Complete 2-in-1 Python for Business and Finance Bootcamp

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Complete 2-in-1 Python for Business and Finance Bootcamp paid course free. You will Learn Data Science, Statistics, Hypothesis Tests, Regression, Simulations for Business & Finance: Python Coding AND Theory A-Z

  • Learn Python coding from Zero in a Business, Finance & Data Science context (real Examples)
  • Learn Business & Finance (Time Value of Money, Capital Budgeting, Risk, Return & Correlation)
  • Learn Statistics (descriptive & inferential, Probability Distributions, Confidence Intervals, Hypothesis Testing)
  • Learn how to use the Bootstrapping method to perform hands-on statistical analyses and simulations
  • Learn Regression (Covariance & Correlation, Linear Regression, Multiple Regression, ANOVA)
  • Learn how to use all relevant and powerful Python Data Science Packages and Libraries
  • Learn how to use Numpy and Scipy for numerical, financial and scientific computing
  • Learn how to use Pandas to process Tabular (Financial) Data – cleaning, merging, manipulating
  • Learn how to use stats (scipy) for Statistics and Hypothesis Testing
  • Learn how to use statsmodels for Regression Analysis and ANOVA
  • Learn how to create meaningful Visualizations and Plots with Matplotlib and Seaborn
  • Learn how to create user-defined functions for Business & Finance applications
  • Learn how to solve and code real Projects in Business, Finance & Statistics
  • Learn how to unleash the full power of Python and Numpy with Monte Carlo Simulations
  • Understand and code Sharpe Ratio, Alpha, Beta, IRR, NPV, Yield-to-Maturity (YTM)
  • Learn how to code more advanced Finance concepts: Value-at-Risk, Portfolios and (Multi-) Factor Models
  • Understand the difference between the Normal Distribution and Student´s t-distributions: what to use when

Complete 2-in-1 Python for Business and Finance Bootcamp Course Requirements

  • No (Python) Coding required. This Course starts from complete zero und teaches you everything from scratch.
  • No specific Business/Finance, Statistics & Data Science knowledge needed! The course intuitively explains basic and advanced concepts.
  • A desktop computer (Windows, Mac, or Linux) capable of storing and running Anaconda. The course will walk you through installing the necessary free software.
  • An internet connection capable of streaming videos.
  • Some high school level math skills would be great (not mandatory, but it helps)

Complete 2-in-1 Python for Business and Finance Bootcamp Course Description

######### UPDATE (November 2020) ###########

  • Updated to latest Versions
  • Added: Object-Oriented Programming (OOP) for complete Beginners: with real-world examples and in a way that everyone understands OOP!

Hello and welcome to this Course!

This is the primary ever far reaching Python Course for Business and Finance Professionals. You will take in and ace Python from Zero and the full Python Data Science Stack with genuine Examples and Projects taken from the Business and Finance world.

This isn’t only a coding course. You will comprehend and dominate all necessary hypothetical ideas driving the tasks and the code without any preparation.

Significant: the quality Benchmark for the hypothesis part is the CFA (Chartered Financial Analyst) Curriculum. The Instructor of this course holds a Master’s Degree in Finance and breezed through each of the three CFA Exams. In this course, we leave positively no space for wrong/questionable (however as often as possible advanced) rehearses like LSTM stock value forecasts or utilizing stock costs in straight relapses.

You will end up being a specialist in Python Coding as well as in

Business and Finance (Time Value of Money, Capital Budgeting, Risk, Return and Correlation, Monte Carlo Simulations, Quality and Risk Management in Production and Finance, Mortgage Loans, Annuities and Retirement Planning, Portfolio Theory, Portfolio Optimization, Asset Pricing and Factor Models, Value-at-Risk)

Insights (clear and inferential measurements, Confidence Intervals, Hypothesis Testing, Normal Distribution and Student’s t-conveyance, p-esteem, Bootstrapping Method, Monte Carlo Simulations, Normality of Returns)

Relapse (Covariance and Correlation, Linear Regression, Multiple Regression and its traps, Hypothesis Testing of Regression Coefficients, Logistic Regression, ANOVA, Dummy Variables, Links to Machine Learning, Fama-French Factor Models)

This course follows a commonly building up idea: Learning Python and Theory all the while:

Learning Python is more viable while having the right setting and the right models (keep away from toy models!).

Learning and dominating fundamental hypotheses and ideas in Business, Finance, Statistics and Regression is way simpler and more viable with Python as you can reenact, envision and progressively clarify the instinct behind speculations, math and recipes.

This course covers inside and out all significant and ordinarily utilized Python Data Science Packages:

Python from the very Basics (Standard Library)

Numpy and Scipy for Numeric, Scientific, Financial, Statistical Coding and Simulations

Pandas to deal with, measure, spotless, total and control Tabular (Financial) Data. You merit something other than Excel!

statsmodels to perform Regression Analysis, Hypothesis Testing and ANOVA

Matplotlib and Seaborn for logical Data Visualization

This course isn’t simply recordings:

Downloadable Jupyter Notebooks with a huge number of lines of code

Downloadable PDF Files containing many slides clarifying and rehashing the main ideas

Downloadable Jupyter Notebook with many coding practices incl. clues and arrangements

I rigorously adhere to one straightforward principle in my coding courses: No code without clarifying the WHY. You will not hear remarks like “…that’s the Python code, go ahead and google for more foundation data and sort it out yourself”. Your chief, your customers, your colleagues and your schools don’t acknowledge that. For what reason would it be advisable for you to at any point acknowledge this in a course that forms your profession? Indeed, even the best (coding) results have possibly little worth in the event that they can’t be disclosed and offered to other people.

I’m Alexander Hagmann, Finance Professional and smash hit Instructor for (Financial) Data Science, Finance with Python and Algorithmic Trading. Understudies who finished my courses work in the biggest and most well known tech and money organizations from one side of the planet to the other. From my own insight and having instructed a large number of experts and organizations on the web and face to face, there is one key discovering: Professionals normally start with some unacceptable pieces of the Python Ecosystem, in some unacceptable setting, with some unacceptable tone and for some unacceptable vocation way.

Do it right the first run through and save time and nerves! What are you hanging tight for? There is no danger for you as you have a 30 Days Money Back Guarantee.

Thanks and looking forward to seeing you in the Course!

Who this course is for:

  • All Business and Finance Professionals (Python is the future)
  • Python Developers / Computer Scientists who want to step into Business, Finance & Data Science Roles
  • Researchers who need to analyze large data sets and perform statistical & regression analysis
  • Everyone who want to complement/replace Excel at work to increase productivity
  • Everyone who want to get the full picture: Coding and underlying Theory (Statistics, Regression, Finance)

Source: https://www.udemy.com/course/complete-python-for-business-and-finance-bootcamp/

Complete 2-in-1 Python for Business and Finance Bootcamp

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