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Python classes recently conducted by online tutors
Recent Python lessons for all levels
Mohit taught 2 days ago
An instructor and a university student from the University of Southern California in Los Angeles practiced Python, focusing on using loops to manipulate arrays and perform calculations. The student worked on creating arrays, taking user input, and performing calculations such as summing and multiplying elements. The instructor assigned practice problems and mentioned that they would cover indentation in the next lesson.
Python Lists
For Loops
Input Function
List Append Method
Multiplication Assignment Operator (*=)
Mohit taught 7 days ago
Mohit and a student from Texas A&M University discussed their progress in learning Python, including their use of resources like CS50 and the "Python Crash Course" book. Mohit explained VS Code terminals, Python data types, and the `flush` argument in the `print()` function. Mohit advised the student on learning strategies and will provide notes from the lesson, which was not recorded; they scheduled another lesson for Monday.
Data Types in Python
VS Code Terminal
Input Function
Print Function
Flush
Mohit taught 9 days ago
Mohit Kadwe recently helped Chris Russell get started with Python development in VS Code. Their lesson focused on foundational aspects, including basic Python syntax, navigating VS Code's interface, and understanding code execution. Chris applied these concepts by writing a simple calculation program. Mohit then assigned a video on Python fundamentals as homework, with their next lesson set for Friday morning.
VS Code Interface
Data Type Conversion
Input Function
File Management in VS Code
VS Code Terminals
Debugging in VS Code
Python Interpreter
Steven taught 15 days ago
Steven collaborated with a student from Texas Christian University in Fort Worth on improving an Excel VBA tool designed to analyze Netflix data. Steven reviewed the student's code, focusing on data validation, error handling, code structure, and data import/cleaning techniques. They discussed strategies for improving efficiency and readability, and the student will receive the updated file to review before their next lesson on Friday the 15th.
Data Import Methods
Sorting Data
File Path Validation
Variable Naming Conventions
Subroutine Structure
Error Handling
VBA Efficiency - 'With' Statements
Data Exploration
Steven taught Olivia 15 days ago
Steven recently tutored Olivia on a data science assignment, specifically focusing on essential data preprocessing steps. During their lesson, Olivia gained practical experience implementing these steps in Python using Pandas, covering tasks such as reading CSV files, dropping unnecessary columns, creating dummy variables, and standardizing features. They've scheduled another lesson to continue their work, with Olivia preparing more focused questions and sharing her code in advance.
Dropping Columns
Dropping Rows
One-Hot Encoding
Standardization Necessity
Steven taught Edward 22 days ago
Steven Lawrence is currently collaborating with E.T. on the development of a VBA tool within Excel, designed to process various datasets, starting with employee information and later E.T.'s Netflix viewing history. Their recent lesson covered crucial topics for this Excel VBA utility, such as dynamic row counting, efficient data loading, and advanced error handling techniques beyond simple message boxes. They also delved into data parsing using delimiters and the creation of output sheets complete with error indicators. The ultimate aim for this tool is to enable standalone data import from user-specified paths, record validation, and comprehensive error logging for analysis. They've scheduled another meeting to review the progress made on the project.
Adding Sheets in VBA
File Path Reliability
Looping Through Data
Variable Naming Conventions
Error Handling in VBA
Text to Columns Feature
VBA vs. Python for Excel
Storing Error Information
Python classes online for kids, beginners, and coding enthusiasts
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Online Python learning at Wiingy
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Learn Python Online: Master Programming with Expert Python Tutors

Why Choose Python for Your Coding Journey?
Python is the most popular programming language in the world for a reason it’s easy to read, beginner-friendly, and incredibly versatile. From web development and automation to data science and artificial intelligence, Python powers everything. Its straightforward syntax makes coding approachable, helping you quickly understand and write effective programs, no matter your skill level.
What Can You Do With Python?
Python is widely used in diverse fields and industries, including:
- Web Development: Build robust websites and apps using Django, Flask, or FastAPI frameworks.
- Data Science & Analysis: Analyse and visualise data using libraries like Pandas, NumPy, and Matplotlib.
- Artificial Intelligence & Machine Learning: Create intelligent systems and predictive models with TensorFlow, Keras, and scikit-learn.
- Automation & Scripting: Automate everyday tasks, improve efficiency, and simplify workflows.
- Game Development: Develop engaging games and interactive experiences using libraries like Pygame.
Why Learning Python Online is More Effective
Learning Python online is an exceptionally effective way to master coding, offering distinct advantages over traditional methods. Here's why:
1. Personalised Learning Experience
Online Python tutoring provides one-on-one interaction tailored specifically to your learning speed, style, and goals. Unlike crowded classrooms, you get direct, customised support, helping you grasp complex concepts quickly.
2. Flexible Scheduling
Online learning gives you the freedom to learn anytime, anywhere. Whether you're at home, in a café, or traveling, you can consistently progress without interruption. Flexibility helps you fit Python lessons seamlessly into your daily life.
3. Instant Feedback and Support
With online Python tutoring, you receive immediate feedback on your code, accelerating your learning process. Tutors identify and correct mistakes instantly, guiding you towards better coding habits right from the start.
4. Interactive and Engaging Learning
Online Python platforms often use interactive tools, coding challenges, quizzes, and visual demonstrations. This interactive approach makes Python learning engaging, enjoyable, and easy to retain.
5. Access to Top Experts Globally
Online Python tutoring connects you with experienced tutors from around the world. You're not limited by geography, so you can choose tutors who specialise in areas aligned with your interests, such as web development, data science, or AI.
6. Real-World Projects and Applications
Online Python courses often emphasize hands-on projects and real-world scenarios. You’ll build practical skills quickly, working on tasks that mirror professional environments preparing you effectively for future job opportunities.
7. Cost-Effectiveness
Online Python learning eliminates travel expenses, saves commuting time, and provides affordable course options. You receive high-quality education without the added costs associated with traditional classroom setups.
8. Continuous Access to Resources
Online learning platforms provide recordings, notes, and resources available 24/7. You can revisit lessons, review key concepts, or practice coding whenever needed, ensuring thorough understanding and long-term retention.
9. Comfortable Learning Environment
Learning Python online allows you to study comfortably and confidently from your own space. A stress-free learning environment significantly enhances your concentration, motivation, and overall success.
When Should You Start Learning Python?
There's never been a better time than now. With expert online tutors, easy access to resources, and countless career opportunities waiting, today is perfect to begin your Python learning journey.
Where Can Python Skills Take You?
Learning Python opens the door to numerous exciting career paths, including:
- Software Developer
- Data Scientist
- Machine Learning Engineer
- Web Developer
- Cybersecurity Analyst
- Automation Specialist


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