Python for Finance – Financial Analysis

Why do you need to take this Python for Finance Course? The Finance and Investment Industry is experiencing rapid change due to the rapid advancement of processing power, connectivity, and machine learning tools. Not only this, Finance and Investment are increasingly becoming a data-driven business, shifting from a math/formula-based business.

How can you keep up?
You need to leave Excel behind to manage your Financial Data. Python and Pandas offer the opportunity for deep dives into Machine Learning, as well as becoming more efficient at work when you are dealing with Financial Data.
Learning Pandas from scratch is nearly as easy as learning Excel. Pandas is like Excel for Python. Due to its many features, Pandas appears to be more complicated than other tools. As you practice, you will become familiar with pandas and will be able to use them for managing financial data, for meeting the same goal Jobaaj Learnings introduced Advanced Python for Finance Course.

Significant Highlights of The Course

• Deep Dive in Pandas, Financial Data, and Financial Concepts
• Online video lectures
• Quizzes for Practice
• Taught by qualified Python professional
• Projects at the end of the course

Why learn Pandas?

The workflows you usually carry out with Excel can be more efficiently done with Pandas. There may be dozens of lines of coding running automatically behind the scenes of Pandas, which is a high-level coding library. Pandas operations are typically wiped out in one line of code! However, you must learn and master Pandas in an order that enables you to understand more about what’s going on and realize the pitfalls (Don’ts) and remain compliant (DOs). Python/Panda coding is one of the most in-demand skills in Finance.

The difficulty level can be selected from the Python courses we offer:-

For getting started with Python you can choose our Python for Finance Level – 1 Course, there is no prior knowledge needed. In Python for Finance Level – 2 you’ll be learning to Import Financial Data from Free Web Sources, CSV, and Excel Files. Calculate Returns, Risks, and Correlations of Stocks, Indexes, and Portfolios. Calculate Simple Returns, Log Returns, and Annualized Returns and Risks. Learn how to construct your financial index (price, equal, or value-based). Optimize your stock portfolio Calculate Sharpe Ratio, Systematic Risk, Unsystematic Risk, Beta, and Alpha for stocks, indexes, and portfolios. Understanding Modern Portfolio Theory and Risk Diversification, thus allowing for Capital Asset Pricing Model (CAPM). Insight into Mean-Variance Optimization (MVO) and how it is used in Real World (and why it is not used in many cases). Create customized charting with technical indicators (SMA, Candle Stick, Bollinger Bands, etc.) for the financial performance (e.g. Rolling Statistics, Simple Moving Averages, etc.)

What else do we offer?

• Practical-oriented course
  There is a strong practical focus to the course lessons, and students work only with the existing programs to demonstrate the concepts. Every module ends with a Quiz containing practical questions related to the course, and students are encouraged to answer the questions before moving forward.
• Quizzes for practice
  A quiz is also included at the end of every section of this course and the module end questions. We have also provided worksheets, assignments, and projects for practice.
• Instructor support for questions
  Connect with Instructor via WhatsApp/Mail. Jobaaj understands that students will have questions about the course. It is also necessary for a healthy learning process, so we encourage students to ask their questions in the videos discussion forum. Every question will be answered as soon as possible.

Who can take this Course?

• For Investment & Finance Professionals who are interested in transitioning from Excel to Python to boost their careers and work efficiency.
• Finance Students and Researchers who learned to handle large datasets and reached the limits of Excel.
• Data Scientists who want to improve their data handling/manipulation skills (in particular for statistical data).
• Anyone interested in data science (financial).
• Anybody who is interested in how Financial Performance is measured and how indices (stock) and portfolios are created, analyzed, visualized, and optimized. By using data examples instead of theories and formulas, it is easier to understand the concepts.