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Python for Corporate Finance and Investment Analysis

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John Cousins

6:36:32

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  • 1 - Introduction.html
  • 2 - MBA-ASAP-Python-Primer.pdf
  • 2 - Python Primer.html
  • 3 - Introduction to Quizzes.mp4
    01:00
  • 4 - Corporate Book download.html
  • 4 - Corporate-Finance-ASAP-Print.pdf
  • 5 - Intelligent-Investing-Print.pdf
  • 5 - Investing Book download.html
  • 6 - Financial Statements in 60 Minutes.mp4
    01:40
  • 6 - Reading-and-Understanding-Financial-Statements-Print.pdf
  • 6 - reading-and-understanding-financial-statements-kindle.zip
  • 7 - Intro to Understanding Financial Statements.mp4
    01:03
  • 7 - infographic-financial-statements.zip
  • 8 - Financial Statements Overview Lecture.mp4
    12:10
  • 8 - wb-financial-statements-1.zip
  • 8 - wb-financial-statements-2.zip
  • 9 - The Income Statement Revenue.mp4
    06:30
  • 9 - income-statement-revenue.zip
  • 10 - The Income Statement Expenses.mp4
    11:45
  • 10 - income-statement-expenses.zip
  • 11 - The Income Statement Net Income.mp4
    05:54
  • 11 - income-statement-net-income.zip
  • 12 - The Balance Sheet.mp4
    15:10
  • 12 - balance-sheet.zip
  • 13 - The Cash Flow Statement.mp4
    10:05
  • 13 - cash-flow-statement.zip
  • 14 - Financial Statements Interconnection and Flow.mp4
    11:31
  • 14 - financial-statements-interconnection-and-flow.zip
  • 15 - Introduction to Financial Statement Analysis Lecture.mp4
    05:02
  • 15 - ratio-analysis.zip
  • 16 - Financial-Statement-Glossary-of-Terms.pdf
  • 16 - Intro to Financial Statement Ratio Analysis.mp4
    02:53
  • 16 - MBA-ASAP-Understanding-Financial-Statements.pdf
  • 17 - Financial Ratio Analysis.mp4
    03:40
  • 17 - MBA-ASAP-Financial-Statement-Analysis.pdf
  • 18 - Financial-Statements-for-ratio-calculation.xlsx
  • 18 - Liquidity and Solvency Ratios.mp4
    12:47
  • 19 - Financial Ratio Analysis Conclusion.mp4
    01:09
  • 20 - MBA-ASAP-Python-Primer.pdf
  • 20 - Python Coding Primer.html
  • 21 - Python Coding for Financial Statement Information.mp4
    02:33
  • 22 - Python coding exercise for calculating Financial Ratios.mp4
    03:50
  • 23 - Add Python code to display results.mp4
    05:50
  • 24 - What we have covered so far and whats next.mp4
    01:10
  • 24 - fs-and-tvm-whiteboard.zip
  • 25 - Finance is Empowering.mp4
    02:01
  • 26 - Introduction to the Time Value of Money.mp4
    04:13
  • 27 - The Time Value of Money TVM.mp4
    03:38
  • 28 - Discounting Cash Flows DCF Present Value and Future Value.mp4
    06:40
  • 29 - The Weighted Average Cost of Capital.mp4
    07:51
  • 29 - wacc-whiteboard.zip
  • 30 - The Debt Subsidy.html
  • 31 - Modigliani Miller Theorem.html
  • 32 - WACC Quiz.mp4
    01:39
  • 33 - WACC Quiz Excel Solution.mp4
    05:51
