
Learn to automate accounting with Python and ai, covering profit and loss, expense visualization, anomaly detection, tax calculations, bank reconciliation, invoice processing, depreciation, and financial reporting.
Explore how to automate accounting and bookkeeping tasks with Python and generative AI, covering transaction categorization, invoice processing, tax calculations, and financial reporting using tools like Pandas, Tesseract, and ChatGPT.
Identify three main audiences—accountants, auditors, and business owners—and show how Python and generative AI automate repetitive tasks, streamline auditing, and improve financial insights.
Leverage Python for accounting data with pandas and visualize trends with matplotlib, then forecast expenses using TensorFlow GRU, and explore AI models like deep sig and ChatGPT.
Learn how ai and python automate accounting tasks by categorizing transactions with machine learning, generating financial reports with nlp, providing insights, detecting anomalies and duplicates, and processing invoices via ocr.
Calculate a profit and loss statement with Python by loading general ledger in Google Colab, cleaning data with pandas, and computing revenue, cogs, gross profit, operating expenses, and net profit.
Visualize expense data with matplotlib by preprocessing debit and credit, filtering expense accounts, grouping by account, and plotting a pie chart titled 'expense data breakdown' with labeled categories and percentages.
Learn to detect anomaly and duplicate transactions with Python on Google Colab, using a dataset, converting debit and credit, and flagging with mean plus three standard deviations.
Automate vat calculations in python by cleaning data, converting debits and credits, and computing output vat from sales revenue and input vat from purchases, yielding net vat payable or refundable.
Learn to calculate fixed assets depreciation in Python using pandas by building an assets data frame, applying a depreciation function, and deriving annual, accumulated depreciation and current book value.
Automate invoice matching with Python by merging invoice and purchase order datasets using pandas, then check quantity, unit price, and total to identify matches and mismatches.
Track accounts receivable and payable with Python by loading a dataset in Colab, cleaning numeric columns, converting dates, computing totals and net balance, and listing due statuses.
Welcome to Accounting and Bookkeeping with Python & Generative AI course. This is a comprehensive tutorial for accountants and business owners who are interested in using AI for automating repetitive accounting tasks, improving accuracy in financial reporting, and enhancing the auditing process. This course is a perfect combination between accounting and artificial intelligence, making it an ideal opportunity to practice your programming skills while improving your technical knowledge in financial accounting. In the introduction session, you will learn how AI and Python can be used to automate accounting tasks, such as categorizing transactions, generating financial reports, detecting transaction duplicates, and processing invoices. Then, in the next section, you will learn how to automate bookkeeping using Python. Firstly, we are going to calculate profit and loss by analyzing revenue and expense data systematically. This will help us understand the financial performance of the business over a specific period. Afterward, we are also going to calculate fixed assets depreciation using Python. This will enable us to accurately reflect asset value reductions on the balance sheet. Then, after that, we are going to track accounts receivable and payable to monitor incoming and outgoing payments efficiently. This allows us to maintain healthy cash flow and timely manage outstanding balances. In the next section, we are going to visualize expense data breakdown using Matplotlib. This will help us to identify major cost drivers and optimize spending. Following that, we are going to detect anomalies and duplicate transactions automatically using Python. This will allow us to reduce errors and prevent potential fraud in accounting records. Then, we are also going to automate invoice matching by comparing purchase orders, invoices, and payment data seamlessly. This will help us to streamline the accounts payable process without having to manually cross check documents one by one. Following that, we are going to automate bank reconciliation by matching bank statement transactions with internal records. This enables us to quickly identify discrepancies and maintain clean financial records. We are also going to automate tax calculation by applying relevant tax rules to each transaction accurately. This allows us to ensure compliance during tax season. In the next section we will leverage machine learning for forecasting monthly expenses, specifically we will build a forecasting model using Gated Recurrent Unit. In addition to that, we are also going to automate invoice processing using optical character recognition, specifically, we will extract text from uploaded invoice images using Tesseract. In the next section, we are going to create a system that is able to categorize transactions and generate financial statements from transaction data input using Deepseek and Open Router AI. This will help us automate data classification and streamline the financial reporting process. Following that, we are going to generate comprehensive financial reports using ChatGPT. This will enable us to transform raw data into easy to understand summaries and quickly produce insightful reports for decision-makers. Next, we are going to automate payroll processing using Microsoft Copilot. This will help us accurately calculate employee salaries, deductions, and taxes, ensuring timely and error free payroll management. Then, after that, we are going to automate journal entry creation using Claude AI. This will enable us to interpret transaction details and generate appropriate accounting entries with accurate debit and credit postings, ensuring the ledger remains balanced. Lastly, at the end of the course, we are going to analyze and summarize the cash flow statement using Julius AI. This will help us provide clear insights into company financial health, identify key trends, and make more informed strategic decisions.
Firstly before getting into the course, we need to ask this question to ourselves, why should we use Python and AI for automating accounting tasks? Well, here is my answer, by outsourcing some of the work to AI, accountants will be able to save time by handling repetitive tasks quickly and accurately, reducing the chance of human error. Additionally, it allows accountants to focus more on strategic analysis and advisory roles instead of dealing with repetitive tasks.
Below are things that you can expect to learn from this course:
Learn how to use generative AI and Python to automate repetitive accounting tasks
Learn how to calculate and display profit and loss statement using Python
Learn how to visualise expense data using Matplotlib
Learn how to detect anomaly and duplicate transactions using Python
Learn how to automate tax calculation using Python
Learn how to calculate fixed assets depreciation using Python
Learn how to match invoice with purchase order using Python
Learn how to track account receivable and account payable using Python
Learn how to automate bank reconciliation with Python
Learn how to forecast monthly expense using machine learning
Learn how to process invoice and receipt using optical character recognition
Learn how to categorize transaction using Deep Seek AI
Learn how to generate financial statement using Deep Seek AI
Learn how to create financial report template using ChatGPT
Learn how to create journal entry using Claude AI
Learn how to automate payroll processing using Microsoft Copilot
Learn how to analyze cash flow statement using Julius AI