Enroll Course: https://www.udemy.com/course/ittensive-python-advanced/
In the ever-evolving world of data science, proficiency in Python is paramount. For those looking to dive deep into data manipulation, analysis, and automation, the Udemy course “Парсинг и анализ данных на Python: от азов до автоматизации” (Data Parsing and Analysis in Python: From Basics to Automation) by ITtensive is a highly recommended resource. This comprehensive course is structured into four major parts, covering a vast array of essential skills.
**Part 1: Data Analysis**
This section is your gateway to becoming a data wizard with Python. You’ll learn to master the `pandas` library, covering everything from importing and merging datasets to transforming, filtering, and even predicting trends. The course emphasizes practical application, teaching you to load data from various formats like CSV, TSV, and Excel, extract specific values, uncover relationships between datasets, and effectively reshape them. A significant portion of this part is dedicated to understanding linear regression, equipping you with the mathematical foundation to identify linear relationships and predict future values with confidence.
**Part 2: Data Parsing**
Moving beyond structured data, this part delves into the art of data parsing. You’ll explore data acquisition in Python using the `requests` library, working with APIs, and handling JSON and XML formats, including SOAP. The course doesn’t shy away from unstructured data, teaching you how to scrape HTML content, extract valuable information, and convert it into dataframes. A key takeaway here is the creation of a multi-process web crawler to efficiently gather data from entire websites. The section concludes with setting up SQLite and seamlessly loading your collected data into a database, with the ability to query it directly into dataframes.
**Part 3: Data Visualization**
What good is data without the ability to visualize it effectively? This part demystifies data visualization using `matplotlib` and `seaborn`. You’ll learn the anatomy of `matplotlib` and master various chart types, including line, area, bar, and pie charts. The course highlights how to visualize data dependencies and linear regression with `seaborn`, creating insightful box plots, pair plots, and distribution plots. Special attention is given to time-series data, covering line charts, moving averages, deviations, and Japanese candlesticks. The final segment introduces `geopandas` for working with geo-data and building choropleth maps from multiple datasets.
**Part 4: Report Generation and Automation**
The final pillar of this course focuses on bringing your data insights to life and automating workflows. You’ll learn to create and manipulate PDF documents, generate them from HTML using templating engines, and automate email reporting. The course covers essential libraries like `reportlab`, `pypdf2`, `pdfkit`, `jinja2`, `smtplib`, and `email`, along with the `wkhtmltopdf` binary. Practical skills include generating PDFs via a canvas, parsing existing PDFs, merging documents, creating HTML and PDF from HTML, templating HTML with `jinja2`, and handling binary data with Base64 encoding. The course culminates in sending emails, including HTML-formatted emails with attached PDF reports.
**Recommendation**
This course is an exceptional choice for anyone serious about becoming proficient in data analysis and parsing with Python. Its structured approach, comprehensive coverage of essential libraries, and practical, hands-on exercises make it ideal for both beginners and intermediate learners looking to advance their skills. The ability to automate reporting and data collection is a significant advantage in today’s job market.
**Important Note:** To access the ITtensive courses on Udemy, you need to contact them directly at support@ittensive.com with the name of the course or group of courses you wish to enroll in.
Enroll Course: https://www.udemy.com/course/ittensive-python-advanced/