  • 33 - WACC-Quiz-Solution-Spreadsheet.xlsx
  • 34 - Intro to Python coding exercise to calculate WACC.mp4
    04:13
  • 35 - Free Cash Flow.mp4
    16:21
  • 36 - Free Cash Flow Case Studies.html
  • 37 - Introduction to Net Present Value.mp4
    05:27
  • 38 - NPV.mp4
    04:47
  • 39 - Net Present Value Calculation.mp4
    06:16
  • 39 - mba-lite-financial-projection-template.xlsx
  • 40 - Capex vs Opex.mp4
    02:32
  • 41 - NPV Review.mp4
    18:02
  • 42 - NPV Excel Spreadsheet Quiz Answers.mp4
    15:53
  • 43 - IRR calculations and analysis.mp4
    09:42
  • 43 - MBA-ASAP-IRR-PDF.pdf
  • 44 - IRR-Caveats-PDF.pdf
  • 44 - The Limitations of IRR.html
  • 45 - How to Define and Measure Risk.mp4
    10:18
  • 45 - risk.zip
  • 45 - risk-premiums.zip
  • 46 - Exploring Financial Risk with Case Study.html
  • 47 - Managing Risk.mp4
    08:15
  • 47 - insurance-white-board.zip
  • 48 - Summary Against the Gods The Remarkable Story of Risk by Peter L Bernstein.html
  • 49 - Risk Return and Diversification.mp4
    14:17
  • 50 - Understanding Market Volatility A Deep Dive into Beta and Investment Risk.mp4
    07:09
  • 50 - beta-whiteboard.zip
  • 51 - Decoding Market Risk The Mathematics of Beta Slope Calculation.mp4
    07:22
  • 51 - beta-slope-whiteboard.zip
  • 52 - CAPM the Dynamics of Risk and Return in Financial Markets and Asset Pricing.mp4
    08:54
  • 53 - Beta and CAPM.html
  • 54 - Maximizing Returns Mastering the Sharpe Ratio for Optimal Portfolio Performance.mp4
    14:03
  • 54 - sharpe-ratio.zip
  • 55 - Price to Earnings Ratio PE.mp4
    11:24
  • 55 - price-earnings-ratio-whiteboard.zip
  • 56 - Create a Python Script for PE Ratio.mp4
    03:42
  • 57 - Calculate PE with data.mp4
    02:48
  • 58 - Calculate EPS and PE.mp4
    03:06
  • 59 - 1-whiteboard-peg.zip
  • 59 - PEG Ratio.mp4
    10:37
  • 60 - 2-peg-pe-compare.zip
  • 60 - PE and PEG Comparison.mp4
    08:41
  • 61 - 3-peg-ratio-quiz-whiteboard.zip
  • 61 - PEG Quiz.mp4
    01:41
  • 62 - 4-peg-quiz-answers.zip
  • 62 - PEG Quiz Answers.mp4
    03:50
  • 62 - PEG-Calculations.xlsx
  • 63 - An example comparing two stock market indexes using PE and PEG.html
  • 64 - Price of Stocks how stock prices are determined.mp4
    06:40
  • 65 - Stock Valuation present value of future cash flows.mp4
    03:56
  • 66 - Introduction to Stock Options.mp4
    02:48
  • 66 - stock-options-1.zip
  • 67 - Stock Options Puts and Calls.mp4
    17:52
  • 67 - puts-and-calls.zip
  • 68 - Options Trading Practices.html
  • 69 - BlackScholes Option Pricing Model.mp4
    11:25
  • 69 - black-scholes-option-pricing-model.zip
  • 70 - Implied Volatility.mp4
    06:56
  • 70 - implied-volatility.zip
  • 71 - Option Pricing with Quantum Computing.html
  • 71 - Option-Pricing-with-Quantum-Computers.pdf
  • 72 - The Bond Market Unlocking the Secrets of Debt Financing.html
  • 73 - Bond Math.html
  • Description


