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!
Coding tutor specialities
Job readiness
Debugging
Code Review
Assignment help
Project help
Exam prep
AI modules
Summary
Podcast
Quiz
Learnings
Flashcard
Spotlight
Zero Risk Guaranteed
15-days refund
Free tutor swap
No cancel fee
1-yr validity
24/7 support
Learner types for coding classes
Coding for School students
Coding for Adults
Coding for College students
Coding for Kids
Coding for Beginners
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 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.
Steven - Coding tutor also teaches
Coding for kids
SQL

Coding concepts taught by Steven
The tutor guided the student through using Excel's translation function, formatting spreadsheets for financial statement analysis, and performing horizontal and vertical checks on an income statement. They also discussed data management strategies, with a future session planned to delve deeper into file organization techniques.
Excel Translation Function
Excel Tables vs. Word Outlines
Creating and Formatting Spreadsheets for Printing
Financial Statement Analysis: Horizontal and Vertical Checks
The Tutor and Student reviewed and practiced VLOOKUP functions in Excel, focusing on data preparation, formula construction, and error troubleshooting. They also began exploring relative and absolute cell references for scaling calculations, with plans to revisit pivot tables in a future session.
VLOOKUP Function: Core Principles
Understanding and Using Pivot Tables
Data Preparation: Text to Columns
Relative vs. Absolute References
The student and tutor worked through practical exercises in Google Sheets, focusing on data manipulation and advanced functions like SUMIF. They practiced generating datasets using AI, cleaning and splitting data, and applying SUMIF to calculate totals based on specific criteria, with plans to continue this practice in the next session.
Data Validation for Exact Matching
Data Splitting with the SPLIT Function
Dynamic Summation with SUM(Column)
Conditional Summation with SUMIF
The Tutor and Student worked on refining Excel formulas for data analysis, specifically focusing on creating unique lists of accounts and associated personnel, and accurately calculating associated costs. They also troubleshooted formula errors and discussed methods for handling discrepancies and errors in the data, planning to build an output sheet for reconciliation in the next session.
Dependent Dropdowns (Conditional Dropdowns)
VLOOKUP with Exact Match
SUMIFS for Conditional Aggregation
Unique Function for Data Cleaning
The student and tutor worked through a complex Excel data reconciliation task using real-time financial data. They practiced advanced techniques like data alignment, formula implementation (IF statements), error identification, and formatting. The next session will involve a repeat of this process for reinforcement.
Conditional Logic with IF Statements
Identifying Data Relationships and Linkages
Data Reconciliation and Merging
The tutor guided the student through practical data manipulation techniques in Google Sheets, including splitting data, using SUM and AVERAGE functions, and extracting unique values. They practiced applying formulas and discussed efficient methods for data analysis and spreadsheet organization. The session concluded with renaming the document for future reference.
Using Functions for Data Analysis (SUM
AVERAGE
UNIQUE)
Hiding Columns and Avoiding Data Loss
Cell References and Formulas
Data Splitting with the SPLIT Function
Approach & tools used by coding tutor
Jupyter Notebook
Google Colab
Visual Studio Code
Hands-on coding classes
Note taking
Chat for quick help
Parent feedback
Weekend lessons
Record lessons

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