MERIT
,
Robotics and Process Automation
The course provides an in-depth understanding of Robotic Process Automation (RPA), focusing on the design and use of RPA systems for structured business process automation. The course covers modern programming languages and management algorithms used in the development of RPA solutions. It examines methods and algorithms necessary for data management and process optimization, using intelligent system management methods. Theoretical exploration of programming libraries and development tools in the context of RPA is offered. The interaction of external input/output devices using system management and process automation methods is also discussed. The course analyzes data flow control methods. Through practical tasks, students are introduced to data processing methods, graph search algorithms, classification, optimization, machine learning, and big data processing methods, which are crucial for effective RPA implementation.
This course introduces robotic process automation (RPA) with Python. You will learn how to automate routine office and data-processing tasks: reading and writing Excel, CSV, text and PDF files, collecting data from websites, controlling a web browser and automating desktop applications, files and e-mail.
The course is practice-oriented: every lesson combines a video lecture, short theory topics with code examples and a knowledge check. Three lessons also include a practical task based on real-life data.
COURSE LEARNING OBJECTIVES
- Master Python basics needed for automation: input/output, conditions, loops and data structures.
- Automate data processing in Excel, CSV and text files using
openpyxlandpandas. - Extract and generate information in PDF documents using
PyPDF2andreportlab. - Collect data from the web using
requestsandBeautifulSoup, and automate browser actions withSelenium. - Automate desktop, file and e-mail operations using
pyautoguiand standard Python libraries. - Validate input data and build reliable automation scripts that handle incorrect data.
COURSE STRUCTURE
- Introduction to Python
- Processing Excel data with Python openpyxl (+ Practical task Nr.1)
- Processing Excel data with Python Pandas (+ Practical task Nr.2)
- Processing Text Data with Python
- PDF file processing with Python (+ Practical task Nr.3)
- Web Scraping and Data Extraction
- Browser automation with Selenium
- Desktop GUI Automation with pyautogui
- File, E-mail and System Automation
HOW TO COMPLETE THE COURSE
- Go through all lessons and topics in the given order – the next step opens after the previous one is completed.
- Every lesson ends with a short knowledge check (Quiz Nr.1–9). Pass it with at least 80% correct answers to unlock the next lesson.
- Complete the practical tasks at the end of their lessons: Nr.1 (openpyxl lesson), Nr.2 (Pandas lesson) and Nr.3 (PDF lesson). Download the project template, run your program locally and enter the result it produces. Each practical task must also be passed with at least 80%.
- Quizzes and practical tasks can be retaken.
REQUIRED SOFTWARE
- Python 3 and a code editor / IDE (e.g. Visual Studio Code or PyCharm).
- Python libraries are installed with
pip(e.g.pip install openpyxl pandas PyPDF2 requests beautifulsoup4 selenium pyautogui). - No previous programming experience is required.
INSTRUCTORS
- Aleksejs Jurenoks
Kurss Content
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