What Does MVP Stand For? It’s Not What You Think.
October 7, 2024
Article
Instructor: Packt - Course Instructors
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Recommended experience
Intermediate level
This is for finance professionals & data analysts with a math foundation. Basic finance concepts are beneficial; no prior programming is required.
Recommended experience
Intermediate level
This is for finance professionals & data analysts with a math foundation. Basic finance concepts are beneficial; no prior programming is required.
Identify Python syntax and data types relevant to financial analysis.
Explain key finance concepts such as portfolio optimization and risk measurement.
Use Python to calculate investment returns and risks.
Perform regression analysis to evaluate financial data and trends.
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October 2024
7 assignments
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Step into the world of finance with Python as your primary tool. This course starts with a thorough introduction to Python, covering essential programming concepts like variables, loops, and functions. You’ll become proficient in handling data types, creating iterations, and applying Python’s syntax to real-world problems. With hands-on experience in Jupyter notebooks, you’ll quickly grasp the fundamentals needed for financial applications.
The second phase dives deep into financial analysis, leveraging Python to calculate returns, measure risk, and run complex models like Markowitz portfolio optimization. You’ll learn how to use regression analysis to interpret market trends and make data-backed investment decisions. By integrating Python's advanced tools, you can analyze large datasets with precision, allowing for more accurate forecasts and financial assessments. As the course progresses, you’ll explore sophisticated techniques like the Capital Asset Pricing Model (CAPM) and Monte Carlo simulations. These powerful tools will equip you to evaluate investment opportunities and optimize decision-making. By the end, you’ll not only understand finance but also be able to programmatically implement financial strategies using Python. This course is designed for finance professionals, data analysts, and students with a foundational understanding of mathematics. Familiarity with basic finance concepts is recommended, but no prior programming experience is required.
In this module, we will introduce the course, outlining the main objectives and topics that will be covered. We’ll also introduce the instructors and explain who this course is designed for, providing a comprehensive overview of what to expect throughout the lessons.
1 video1 reading
In this module, we will delve into the fundamentals of Python programming and the Jupyter Notebook environment. You’ll learn how to set up the necessary tools, explore Python’s features, and become familiar with the Jupyter interface, ensuring a solid foundation for the course.
12 videos
In this module, we will introduce the core data types in Python, including variables, numbers, Booleans, and strings. You will learn how to store and manipulate different types of data, forming the basis for more advanced programming tasks.
3 videos1 assignment
In this module, we will cover Python’s essential syntax elements, including operators, commenting, and the importance of indentation. You’ll learn techniques to enhance code readability and functionality, preparing you for more complex coding challenges.
7 videos
In this module, we will dive deeper into Python operators, focusing on comparison, logical, and identity operators. You will enhance your ability to create expressions that drive decision-making in your code.
2 videos
In this module, we will explore conditional statements, such as IF, ELSE, and ELIF. You’ll learn how to build logic-driven code that can handle different scenarios and outcomes based on conditions.
4 videos1 assignment
In this module, we will focus on Python functions—how to define them, use parameters, and combine them with other tools. You’ll also explore some of Python’s built-in functions to streamline your programming.
7 videos
In this module, we will cover Python’s sequence types, including lists, tuples, and dictionaries. You’ll learn how to store, slice, and manage data effectively within these structures.
5 videos
In this module, we will introduce Python’s looping mechanisms, focusing on for-loops, while-loops, and the range() function. You’ll also learn to integrate loops with conditional logic and functions for powerful automation.
6 videos1 assignment
In this module, we will introduce advanced Python tools, including OOP concepts, modules, and data manipulation techniques. You’ll learn how to work with external packages and handle complex data operations in finance.
14 videos
In this module, we will explore the foundational concepts of calculating and comparing rates of return. You’ll learn how to apply these concepts in Python to compute the returns of individual securities, portfolios, and stock indices, providing key insights into risk and performance.
10 videos
In this module, we will dive into risk measurement in finance. You’ll learn how to quantify the risk of securities and portfolios, calculate covariance and correlation, and use Python tools to analyze the risks associated with investment decisions.
10 videos1 assignment
In this module, we will cover regression analysis and its application in finance. You will learn how to run regressions in Python, interpret the results, and use key indicators such as Alpha and Beta to assess financial performance.
4 videos
In this module, we will introduce Markowitz Portfolio Optimization, focusing on building efficient portfolios. You’ll learn to calculate the efficient frontier in Python and optimize asset allocation to achieve the best balance between risk and return.
4 videos
In this module, we will examine the Capital Asset Pricing Model (CAPM), its calculation, and its significance in finance. You’ll use Python to calculate Beta, expected returns, and performance metrics like the Sharpe Ratio and Alpha to evaluate investments.
8 videos1 assignment
In this module, we will focus on multivariate regression analysis, applying it in the context of finance. You’ll learn to run multivariate regressions in Python and analyze the relationships between multiple variables affecting asset performance.
2 videos
In this module, we will delve into Monte Carlo simulations and their powerful applications in finance. You’ll use Python to simulate future profits, forecast stock prices, and apply the Black Scholes formula, enhancing your ability to make informed investment decisions.
13 videos2 assignments
Packt helps tech professionals put software to work by distilling and sharing the working knowledge of their peers. Packt is an established global technical learning content provider, founded in Birmingham, UK, with over twenty years of experience delivering premium, rich content from groundbreaking authors on a wide range of emerging and popular technologies.
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Yes, you can preview the first video and view the syllabus before you enroll. You must purchase the course to access content not included in the preview.
If you decide to enroll in the course before the session start date, you will have access to all of the lecture videos and readings for the course. You’ll be able to submit assignments once the session starts.
Once you enroll and your session begins, you will have access to all videos and other resources, including reading items and the course discussion forum. You’ll be able to view and submit practice assessments, and complete required graded assignments to earn a grade and a Course Certificate.
If you complete the course successfully, your electronic Course Certificate will be added to your Accomplishments page - from there, you can print your Course Certificate or add it to your LinkedIn profile.
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You will be eligible for a full refund until two weeks after your payment date, or (for courses that have just launched) until two weeks after the first session of the course begins, whichever is later. You cannot receive a refund once you’ve earned a Course Certificate, even if you complete the course within the two-week refund period. See our full refund policy.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
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