    Introduction to Financial Automation: Empowering Financial Decision-Making Through Python Programming

    What You'll Learn?


    • Learn to manipulate and analyze financial data using Python
    • Understand the Basics of Python Programming
    • Gain a foundational understanding of Python programming, including data types, control structures, functions, and libraries essential for financial analysis.
    • Acquire the ability to construct financial models and forecasts using Python, including cash flow analysis, budgeting, and financial statement analysis.
    • Acquire the ability to construct financial models and forecasts using Python, including cash flow analysis, budgeting, and financial statement analysis.
    • Applying the Black-Scholes model, bond yield calculation for options pricing.
    • Programming with Python Write effective Python code for solving complex business problems.

    Who is this for?


  • This course, "Python for Corporate Finance and Investment Analysis," is tailored for a diverse range of participants who share an interest in integrating Python programming skills with financial analysis and investment strategies. The target audience includes:
  • Finance Professionals: Individuals working in corporate finance, investment banking, portfolio management, risk management, and financial planning who want to enhance their analytical skills and embrace automation and data-driven decision-making in their workflows.
  • Business Analysts and Consultants: Professionals in business analysis and consulting roles who seek to deepen their analytical capabilities and provide more sophisticated insights into financial performance, market trends, and investment opportunities.
  • Students and Academics in Finance and Economics: University students and academic researchers in finance, economics, business administration, and related fields who aim to supplement their theoretical knowledge with practical, hands-on experience in Python for data analysis and financial modeling.
  • Investment Enthusiasts and Individual Traders: Individuals managing their investments or interested in stock market trading, who want to learn how to use Python for investment analysis, portfolio optimization, and developing algorithmic trading strategies.
  • Career Changers and Lifelong Learners: Professionals from non-finance backgrounds aspiring to transition into finance or investment roles, or those who are interested in personal development and acquiring new, marketable skills at the intersection of finance and technology.
  • Technology Professionals Seeking Finance Domain Knowledge: IT and tech professionals, including software developers, who are looking to diversify their skillset by gaining knowledge in financial analysis and investment strategies.
  • This course is designed to be accessible to those new to programming while still being challenging enough for those with some experience in Python. It offers a unique blend of financial theory and practical application, making it suitable for anyone looking to enhance their skill set at the nexus of finance and technology.
  • What You Need to Know?


  • This course doesn't go through basic programming and Python. It does go through basic Finance and then we crush some basic code.
  • There are no financial prerequisites for taking this course as it will go over understanding financial concepts and Python coding concepts.
  • Prior Programming Experience Required: While prior experience with programming is beneficial, it is not a prerequisite, but you should be familiar with programming concepts and Python syntax,
  • Willingness to Learn and Experiment: An open mindset and willingness to engage with both the programming and financial aspects of the course, including a readiness to solve problems and work on projects.
  • Our slogan is, if you’re reasonably good at math, have a basic understanding of programming, you love it, and you have time to devote to it, then this course is completely fine for you.” “It’s fun,” she says. “It’s just like any other course. You know, we watch the lecture, and then do the quiz, and then we do the problem set.”
  • More details


    Description

    From Data to Decisions: Python in Corporate Finance

    Real-World Python Applications in Corporate Finance


    Programming with Python

    Write effective Python code for solving complex business problems


    When it comes to programming languages, Python shines brightest when dealing with tasks related to data processing, machine learning, and web development. Python has all the necessary tools to help you succeed.


    With a foundation in finance laid down, you will acquire the skills needed to develop various financial applications using Python.


    Here are some of the topics we will cover in this course:


    1. Basic Understanding of Finance and Accounting Principles:

      • Familiarity with fundamental concepts of corporate finance, such as cash flows, financial statements (income statement, balance sheet, cash flow statement), and basic financial metrics (ROI, ROE, etc.).

      • Basic knowledge of investment principles, including stocks, bonds, and other financial instruments.

    2. Foundational Mathematical Skills:

      • Gain comfort with basic mathematics, including algebra and elementary statistics. Understanding of financial mathematics concepts like compounding, discounting, and basic statistical measures (mean, median, standard deviation)

    3. Introductory-Level Knowledge of Economics:

      • Basic understanding of macroeconomic and microeconomic principles, as they underpin many financial theories and models.

    4. Basic Computer Literacy:

      • Proficiency in using computers, especially for tasks like installing software, managing files, and navigating the internet.

    5. No Prior Programming Experience Required:

      • While prior experience with programming can be beneficial, it is not a prerequisite. The course is designed to start with the basics of Python programming.

    This course builds a solid foundation upon which to build your understanding of using Python in corporate finance and investment analysis. The course focuses on bridging the gap between finance and Python programming.


