Mariana Meraz

Knowing the fundamentals of machine learning (ML) and how to implement basic models like linear regression is highly relevant to both my accounting career and running my parents' small car business. Knowing how ML works, especially through supervised, unsupervised, and reinforcement learning, gives me a foundation to use data-driven decision making in accounting and business uses. Machine learning is also a solution becoming unavoidable in accounting and finance, particularly financial forecasting, risk management, and fraud detection. For example, linear regression as viewed in the Google Colab assignment can make predictive revenue patterns for the future based on past finance data. Accountants use ML to detect unusual transactions as a method of detecting probable fraud or accounting mistakes. In addition, unsupervised learning techniques, such as clustering, can be applied to segment customers or identify spending patterns for improved financial planning.  Reinforcement learnin...

Acquiring the skills to manipulate and clean data using Python, and more so using libraries like Pandas and NumPy, is highly beneficial in a career in accounting. Accountants usually handle large volumes of data, for example, financial statements, expense reports, and tax returns. Using Python, they can clean data automatically, making it accurate and efficient. Also, fraud detection and auditing can be aided by methods of data analysis to identify duplicate payments, missing values, or inconsistencies in financial data. Pandas functions make all this easy. In addition, Python is also useful for budgeting and forecasting because statistical functions in NumPy help accountants grasp trends, averaging, and predicting future fiscal performance based on past trends. Tax and compliance reporting can also be made automatic to reduce the rate of manual intervention and errors. With these capabilities implemented in accounting steps, experts are able to increase efficiency and make more inform...

     Python control structures conditional statements, and loops are central to writing good and sensible programs. Understanding how loops operate, either through the use of for loops that loop around sequences or while loops that continue executing based on a condition, is the foundation of automating repetitive tasks. Also, conditional statements such as if and if else allow a program to make decisions based on some conditions, which is a significant feature in actual applications such as game development, automation, and data handling. The exercises, for example, printing numbers, determining even or odd numbers, and creating a guessing game, reinforce these concepts with practical experience. This practical approach not only reinforces coding abilities but also hones problem-solving abilities essential for coding.      Control structures beyond Python programming have significance in the fields of data science, artificial intelligence, and software dev...

This chapter discussed Google Colab, which is a cloud-based platform where one can write and execute Python code without installation on their local machine. While this may sound more relevant to programming-related fields, it has tremendous benefits for accountants too. After learning accounting, Google Colab and Python can provide a variety of advantages. The greatest benefit is probably the ability to analyze and automate. Accounting is increasingly data-driven in decision-making, and Python is an incredibly powerful tool for handling big data. With Google Colab, accountants can use Python to financial modeling, trend analysis, and automating routine tasks such as reconciliations and report generation. Another advantage of Google Colab is its cloud platform, which facilitates seamless collaboration. Since files are stored in Google Drive, accountants and financial analysts can collaborate over reports and financial models in real-time. This is particularly useful in audit practices,...

Chapter one effectively highlights the revolutionary role that automation technologies play in redefining today's modern workplace. It illustrates the ways in which firms are employing automation to boost productivity, streamline processes, and remain competitive in an increasingly dynamic global economy. The description of industrial automation, robotic process automation (RPA), and artificial intelligence (AI) provides a clear image of various ways automation is utilized across industries. From financial operations and customer service to manufacturing and supply chain management, automation is becoming an invaluable asset for eliminating human error, optimizing efficiency, and enabling employees to focus on higher-level, value-added functions. But even as automation presents so many benefits, this chapter also suggests looking at its broader implications, such as displacing workforces and the upskilling necessary to adapt to them. As businesses are more and more embracing automa...

This is a primer on Python as a fundamental programming language for data science. It begins with an explanation of why Python is heavily used in the business world by virtue of being easy to use, flexible, and having a vast library ecosystem of libraries such as NumPy, Pandas, and Scikit-learn. The ease of learning and facilitation of quick prototyping of Python make it the optimal tool for data analysis and machine learning solutions. After this, the chapter is used to present the basics of Python, including syntax, variables, and data types. Different types of data such as integers, floats, strings, and lists are explained to the readers that will assist them in writing effective Python code. These basics are the building blocks of more advanced programming techniques in data science. To facilitate hands-on learning, the chapter is initiated with Google Colab, a cloud-based environment to code and execute Python code without local setup. Google Colab is particularly beneficial for d...

     Artificial Intelligence is transforming businesses, and having AI skills can help you become a job market standout. Either as a student, a career professional looking to upskill, or just an AI beginner, completing an AI project can help you gain experience and show your abilities to potential employers.         For my final project, I have chosen to design an AI Tutor for Coding and Language Learning. Drawing from my own experience and past courses, I have often found it difficult to understand complex coding concepts and pick up new languages. An AI tutor would have been a big help to me by providing instant feedback, personalized learning pathways, and interactive exercises. This project will utilize AI to assist students through coding explanations, debugging support, and language practice, thus making learning easier and interactive. AI Resume & Cover Letter Analyzer      Employers use AI to scan resumes, so why not use...