The syntax of Python helps to improve the speed of the working system thereby increasing the production of an organization through the generation of products or development of software. It also helps to reduce the chances of mistakes which are even more serious while generating a product for a profoundly controlled sector such as finance. There are several attractive features for the programming language to be highly accepted in most the financial corporate-like; simplicity, robust modeling capacities, and exploring capability. It is found to be famed among analysts, traders and researchers. The applications inbuilt in python find use in different sectors of finance ranging from risk management to cryptocurrencies. Learning the topic is not a hard task, it needs only about 8 weeks to understand the fundamentals and codes in python. The developers of python spend much more time in the field. Python code is briefed and secured to simple English. Python is the ultimate for prototyping and swift, iterative improvement. In accumulation to its great regular library of useful tools, Python has great third-party libraries for financial analysis and computing, such as the Pandas and NumPy libraries.
1. Python for Finance: Investment Fundamentals & Data Analytics by Udemy
The training program is considered as a complete package to learn about programming and Real-World Financial Analysis in Python. The course is dedicated to delivering the importance in the finance sector along with the fundamentals of investments and associated data analytics. The learner would be converted into an expert by the end of the course is what is promised by the providers. They would be able to handle financial calculations and portfolio optimization tasks. The core areas of interest are; finance fundamentals, rate of return of stocks, risk of stocks, rate of return of stock portfolios, risk of stock portfolios, the correlation between stocks, covariance, Monte Carlo simulations, application of black Scholes formula, and using Monte Carlo for stock pricing. The topics are explained using a theoretical backdrop as well as practiced using python. Aspiring data scientists, Programming beginners, People interested in finance and investments, Programmers who want to specialize in finance, those who want to learn how to code and apply their skills in practice, and Finance graduates and professionals who need to better apply their knowledge in Python can opt for the course.
2. Python for Finance: Portfolio Statistical Data Analysis by Coursera
The topic of interest is the ability to use python to execute collection allotment and analysis of the performance of portfolio using metrics such as cumulative return, average daily returns, and Sharpe ratio. The companies that are well known are analyzed for the last 7 years. Facebook, Netflix, and Twitter are the considered organizations. The project is invaluable for investors for managing their portfolios, visualizing datasets, finding useful patterns, and gaining valuable insights about stock daily returns and possible risks. This project can be useful for the analysis of company stocks, indices, or currencies and the presentation of portfolios. The teachers are proficient in the field and they take the complete responsibility to guide and cater according to the needs of the student. The video projections during the course take the learner through the following path; understanding the problem statement and business case, importing datasets and libraries, performing random asset allocation and calculating portfolio daily return, data visualization, and understanding the calculation of the portfolio statistical metrics.
3. Introduction to Python for Finance by Datacamp
The course as the name indicates is a prologue to Python for financial analysis. The industry of finance is opting for Python for common aspects of programming and quantitative analysis. The understanding of trading dynamics to the management of possible risks comes under it. The main area of focus is the financial sector. They make use of examples to learn the topic better. The different methods of storing and manipulating economic statistics to recognize the tendency of financial drift are also analyzed during the time of the study.
4. Machine Learning for Finance – Python Fundamentals by Corporate Finance Institute
Finance professionals are more interested in knowing the fundamentals of Python. The set of skills required in managing the language Python becomes essential in order to progress in the financial sector. The course begins at a slower rate with the basics and then moves on to more sophisticated topics. The main areas that are covered are setting up Anaconda and Jupyter Notebooks for Python, Python Native Data Types, Input, and output formatting building custom functions, developing loops and conditional logic, and usage of Numpy and Pandas package. The completion of the course enables the learner to write and put forth the basic codes of the language for enhanced calculation, creating and manipulating important data structures sets, and dictionaries; and many more beneficial aspects to enrich the knowledge in the world of finance.
