Top-rated Data Science tutor in Canada
Data science turns raw numbers into real insight, and an online data science tutor shows you how. Lessons cover Python, pandas, statistics, and the basics of machine learning, using real datasets and building on school stats like Ontario's MDM4U. It is one of Canada's most in-demand skills, useful for students, analysts, and career changers. You learn hands-on over video, building projects you can add to a portfolio.
Free Trial
15-days refund
Free tutor swap
No cancel fee
Summary
Podcast
We match you with best tutors for your requirements
Data science taught through tutor-led classes
Learners attend in Toronto, Edmonton, Calgary
Yeriko taught 2 days ago
The Student and Tutor worked through a statistics homework assignment using R programming, focusing on data manipulation, descriptive statistics, and visualization techniques. They covered topics including variable transformation, calculating central tendencies and dispersion, interpreting skewness and z-scores, and analyzing categorical data. The Tutor will provide a detailed R script with comments and a Word document of answers for the Student to review and complete.
R Studio Environment & Data Import
Data Preparation: Missing Values & Variable Transformation
Descriptive Statistics & Data Visualization
Z-scores & Data Normalization
Population vs. Sample Measures (Variance & Standard Deviation)
Categorical Data Analysis: Frequency & Group Means
Yeriko taught 10 days ago
The session was a demo lesson focused on R Studio programming for an undergraduate Economics course (Econ 221). The Student sought help with a homework assignment involving data analysis concepts such as identifying missing values, understanding variables, constructing new variables, analyzing relationships, and calculating probabilities. The Tutor explained these concepts in detail, relating them to economics and discussing a plan to work through the homework questions and prepare for an upcoming midterm.
Handling Missing Values (NA
NaN) in R
Understanding Data Variables and Structures
Feature Engineering: Creating New Variables
Analyzing Relationships Between Variables
Grouping Data for Comparative Analysis
Introduction to Probability Concepts in Data
Steven taught about 1 month ago
The Student and Tutor reviewed the XLOOKUP function, including optional parameters, nested lookups, and order of operations in complex formulas. They also discussed absolute vs. relative cell references, data cleaning with 'Text to Columns', and strategies for reconciliation in Excel, including potential pitfalls and the use of the COUNTIF function. The Student received intermediate and advanced XLOOKUP practice files and plans to gain hands-on experience with reconciliation data at their new job to inform future lessons.
XLOOKUP Function Fundamentals
Nested XLOOKUPs for Multi-Step Retrieval
Excel's Order of Operations
Absolute and Relative Cell References
Data Cleaning: Text to Columns
Reconciliation Strategies & Avoiding False Positives
Introduction to Excel Automation & VBA
Nikita taught about 2 months ago
The Student and Tutor worked on refining an Excel workbook designed for tracking real estate commissions. They focused on updating and verifying commission data, refreshing pivot tables and charts to reflect the changes, and adjusting page breaks to optimize the print layout. The next session will involve integrating new commission data once it becomes available.
Excel Data Entry & Formula Management
Dynamic Data Visualization: Refreshing Pivot Tables and Charts
Optimizing Print Layouts with Page Breaks
Data Verification & Reconciliation with External Sources
Nikita taught about 2 months ago
The student and tutor worked on automating Excel formulas for commission tracking. They focused on updating `SUMIF` functions and cell ranges within Excel tables to ensure dynamic calculations for agent commissions and total payouts, with plans to verify accuracy once brokerage data is received.
Formula Automation in Spreadsheets
Data Validation and Accuracy Checks
Understanding Collapsed Deals in Sales Tracking
Spreadsheet Table Designations and Row Numbering
Nikita taught 2 months ago
The student and tutor focused on implementing and troubleshooting Excel formulas to automate deal counts and total commission calculations across multiple tables. They practiced applying dynamic formulas, correcting syntax errors, and understanding the difference between automated and manual data entry for financial reporting.
Automating Table Calculations
Dynamic Formula Referencing
Handling Column Name Inconsistencies in Formulas
Manual vs. Automated Data Entry
