Workshop Materials for Data Science at Rutgers-New Brunswick Libraries (Fall 2024)
Topics covered, by workshop number are:
- Introduction to Python Programming:
This workshop is designed for beginners with little to no experience in programming, aiming to provide a rapid yet comprehensive introduction to the world of Python, one of the most popular and versatile programming languages today. Learners will quickly grasp Python syntax, script execution, and fundamental constructs like variables, data types, and operators. They will also explore control structures like if-else statements, loops, and functions, gaining practical skills in data structures such as lists, tuples, sets, and dictionaries.
- Advanced Python Programming:
The workshop covers debugging and error handling in Python to help participants understand common programming errors and how to fix them. Object-oriented Programming. Functional Programming in Python: Concepts of functional programming. Using lambda, map, filter, reduce for functional style programming. Introduction to Data Structures (Stacks and Queues).
- Web Scraping with Python: Techniques and Ethics
Teach participants how to programmatically gather data from the internet using Python, focusing on legal and ethical considerations. Introduction to Web Scraping: Overview of what web scraping is and its practical applications in various industries like market research, sentiment analysis, and competitive analysis. Discussion of the legal and ethical considerations, including respect for website terms of service and data privacy laws. Tools and Libraries: Introduction to the essential Python libraries for web scraping such as requests for making HTTP requests and BeautifulSoup for parsing HTML and XML documents. Building a Simple Web Scraper: Step-by-step coding session where participants build a basic scraper to extract data from a simple HTML page. Techniques for navigating and parsing a website's structure, handling exceptions, and managing errors. Data Handling: Methods for cleaning and organizing scraped data using Pandas. Strategies for storing scraped data effectively in databases or CSV files. Advanced Web Scraping Techniques: Techniques for dealing with pagination, handling login/authentication, and scraping data from APIs. Tips for scraping efficiently and responsibly, including setting request headers, managing request intervals to avoid server overload, and using proxies and VPNs for anonymization. Ethical Web Scraping Practice: Deep dive into ethical considerations, emphasizing respect for data privacy and adherence to legal restrictions. Discussion on how to approach scraping projects with a focus on sustainability and minimal impact on the target websites.
- Mastering Data Analysis: Pandas and NumPy Essentials:
This workshop is designed to equip learners with powerful tools for data analysis in Python. Participants will delve into the world of NumPy, exploring its efficient arrays and array operations, which form the backbone of numerical computing in Python. The workshop then shifts to Pandas, where learners will get hands-on experience with its fundamental data structures - Series andDataFrame. This comprehensive session is ideal for anyone looking to enhance their data analysis skills, offering the tools needed to unlock insights from data with efficiency and precision.
- Data Management with Python Workshop (SQL and NoSQL)
The workshop will equip participants with the skills to effectively interact with both SQL and NoSQL databases using Python, highlighting the appropriate use cases and best practices for each.