HRDC Reg. No: 10001466994
Duration: 21 Hours (3 Days)
Course Overview
This hands-on course provides a comprehensive introduction to data scraping and mining using Python. Participants will explore libraries like Beautiful Soup, Scrapy, and Selenium for data scraping, as well as data mining techniques like clustering, classification, and association rules. By the end of the course, attendees will have the skills to automate data extraction, clean data for analysis, and extract actionable insights for various applications.
Who Should Attend
Industries:
- Technology
- Finance
- Marketing
- Research
- Data-driven industries
Participants:
- Data Analysts
- Data Scientists
- Software Developers
- Researchers
- Professionals seeking automation in data collection and analysis
Why Choose This Course
This HRDC-claimable course (Reg. No: 10001466994) offers practical skills in data scraping and mining, empowering participants to automate data workflows and analyze datasets for informed decision-making.
Learning Outcomes
Participants will:
- Understand the fundamentals of data scraping and data mining.
- Utilize Python libraries like Beautiful Soup, Scrapy, and Selenium for web scraping.
- Apply clustering, classification, and association rule techniques in data mining.
- Process and clean data for analysis using Python.
- Automate data extraction and analysis workflows.
- Gain insights from real-world datasets through practical applications.
Prerequisites
- Basic Python programming knowledge.
- Familiarity with HTML and web page structures.
- Basic understanding of data analysis concepts.
Lab Setup
- Software: Python environment (Anaconda or similar), Jupyter Notebook.
- Libraries: Beautiful Soup, Scrapy, Selenium, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn.
- Internet access for live data scraping exercises.
Teaching Methodology
- Interactive lectures with demonstrations.
- Hands-on coding sessions and exercises.
- Real-world case studies and projects.
- Continuous assessments through quizzes and challenges.
