The graph titled “Python Job Fields: Difficulty Level (%) from Easy to Hard” illustrates the relative challenge of entering various career paths using Python. At the easier end, roles like Data Entry Automation (20%) and Web Scraping (25%) require basic Python scripting knowledge, making them beginner-friendly. Scripting & Automation (30%) and Web Development with Django or Flask (40%) need intermediate skills, including libraries and frameworks. Data Analysis (45%) adds complexity with tools like Pandas, NumPy, and data visualization libraries. Moving up, Machine Learning (60%) and Data Engineering (65%) require advanced problem-solving, algorithms, and handling large datasets. The most challenging fields include AI & Deep Learning (75%), Computer Vision (80%), and Robotics Programming (85%), demanding strong mathematical foundations, specialized libraries, and domain expertise. This ranking helps learners choose a path aligned with their skill level and career goals, progressing from easy automation tasks to cutting-edge AI applications.
Here is the tabular data that you can use for your projects:
| Field | Estimated Difficulty % |
|---|---|
| Data Entry Automation | 20% |
| Web Scraping | 25% |
| Scripting & Automation | 30% |
| Web Development (Django/Flask) | 40% |
| Data Analysis (Pandas, Excel) | 45% |
| Machine Learning | 60% |
| Data Engineering | 65% |
| AI & Deep Learning | 75% |
| Computer Vision | 80% |
| Robotics Programming | 85% |