5. Python and Statistics for Financial Analysis by Coursera
Python is the booming programming language of the modern era. The expression in simple form and the ease of reading it is being accepted widely throughout the financial industry. The concepts of statistical data and python coding are applied to the analysis of financial data. The completion of the course enables the learner to use python language for importing, pre-processing, saving, visualizing generating new variables, recalling and applying statistical concepts into financial contexts, creating models using multiple linear regression model, evaluating the trading model using different investment indicators, all for practicing python coding without establishing any client applications. The learner gains the skills of statistical analysis, financial analysis, financial data analysis, and python programming
6. Python and Statistics for Financial Analysis Offered by the Hong Kong University of Science and Technology on Class Central
The course is offered through Coursera and is aided by The Hong Kong University of Science and Technology. Python is gaining importance as a programming language. The financial sector is nowadays more dependent on Python for its analysis of data. The core concepts include Visualizing and Munging Stock Data, Random variables and distribution, Sampling and Inference, and Linear Regression models for financial data analysis.
7. Python for Finance Level -1 by Jobaaj Learnings
The course on Python is mainly formatted to encourage the learning of the programming language for any beginner. The financial sector is growing at an enormous rate today and so they require the technology also to grow along with equal speed. The course is designed after getting reviews from professionals in the field of finance. The course is an All in One course which is the initial footstep into the programming world. Python is introduced in the basic and intermediate levels and used in Data Analysis, Data Science, Investment Banking, Machine Learning, and Financial Modeling. The classes are delivered as video lessons. Worksheets and quizzes are given to check the progress of the study. The teachers are qualified in the language and they constantly support the learners in every way possible. The learners get a thorough knowledge on how to deal with things once start working on them. Learners don’t require any prior understanding of coding to take the course. The course is suitable for those who are already working in the language and would like to supplement with more information.
8. Certificate Program in Python Programming for Finance by Indian Institute of Quantitative Finance
Python is the best-known programming language as of now, due to its simplicity and easily understandable mode. It is getting furthermore popular among those who are using it and also many more are coming forward to learn about it. Python has a set of libraries that is on the verge of tremendous growth making the work of people using it easier with minimum effort. Coding is made effortless difficulties and hurdles in the financial domain are solved easily through the administration of the language. The course is technically for teaching the basics of the subject along with the know-how of writing programs, especially for financial needs. The multifaceted banking applications of the finance sector are concluded at the end of the course.
9. Analyze Financial Data with Python by Codecademy
Python serves to be the best programming language that is growing so fast and enabling the processing, analyzing, and visualizing financial data transfer. The topics of study include; the introduction to Python along with its utilization in the financial sector; basics of NumPy, multidimensional arrays and matrices, and to improve the analysis of the financial status; introduction to Pandas, data manipulation, and assessing of financial data from APIs; visualizing finance data, basic understanding about Matplotlib, a Python enclosure for data visualization, and determining the optimization of the range of stocks; regression basics, calculating the relationship between variables; and finally to end up with a project to test the financial and programming skills. In total; the learner would be able to achieve a real-life ability to work in an environment related to the core. The educators are following a step-by-step path with good guidance and support. The contents are specifically selected to increase the velocity of the development of skills.
10. Machine Learning with Python for Finance Professionals Offered by by ACCA on edx
The course is aimed at professionals in finance. The language is taught in sessions with practical skills in order to increase the use of tools to save time and enhance the working in the organization. The program is offered by ACCA (Association of Chartered Certified Accountants). The association is the universal organization for professional accountants. It is also part of the FinTech for finance and business leaders’ professional certificate program. The program includes the deep-rooted information about machine learning output, improved examining of a model, and association with data scientists and organizations to force acceptance and employing of machine learning. Knowledge acquiring and skill attaining on digital financing are essential for a technological shift to increase business and to make it more centered towards the customer. The modules of study include the introduction to python from the beginning such as data types, variables, mathematical operators, flow control, and functions; using Python for data analysis; automating Excel workflows using Python; use of Machine Learning; know-how of the basic workings of a machine learning model; application to real-world machine learning examples to meet practical objectives such as evaluation and improvement of the model and detection and correction of errors.