    • Harnessing Python for Effective Investment Strategies

    • Leveraging Python for Strategic Investment Insights

    • Navigating Financial Markets with Python Skills

    • Transformative Skills for the Modern Financial Professional

    • Python for the Future of Finance: Analytics and Beyond


    This course includes many coding exercises in Python.  These exercises will help turbo charge your career.


    Integrating Python coding exercises into finance education offers several significant benefits for students. These benefits stem from the increasing role of technology and data analysis in the finance sector. Here are some key reasons why Python coding exercises are beneficial for finance students:


    1. Enhanced Data Analysis Skills:

    o Python is widely used for data analysis and data science. Finance students can leverage Python to analyze complex financial datasets, perform statistical analysis, and visualize data, skills that are highly valuable in today's data-driven finance industry.

    2. Automation of Financial Tasks:

    o Python can automate many routine tasks in finance, such as calculating financial ratios, risk assessments, and portfolio management. By learning Python, students can understand how to streamline these processes, improving efficiency and accuracy.

    3. Integration with Advanced Financial Models:

    o Python is versatile and can be used to develop sophisticated financial models for risk management, pricing derivatives, asset management, and more. Understanding these models is crucial for modern finance professionals.

    4. Machine Learning and Predictive Analytics:

    o Python is a leading language in machine learning and AI. Finance students can learn to apply machine learning techniques for predictive analytics in stock market trends, credit scoring, fraud detection, and customer behavior analysis.

    5. Access to a Wide Range of Libraries:

    o Python offers a vast array of libraries and tools specifically designed for finance and economics, such as NumPy, pandas, matplotlib, scikit-learn, and QuantLib. Familiarity with these libraries expands a student’s toolkit for financial analysis.

    6. Preparation for Industry Demands:

    o The finance industry increasingly values tech-savvy professionals. Familiarity with Python and coding in general prepares students for the current demands of the finance sector and enhances their employability.

    7. Understanding of Algorithmic Trading:

    o Python is extensively used in algorithmic trading. Finance students can learn to code trading algorithms, understand backtesting, and gain insights into the technological aspects of trading strategies.

    8. Improved Problem-Solving Skills:

    o Coding in Python fosters logical thinking and problem-solving skills. These skills are transferable and beneficial in various areas of finance, from analyzing financial markets to strategic planning.

    9. Broad Applicability:

    o Python is not just limited to one area of finance but is applicable across various domains, including investment banking, corporate finance, risk management, and personal finance.

    10. Collaboration and Innovation:

    o By learning Python, finance students can more effectively collaborate with IT departments and data scientists, bridging the gap between financial theory and applied technology, leading to innovative solutions in finance.

    Incorporating Python into finance education equips students with a practical skill set that complements their theoretical knowledge, making them well-rounded professionals ready to tackle modern financial challenges.


    Python: Your Gateway to Advanced Finance Analytics


    This course, "Python for Corporate Finance and Investment Analysis," is tailored for a diverse range of participants who share an interest in integrating Python programming skills with financial analysis and investment strategies. The target audience includes:

    1. Finance Professionals:

      • Individuals working in corporate finance, investment banking, portfolio management, risk management, and financial planning who want to enhance their analytical skills and embrace automation and data-driven decision-making in their workflows.

    2. Business Analysts and Consultants:

      • Professionals in business analysis and consulting roles who seek to deepen their analytical capabilities and provide more sophisticated insights into financial performance, market trends, and investment opportunities.

    3. Students and Academics in Finance and Economics:

      • University students and academic researchers in finance, economics, business administration, and related fields who aim to supplement their theoretical knowledge with practical, hands-on experience in Python for data analysis and financial modeling.

    4. Investment Enthusiasts and Individual Traders:

      • Individuals managing their investments or interested in stock market trading, who want to learn how to use Python for investment analysis, portfolio optimization, and developing algorithmic trading strategies.

    5. Career Changers and Lifelong Learners:

      • Professionals from non-finance backgrounds aspiring to transition into finance or investment roles, or those who are interested in personal development and acquiring new, marketable skills at the intersection of finance and technology.

    6. Technology Professionals Seeking Finance Domain Knowledge:

      • IT and tech professionals, including software developers, who are looking to diversify their skillset by gaining knowledge in financial analysis and investment strategies.

