
  • Financial Ratios
  • Fixed income with Python
  • Option strategies with Python
  • Portfolio management with Python
  • Regression analysis
  • 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