Steven Lawrence
Data Analysis Tutor from Thomas College Offering Comprehensive Data Science Sessions
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Steven Lawrence
Bachelors degree
/ 55 min
About your data science tutor
Hello! I’m Steven, a tutor specializing in Microsoft Excel and VBA coding. With over 10 years of Excel expertise and 3+ years of solving real-world problems with VBA, I’ve automated workflows that boosted productivity by over 300%. I offer personalized coaching, project guidance, and a structured six-lesson series designed to prepare you for a professional career using Excel and VBA. Whether you're a student or a working professional, my step-by-step approach will help you master essential techniques, optimize workflows, and automate tasks effectively. My lessons foster confidence, creativity, and problem-solving skills in a relaxed learning environment. By working on projects that challenge and inspire you, you'll gain the expertise needed to apply Excel and VBA in real-world scenarios. Let’s elevate your skills together looking forward to helping you succeed!
Data Science tutor skills
Business intelligence
Deep Learning
Data visualization
Assignment help
CoTutorAI 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 data science class
Data Science for advanced
Data Science for beginners
Data Science for intermediate
Data sciece class overview
My tutoring approach is rooted in solving real-world problems. Traditional Excel and VBA lessons often rely on basic examples that don’t translate effectively into practical scenarios. My goal is to bridge that gap, helping students develop the flexibility, creativity, and problem-solving skills needed to tackle complex challenges. I structure problem-solving into three key steps: WHAT, WHY, and HOW. First, we define WHAT—identifying the business rules shaping the project. Next, we explore WHY—understanding the purpose behind the task. Finally, we determine HOW—the implementation strategy. Many rush into execution without considering the what or why, leading to ineffective solutions. My approach ensures you design robust, scalable tools. A key part of my tutoring is a six-lesson series designed to prepare students for a professional role in tech. This structured program equips you with essential skills to efficiently manage data, automate workflows, and build solutions that withstand real-world demands. I prioritize building tools that are efficient and sustainable. Simple solutions are often the best, but they must hold up under real-world pressures. Through my training, you’ll gain expertise in Excel and VBA, making you a valuable asset in any professional setting. If you're ready to take the next step in mastering Excel and VBA for a career in tech, let's get started!
Improved problem-solving skills
92% of students report faster problem-solving after lessons.
Project-based learning for real-world skills
90% of students complete relevant coding projects.
Focused on real-world coding applications
Build real projects, from apps to websites.
Your data science tutor also teaches
Data Analysis
Excel
Data Science concepts taught by Steven
The Tutor introduced fundamental Python programming concepts including functions, basic arithmetic operators, and data types. The Student practiced using the `print()` function for output, performing calculations, and understanding the difference between data types like integers and strings. The session concluded with an introduction to variables, emphasizing their role in storing and manipulating data dynamically, and the Tutor offered to share resources for setting up a Python development environment.
Variables
Data Types
Basic Arithmetic Operators
The Print Function
The Student and Tutor worked through complex Excel formulas, focusing on dynamic data analysis using functions like FILTER, XLOOKUP, and IF.ERROR. They practiced building flexible models with checkboxes for scenario planning and discussed best practices for creating reusable spreadsheet solutions, aiming to improve efficiency and reduce errors in future analyses. The next session will continue exploring these concepts.
VLOOKUP vs. XLOOKUP
Dynamic Array Functions (FILTER
ROWS)
Avoiding Hardcoding with Named Ranges and Cell References
Nesting Functions (IFERROR
SUM
CHOOSE.COLUMNS)
Understanding 'Spill' Errors
The tutor introduced a beginner student to Python programming, focusing on data cleaning techniques using a practical example. The student learned about identifying and resolving data inconsistencies, missing values, and formatting issues in a CSV file through a Python script, with plans to continue with further lessons.
What is "Dirty Data"?
Python for Data Cleaning: Core Operations
The Data Lifecycle: From Raw to Insight
The tutor guided the student through data consolidation and updating procedures using Excel within a reporting software. They practiced copying and pasting data, troubleshooting display issues with pivot tables, and refreshing data for accurate reporting, with a focus on ensuring data visibility and integrity.
Screen Sharing Best Practices
Excel: Identifying Open Files via Taskbar Indicators
Excel: Adjusting Decimal Places and Understanding Auto-Rounding
Excel: Unhiding Columns and Adjusting Column Widths
Excel: Using Data Filters and the 'Clear' Function
Excel: Copying and Pasting Data with Shortcuts
Excel: Refreshing Pivot Tables for Updated Data
Student and Tutor discussed strategies for organizing financial data in Google Sheets, including distinguishing between personal, work, and business expenses. They implemented an automated ID generation formula and refined the process for importing bank statement data from CSV files. Future sessions will focus on building automated data transformations using Power Query to streamline data entry from various bank sources.
Data Source Simplification & Single Source of Truth
Dynamic Unique ID Generation in Google Sheets
Optimizing Bank Statement Imports: CSV vs. PDF
Essential Data Transformations for Clean Imports
Introduction to Power Query for Automated Transformations
The Student and Tutor worked on enhancing an expense tracking system in Google Sheets. They implemented advanced `FILTER` and `CHOOSECOLS` functions to create a dynamic "Refund Status" sheet and extensively debugged a Google Apps Script to automate the updating and removal of paid refundable expenses. The Tutor shared an updated calendar link for planning future sessions.
Refining Dynamic Filters for Real-time Updates
Google Apps Script for Inter-Sheet Data Synchronization
Dynamic Data Extraction with Google Sheets Functions
Principles of Custom Financial Tracking
AI's Role and Limitations in Data Automation
Teaching tools used by data science tutor
Google Colab
Interactive data science classes
Note taking
Pets are welcomed
Open Q&A
Weekend lessons
Record lessons
Data Science tutors on Wiingy are vetted for quality
Every tutor is interviewed and selected for subject expertise and teaching skill.