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SELECT id, date, short_story, xfields, title, category, alt_name FROM dle_post WHERE MATCH (title, short_story, full_story, xfields) AGAINST ('Python For Corporate Finance And Investment Analysis Free Download Python For Corporate Finance And Investment AnalysisPublished 1/2024MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHzLanguage: English | Size: 10.50 GB | Duration: 7h 21mIntroduction to Financial Automation: Empowering Financial Decision-Making Through Python ProgrammingWhat you\'ll learnLearn to manipulate and analyze financial data using PythonUnderstand the Basics of Python ProgrammingGain 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.RequirementsThere are no prerequisites for taking this course as it will go over understanding financial concepts and Python coding concepts.No Prior Programming Experience Required: While prior experience with programming can be beneficial, it is not a prerequisite.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.\"DescriptionFrom Data to Decisions: Python in Corporate FinanceReal-World Python Applications in Corporate FinanceHere are some of the topics we will cover in this course: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.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)Introductory-Level Knowledge of Economics:Basic understanding of macroeconomic and microeconomic principles, as they underpin many financial theories and models.Basic Computer Literacy:Proficiency in using computers, especially for tasks like installing software, managing files, and navigating the internet.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 StrategiesLeveraging Python for Strategic Investment InsightsNavigating Financial Markets with Python SkillsTransformative Skills for the Modern Financial ProfessionalPython for the Future of Finance: Analytics and BeyondThis 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 AnalyticsThis 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.OverviewSection 1: IntroductionLecture 1 IntroductionLecture 2 Python PrimerLecture 3 Introduction to QuizzesLecture 4 Corporate Book downloadLecture 5 Investing Book downloadSection 2: Financial Statements ReviewLecture 6 Financial Statements in 60 MinutesLecture 7 Intro to Understanding Financial StatementsLecture 8 Financial Statements Overview LectureLecture 9 The Income Statement: RevenueLecture 10 The Income Statement: ExpensesLecture 11 The Income Statement: Net IncomeLecture 12 The Balance SheetLecture 13 The Cash Flow StatementLecture 14 Financial Statements Interconnection and FlowSection 3: Financial Statement AnalysisLecture 15 Introduction to Financial Statement Analysis LectureLecture 16 Intro to Financial Statement Ratio AnalysisLecture 17 Financial Ratio AnalysisLecture 18 Liquidity and Solvency RatiosLecture 19 Financial Ratio Analysis ConclusionSection 4: Python Coding Exercises for Financial Statement AnalysisLecture 20 Python Coding PrimerLecture 21 Python Coding for Financial Statement InformationLecture 22 Python coding exercise for calculating Financial RatiosLecture 23 Add Python code to display results.Section 5: IntermissionLecture 24 What we have covered so far, and what\'s next.Lecture 25 Finance is EmpoweringSection 6: The Time Value of MoneyLecture 26 Introduction to the Time Value of MoneyLecture 27 The Time Value of Money TVMLecture 28 Discounting Cash Flows DCF: Present Value and Future ValueSection 7: Python coding exercise for calculating DCFSection 8: The Weighted Average Cost of Capital WACCLecture 29 The Weighted Average Cost of CapitalLecture 30 The Debt SubsidyLecture 31 Modigliani Miller TheoremLecture 32 WACC QuizLecture 33 WACC Quiz Excel SolutionLecture 34 Intro to Python coding exercise to calculate WACCSection 9: Free Cash Flow FCFLecture 35 Free Cash FlowLecture 36 Free Cash Flow Case StudiesSection 10: Net Present Value NPVLecture 37 Introduction to Net Present ValueLecture 38 NPVLecture 39 Net Present Value CalculationLecture 40 Capex vs. OpexLecture 41 NPV ReviewLecture 42 NPV Excel Spreadsheet Quiz AnswersSection 11: Internal Rate of Return IRRLecture 43 IRR calculations and analysisLecture 44 The Limitations of IRRSection 12: RiskLecture 45 How to Define and Measure RiskLecture 46 Exploring Financial Risk with Case StudyLecture 47 Managing RiskLecture 48 Summary: \"Against the Gods: The Remarkable Story of Risk\" by Peter L. BernsteinSection 13: Beta and the Capital Asset Pricing Model CAPMLecture 49 Risk, Return, and DiversificationLecture 50 Understanding Market Volatility: A Deep Dive into Beta and Investment RiskLecture 51 Decoding Market Risk: The Mathematics of Beta Slope CalculationLecture 52 CAPM: the Dynamics of Risk and Return in Financial Markets and Asset PricingLecture 53 Beta and CAPMLecture 54 Maximizing Returns: Mastering the Sharpe Ratio for Optimal Portfolio PerformanceSection 14: Price Earnings Ratio and PEG RatioLecture 55 Price to Earnings Ratio P/ELecture 56 Create a Python Script for P/E RatioLecture 57 Calculate P/E with dataLecture 58 Calculate EPS and P/ELecture 59 PEG RatioLecture 60 P/E and PEG ComparisonLecture 61 PEG QuizLecture 62 PEG Quiz AnswersLecture 63 An example comparing two stock market indexes using P/E and PEG.Section 15: Stock Markets: Stock Price and ValuationLecture 64 Price of Stocks: how stock prices are determinedLecture 65 Stock Valuation: present value of future cash flowsSection 16: Derivatives: Stock OptionsLecture 66 Introduction to Stock OptionsLecture 67 Stock Options: Puts and CallsLecture 68 Options Trading PracticesLecture 69 Black-Scholes Option Pricing ModelLecture 70 Implied VolatilityLecture 71 Option Pricing with Quantum ComputingSection 17: Bonds and Debt FinancingLecture 72 The Bond Market: Unlocking the Secrets of Debt FinancingLecture 73 Bond MathThis 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. 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