Python with AI, Web, Automation, and Data Science-Virendra M

Hi there, my name is Virendra M., and I have been teaching Python, AI, Data Science, Web Development, and Automation for over ten years. I have taught working professionals who wish to advance their knowledge of Python and AI technologies, even if they are not from a technical background, as well as students from 8th–12th grades, B.E., and B.Tech programs.

My teaching method is project-based and hands-on, which simplifies complex concepts. I offer flexible online and offline classes in Hindi and English. Over the years, I have helped hundreds of students develop practical Python projects, boost their careers, and gain confidence in Python programming online.

📘 Course Name

Mentor Virendra M. – Python with AI, Web, Automation, and Data Science

🔹 Course Summary

This course is ideal for beginners, intermediates, and professionals who want to learn Python programming online, AI, Data Science, Web Development, and Automation. The curriculum is customizable based on the student’s skill level and career goals.

📚 Course Material

1. Fundamentals of Python

• Overview of Python and setup

• Operators, variables, and data types

• Control flow: functions, loops, and if statements

• File handling and exception management

• Modules and packages

2. Python for Web Development (Flask & Django)

• Introduction to the Django framework

• Building web applications with Django

• Models, views, templates, and URL routing

• REST API development with Django

• Introduction to Flask (optional)

3. Machine Learning & AI with Python

• Libraries: Seaborn, Matplotlib, Pandas, Numpy

• Principles of Machine Learning

• Supervised and Unsupervised Learning

• Scikit-learn for ML algorithms

• Creating AI models and prediction systems

4. Automation with Python

• Web scraping using BeautifulSoup and Selenium

• Automating tasks with Python scripts

• Workflow automation and scheduling

• Data and file automation

5. Python for Data Analysis & Data Science

• Data collection, cleaning, and preprocessing

• Exploratory Data Analysis (EDA)

• Data visualization techniques

• Handling large datasets

• Real-time data projects

6. Projects & Real-World Applications

• Build real-time web applications

• Data analysis dashboards and projects

• AI/ML prediction models

• Automation scripts for real-world use

7. Teaching Methodology

• Practical coding with real-world examples

• Individual guidance and mentorship

• Regular assignments and mini-projects

• Career advice and professional portfolio guidance