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% |
Ankit Srivastava is an IT trainer, technology educator, and digital skills mentor with expertise in programming, data analytics, AI, and software development. He has successfully trained thousands of learners, with more than 10,000 student enrollments on Udemy. His practical teaching approach empowers students and professionals to build in-demand technical skills. Colorstech channel where Ankit posts video tutorials has more than 8000 Subscribers.
