Python for Finance: Investment Fundamentals & Data Analytics

What you’ll learnLearn how to code in PythonTake your career to the next levelWork with Python’s conditional statements, functions, sequences, and loopsWork with scientific packages, like NumPyUnderstand how to use the data analysis toolkit, PandasPlot graphs with MatplotlibUse Python to solve real-world tasksGet a job as a data scientist with PythonAcquire solid financial acumenCarry out in-depth investment analysisBuild investment portfoliosCalculate risk and return of individual securitiesCalculate risk and return of investment portfoliosApply best practices when working with financial dataUse univariate and multivariate regression analysisUnderstand the Capital Asset Pricing ModelCompare securities in terms of their Sharpe ratioPerform Monte Carlo simulationsLearn how to price options by applying the Black Scholes formulaBe comfortable applying for a developer job in a financial institutionDo you want to learn how to use Python in a working environment?Are you a young professional interested in a career in Data Science?  Would you like to explore how Python can be applied in the world of Finance and solve portfolio optimization problems?  If so, then this is the right course for you!  We are proud to present Python for Finance: Investment Fundamentals and Data Analytics – one of the most interesting and complete courses we have created so far. It took our team slightly over four months to create this course, but now, it is ready and waiting for you.  An exciting journey from Beginner to Pro.  If you are a complete beginner and you know nothing about coding, don’t worry! We start from the very basics. The first part of the course is ideal for beginners and people who want to brush up on their Python skills. And then, once we have covered the basics, we will be ready to tackle financial calculations and portfolio optimization tasks.   Finance Fundamentals.  And it gets even better! The Finance block of this course will teach you in-demand real-world skills employers are looking for. To be a high-paid programmer, you will have to specialize in a particular area of interest. In this course, we will focus on Finance, covering many tools and techniques used by finance professionals daily:  Rate of return of stocks  Risk of stocks  Rate of return of stock portfolios  Risk of stock portfolios  Correlation between stocks  Covariance  Diversifiable and non-diversifiable risk  Regression analysis  Alpha and Beta coefficients  Measuring a regression’s explanatory power with R^2  Markowitz Efficient frontier calculation  Capital asset pricing model  Sharpe ratio  Multivariate regression analysis  Monte Carlo simulations  Using Monte Carlo in a Corporate Finance context  Derivatives and type of derivatives  Applying the Black Scholes formula  Using Monte Carlo for options pricing  Using Monte Carlo for stock pricingEverything is included! All these topics are first explained in theory and then applied in practice using Python.Is there a better way to reinforce what you have learned in the first part of the course?  This course is great, even if you are an experienced programmer, as we will teach you a great deal about the finance theory and mechanics you will need if you start working in a finance context.     Teaching is our passion.  Everything we teach is explained in the best way possible. Plain and clear English, relevant examples and time-efficient videos. Don’t forget to check some of our sample videos to see how easy they are to understand.   If you have questions, contact us! We enjoy communicating with our students and take pride in responding within the 1 business day. Our goal is to create high-end materials that are fun, exciting, career-enhancing, and rewarding.    What makes this course different from the rest of the Programming and Finance courses out there?  This course will teach you how to code in Python and apply these skills in the world of Finance. It is both a Programming and a Finance course.High-quality production – HD video and animations (this isn’t a collection of boring lectures!)Knowledgeable instructors. Martin is a quant geek fascinated by the world of Data Science, and Ned is a finance practitioner with several years of experience who loves explaining Finance topics in real life and here on Udemy.Complete training – we will cover all the major topics you need to understand to start coding in Python and solving the financial topics introduced in this course (and they are many!)Extensive Case Studies that will help you reinforce everything you’ve learned.Course Challenge: Solve our exercises and make this course an interactive experience.Excellent support: If you don’t understand a concept or you simply want to drop us a line, you’ll receive an answer within 1 business day.Dynamic: We don’t want to waste your time! The instructors set a very good pace throughout the whole course.Please don’t forget that the course comes with Udemy’s 30-day unconditional, money-back-in-full guarantee. And why not give such a guarantee, when we are convinced the course will provide a ton of value for you?Just subscribe to this course! If you don’t acquire these skills now, you will miss an opportunity to separate yourself from the others. Don’t risk your future success! Let’s start learning together now!Who this course is for:Aspiring data scientistsProgramming beginnersPeople interested in finance and investmentsProgrammers who want to specialize in financeEveryone who wants to learn how to code and apply their skills in practiceFinance graduates and professionals who need to better apply their knowledge in PythonCourse content18 sections • 111 lectures • 8h 15m total lengthWelcome! Course IntroductionIntroduction to programming with PythonPython Variables and Data TypesBasic Python SyntaxPython Operators ContinuedConditional StatementsPython FunctionsPython SequencesUsing Iterations in PythonAdvanced Python toolsPART II FINANCE: Calculating and Comparing Rates of Return in PythonPART II Finance: Measuring Investment RiskPART II Finance – Using Regressions for Financial AnalysisPART II Finance – Markowitz Portfolio OptimizationPart II Finance – The Capital Asset Pricing ModelPart II Finance: Multivariate regression analysisPART II Finance – Monte Carlo simulations as a decision-making toolBONUS LECTUREGet Python for Finance: Investment Fundamentals & Data Analytics – Anonymous, Only Price $37Tag: Python for Finance: Investment Fundamentals & Data Analytics  Review. Python for Finance: Investment Fundamentals & Data Analytics  download. Python for Finance: Investment Fundamentals & Data Analytics  discount.