Steven Lawrence
Coding Tutor from Thomas College - Python Lessons for Kids
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Steven Lawrence
Bachelors degree
/ 55 min
About your coding tutor - Steven
I am an experienced programmer with a passion for problem-solving and software development. With years of coding experience across multiple languages, including Python, I specialize in breaking down complex problems into clear, logical steps. My ability to analyze challenges and develop efficient solutions has helped me create robust applications, automate tasks, and optimize workflows. One of my key strengths is visualizing code execution—understanding how each function interacts within a system before implementation. This skill is especially valuable in Python, where data structures, algorithms, and logic flow play a critical role in building scalable solutions. I teach my students how to think beyond individual lines of code, helping them develop a strategic mindset for efficient programming. My structured six-lesson series is designed to prepare students for professional coding roles. Whether you’re aiming to start a career in tech or refine your programming skills, my approach ensures you gain a deep understanding of problem-solving strategies, debugging techniques, and real-world applications—especially in Python, one of the most versatile and powerful languages in the industry. If you’re looking for a tutor who can simplify programming, strengthen problem-solving abilities, and help you visualize what happens when code is executed, I’d love to work with you!
Hands-on learning
Students gain confidence applying coding skills to real projects.
Paired coding for effective learning
90% of students benefit from collaborative lessons.
Proven success with code projects
85% of students complete personal projects in a few months.
Coding tutor specialities
Job readiness
Upskilling
Assignment help
Project help
Code Review
Code Optimization
Coding class highlights
Programming is more than just writing code—it’s about designing solutions that are efficient, scalable, and adaptable. While implementation is important, code design is the foundation of a well-structured program. A strong design ensures code remains maintainable and capable of handling real-world challenges. I structure my teaching approach around three key steps: WHAT, WHY, and HOW. WHAT – We define the problem and establish business rules that shape the project. Clear objectives ensure smart design choices. WHY – We analyze the purpose behind each function or system. Understanding why a solution is needed guides decision-making. HOW – With the what and why established, we write clean, optimized code with confidence, prioritizing architecture over rushed implementation. I foster a relaxed, interactive learning environment where students feel comfortable asking questions and developing creative solutions. My lessons are project-based, focusing on topics that genuinely inspire each student—whether it's automation, data analysis, or web applications using Python. By prioritizing code design first, students gain the ability to visualize how their code functions before writing it. This leads to cleaner, more efficient programs that stand the test of time. My goal is to help students master the thought process behind coding, ensuring long-term success in any tech career.
Hands-on coding classes
Record lessons
Parent feedback
Note taking
Open Q&A
Chat for quick help

Coding concepts taught by Steven
The session focused on streamlining data import from a CRM system into Excel. The student and tutor explored methods for automating data extraction, transformation, and loading. They discussed database normalization principles and practical Excel techniques for data manipulation and error handling. The goal is to automate the process of importing data, validating it, and generating reports for various business metrics. The student was assigned the task of gathering all required data headers from their CRM system to enable future automation.
Data Export and Import
Data Normalization
Excel Shortcuts and Techniques
Using 'IFERROR' Function
Text to Columns Feature
Excel Import Tool with Validation
The student learned advanced Excel techniques for data manipulation, including using the TRANSPOSE function dynamically and managing data integrity during deletions. The session covered sorting and formatting techniques to present data effectively. The Tutor provided a screenshot of the sorting criteria to help the student remember the settings.
Transposing Data with the TRANSPOSE Function
Best Practices for Deleting Data in Tables
Adding Values by Paste Special
Pasting Values and Formatting
Creating Formulas Using Concatenation
Sorting Data in Tables
Filtering Data by Color
The Tutor guided the Student in creating a dynamic Excel sheet for managing employee data. The Student learned how to use VLOOKUP formulas, data validation, and advanced sorting techniques to automate data organization and maintain consistency. The session concluded with setting up error handling and dropdown menus for easier data entry and validation.
Named Ranges
VLOOKUP Function
IFERROR Function
Excel Tables
Sorting Data
Data Validation Lists (Dropdowns)
The student and tutor worked on enhancing a recruitment spreadsheet tool. The student implemented data validation rules, default values, and improved user guidance through error messages. They also started designing the interface for connecting candidates with job requisitions, planning to implement the code in the next session.
Connecting Data Across Sheets
Enhancements: Candidate Sourcing and Candidate Classification
Data Validation and User Input in Spreadsheet Applications
Google Sheets Functionality
The student and tutor reviewed the steps of the data life cycle to build a regression model, focusing on feature engineering, data scaling, and train-test splitting. They analyzed correlation matrices and discussed the impact of data standardization. The student plans to complete the assignment, incorporating the discussed techniques and insights.
Data Life Cycle
Outlier Handling
Feature Scaling (Standardization)
Random Seed for Reproducibility
Importance of Context in Data Interpretation
Data Splitting: Train
Test
The session focused on designing an Excel-based cash flow management tool with dynamic features. The student and tutor worked through data structure, formula building, and user interface design. Follow-up includes the student preparing a spreadsheet with properly formatted and described headers to facilitate formula construction in the next session.
Automating Data Entry with VBA (Visual Basic for Applications)
Data Normalization for Efficient Spreadsheets
Error Handling in Complex Excel Formulas
Distinguishing Actual Transaction Date vs. Expected Payment Date
Dynamic Date Calculations Based on Lookup Tables
Spreadsheet Design Prioritization: Functionality
Ease of Use
Learner types for coding classes
Coding for Beginners
Coding for Adults
Coding for School students
Coding for Kids
Coding for College students
Steven - Coding tutor also teaches
SQL
Coding for kids
Approach & tools used by coding tutor
Google Colab
Visual Studio Code
Jupyter Notebook

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