    This course is designed to be accessible to those new to programming while still being challenging enough for those with some experience in Python. It offers a unique blend of financial theory and practical application, making it suitable for anyone looking to enhance their skill set at the nexus of finance and technology.


    Why Python?


    Python is a good starting point for first-time coders. It uses simple, natural language syntax, almost like spoken English. It is powerful and it is versatile, favored by such diverse industry giants as Netflix, PayPal, NASA, Disney, and Dropbox. Python is used by 87% of data scientists.


    User-Friendly Syntax: As an interpreted language, Python has simpler, more concise syntax than Java. Python's simple, concise syntax makes it easy to write algorithms with just a few lines of code

    Open-Source Libraries: Pre-written code is readily available, with algorithms at your disposal, so you do not have to start every project from scratch. You can benefit from highly specific libraries – physics, web development, gaming, machine learning – by simply importing algorithms and applying them to your own data. It is plug and play at its best, with new functionalities being added all the time

    Community Exchanges: Python’s popularity means it has great community support, with almost 8 million Python developers across the world to help you debug or resolve a programming challenge

    Compatibility: Python is a cross-platform language and can be integrated easily with Windows and other platforms

    Adaptability: Almost every field is adopting Python and needs both generalists and specialists who know how to use it. Fields as varied as gaming, web development, healthcare, and fintech prefer Python over other programming languages, making it the must-learn language for STEM professionals and data scientists

    Who this course is for:

    • This course, "Python for Corporate Finance and Investment Analysis," is tailored for a diverse range of participants who share an interest in integrating Python programming skills with financial analysis and investment strategies. The target audience includes:
    • Finance Professionals: Individuals working in corporate finance, investment banking, portfolio management, risk management, and financial planning who want to enhance their analytical skills and embrace automation and data-driven decision-making in their workflows.
    • Business Analysts and Consultants: Professionals in business analysis and consulting roles who seek to deepen their analytical capabilities and provide more sophisticated insights into financial performance, market trends, and investment opportunities.
    • Students and Academics in Finance and Economics: University students and academic researchers in finance, economics, business administration, and related fields who aim to supplement their theoretical knowledge with practical, hands-on experience in Python for data analysis and financial modeling.
    • Investment Enthusiasts and Individual Traders: Individuals managing their investments or interested in stock market trading, who want to learn how to use Python for investment analysis, portfolio optimization, and developing algorithmic trading strategies.
    • Career Changers and Lifelong Learners: Professionals from non-finance backgrounds aspiring to transition into finance or investment roles, or those who are interested in personal development and acquiring new, marketable skills at the intersection of finance and technology.
    • Technology Professionals Seeking Finance Domain Knowledge: IT and tech professionals, including software developers, who are looking to diversify their skillset by gaining knowledge in financial analysis and investment strategies.
    • This course is designed to be accessible to those new to programming while still being challenging enough for those with some experience in Python. It offers a unique blend of financial theory and practical application, making it suitable for anyone looking to enhance their skill set at the nexus of finance and technology.

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    John Cousins
    John Cousins
    Instructor's Courses
    I am the author of Patent It Yourself!, Negotiation Communication Nation, Learn Accounting Fast!, Managing and Leading Organizations and People, Reading and Understanding Financial Statements, MBA ASAP, and nine other books. I am the founder of MBA ASAP which can be found at MBA-ASAP dot com an "online business education community" chock full of business skills and knowledge on the web.   Previously, I was CEO of a biotech company developing innovative cancer diagnostics. I took two companies public and I was the CFO of several public companies for 15 years. For the past decade I have also been teaching business classes at a number of universities and colleges.   Writing these books and creating these courses has been a wonderful opportunity to gather and organize my thoughts and experiences and share them. I have an electronics degree from MIT, a BA from Boston University and an MBA from Wharton.
    Students take courses primarily to improve job-related skills.Some courses generate credit toward technical certification. Udemy has made a special effort to attract corporate trainers seeking to create coursework for employees of their company.
    • language english
    • Training sessions 56
    • duration 6:36:32
    • Release Date 2024/04/23