Welcome to our course on Real-World Applications and Case Studies in Web Scraping!
This dynamic and engaging course is designed for individuals eager to deepen their understanding of web scraping through practical, real-world examples. As we delve into actual case studies, you’ll see firsthand how web scraping can be applied across various industries to solve problems, enhance decision-making, and unlock new opportunities.
Throughout this course, you will be guided through the nuanced landscape of web scraping, from ethical considerations and legal compliance to technical execution and data management. By focusing on real-world applications, the course not only teaches you the theoretical underpinnings of web scraping but also provides you with actionable insights and skills that can be applied in your own projects or careers.
Whether you are a data scientist, business analyst, or a developer looking to expand your toolkit, this course will arm you with the knowledge and expertise to harness the power of web scraping effectively and responsibly. Prepare to transform the way you think about data gathering and its potential for impact within your professional sphere.
Curriculum
- 7 Sections
- 42 Lessons
- 7 Weeks
- Module 1 E-commerce and RetailOverview7
- Module 2 Social Media and Networks7
- 2.12.1 Introduction – Social Media and Networks
- 2.22.2 Lesson 1 – Extracting Social Media Data
- 2.32.3 Lesson 2 – Sentiment Analysis
- 2.42.4 Lesson 3 – Influencer and Trend Analysis
- 2.52.5 Exercises – Social Media and Networks
- 2.62.6 Quiz – Social Media and Networks10 Minutes5 Questions
- 2.72.7 Summary – Social Media and Networks
- Module 3 News and Content Aggregation7
- 3.13.1 Introduction – News and Content Aggregation
- 3.23.2 Lesson 1 – News Aggregation
- 3.33.3 Lesson 2 – Topic and Trend Identification
- 3.43.4 Lesson 3 – Automated Summarization
- 3.53.5 Exercises – News and Content Aggregation
- 3.63.6 Quiz – News and Content Aggregation10 Minutes5 Questions
- 3.73.7 Summary – News and Content Aggregation
- Module 4 Financial Markets and Data7
- 4.14.1 Introduction – Financial Markets and Data
- 4.24.2 Lesson 1 – Scraping Stock Market Data
- 4.34.3 Lesson 2 – Economic Indicators and Analysis
- 4.44.4 Lesson 3 – Real-Time Alerts and Trading Systems
- 4.54.5 Exercises – Financial Markets and Data
- 4.64.6 Quiz – Financial Markets and Data10 Minutes5 Questions
- 4.74.7 Summary – Financial Markets and Data
- Module 5 Real Estate and Property Markets7
- 5.15.1 Introduction – Real Estate and Property Markets
- 5.25.2 Lesson 1 – Property Listings and Market Analysis
- 5.35.3 Lesson 2 – Rental Yield Calculations
- 5.45.4 Lesson 3 – Geographic and Demographic Analysis
- 5.55.5 Exercises – Real Estate and Property Markets
- 5.65.6 Quiz – Real Estate and Property Markets10 Minutes5 Questions
- 5.75.7 Summary – Real Estate and Property Markets
- Module 6 Travel and Tourism7
- 6.16.1 Introduction – Travel and Tourism
- 6.26.2 Lesson 1 – Hotel and Flight Price Tracking
- 6.36.3 Lesson 2 – Tourism Trend Analysis
- 6.46.4 Lesson 3 – Event and Attraction Analysis
- 6.56.5 Exercises – Travel and Tourism
- 6.66.6 Quiz – Travel and Tourism10 Minutes5 Questions
- 6.76.7 Summary – Travel and Tourism
- Module 7 Health and Science7
- 7.17.1 Introduction – Health and Science
- 7.27.2 Lesson 1 – Medical Research Data Collection
- 7.37.3 Lesson 2 – Epidemiological Data Tracking
- 7.47.4 Lesson 3 – Scientific Data Aggregation
- 7.57.5 Exercises – Health and Science
- 7.67.6 Quiz – Health and Science10 Minutes5 Questions
- 7.77.7 Summary – Health and Science
Requirements
- Basic ability to use computers is needed
- A desire to learn is essential
- You should have time to complete exercises
- Having an interest in the subject matter is important
- Ability to apply learning to real-life situations is encouraged
- No minimum education requirements are necessary
- No professional experience requirements are expected.
Features
- Real-World Applications and Case Studies: This course bridges theory and practice, helping students understand practical applications of learned concepts
- Case Study Analysis: Techniques for analyzing case studies to draw practical insights are provided
- Problem-Solving Skills: Students learn problem-solving strategies to apply knowledge effectively
- Industry Examples: Real-world examples from various industries are shared
- Research-Based Applications: Students explore how research translates to real-world applications
- Adaptability: Techniques for adapting theoretical knowledge to dynamic settings are discussed
- Critical Analysis: Emphasis is placed on critically analyzing real-world data and situations.
Target audiences
- Practical Learners: Students and professionals looking for real-world applications to bridge theoretical knowledge with practice
- Researchers: Individuals wanting to explore case studies that demonstrate theoretical concepts
- Career-Changers: Those seeking practical insights to apply in a new field.