Rithika Rushendra
Excel doesn’t have to be hard! I’ll help you master it one skill at a time through hands-on learning and open discussion!
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Rithika Rushendra
Bachelors degree
Enroll after the free trial
Each lesson is 55 min
50 lessons
20% off
/ lesson
30 lessons
15% off
/ lesson
20 lessons
10% off
/ lesson
10 lessons
5% off
/ lesson
5 lessons
-
/ lesson
1 lessons
-
/ lesson
About your data science tutor
Hi, I’m Rithika Rushendra! I’m a 4th-year Computer Science student at Ontario Tech University, specializing in Data Science. Over the past decade, I’ve had the privilege of teaching a wide range of subjects including Mathematics, English, Coding, and Microsoft Office tools, helping learners of all ages develop their skills and confidence. My expertise lies particularly in Math, Coding, and Excel, which I actively use in my academic and professional projects. I’ve also participated in numerous workshops, certifications, and training sessions to continuously refine my teaching methods and stay current with evolving technology and educational practices. In my lessons, I emphasize hands-on learning and experimentation, encouraging students to explore through trial and error rather than rote memorization. I believe that understanding comes from doing, so my sessions often include interactive exercises, real-world problem-solving, and guided practice to strengthen conceptual understanding. I design personalized study plans that align with each student’s goals and learning style. Whether you’re looking to improve grades, master a new skill, or build confidence in technical subjects, I’m committed to helping you reach your goals with patience, structure, and encouragement.
Data Science tutor skills
Assignment help
Learner types for data science class
Data Science for adults
Data Science for intermediate
Data Science for beginners
Data Science for kids
Data sciece class overview
My tutoring approach is rooted in fostering deep conceptual understanding through hands-on projects, interactive exercises, and real-world applications. I focus on developing not just technical proficiency but also problem-solving confidence, especially in Excel, Data Science, and data visualization techniques. Each session is personalized to the learner’s level and goals. I integrate a blend of online and offline learning tools such as Google Sheets, Excel, Slack, and Zoom, ensuring every lesson is dynamic, collaborative, and easy to follow. This approach helps students not only grasp abstract concepts but also apply them effectively in academic, personal, or professional contexts. By combining individualized attention, clear explanations, and consistent feedback, I’ve successfully guided over 50 students to strengthen their analytical thinking and master complex data concepts with confidence. My goal is to make learning both engaging and empowering, so every student walks away with lasting skills and curiosity to keep exploring.
Improved problem-solving skills
92% of students report faster problem-solving after lessons.
Debugging and problem-solving focus
85% of students improve debugging skills.
Highly rated for problem-solving approach
95% of students improve problem-solving skills and speed.
Flexible Scheduling
Allows 1h early scheduling
Allows 1h early rescheduling
Can wait for 20 mins after joining

10 day Refund
Free Tutor Swap

Data Science concepts taught by Rithika
The student practiced identifying place values and rounding numbers to the nearest ten and hundred. They also worked on converting numbers between standard and expanded form. The session included a brief introduction to French greetings and a plan to learn Spanish phrases in the future.
Place Value
Rounding to the Nearest Ten
Standard Form to Expanded Form
Expanded Form to Standard Form
The Student and Tutor worked through multiple-choice questions covering regression analysis and statistical interpretation. They focused on applying formulas to calculate predicted values and understanding the impact of data transformations on regression lines. The Tutor assigned homework to practice for the next session, where they will review the new unit with the correct formulas.
Least Squares Regression Line
Unit Conversion in Regression Analysis
Impact of Outliers on Regression Line
Logarithmic Transformations in Regression
Observational Studies and Regression Models
The Tutor and Student worked through problems involving linear equations and their application in real-world scenarios, specifically modeling car prices. They practiced deriving algebraic expressions, calculating intercepts for graphing, and determining lines of best fit from data points. The session concluded with comparing different linear models and discussing their limitations.
Formulating Linear Expressions
Graphing Linear Equations
Line of Best Fit
Interpreting Linear Models
The Tutor and Student worked on double-digit subtraction problems. The Student practiced applying borrowing techniques to solve various subtraction equations, showing marked improvement throughout the session. The plan is to continue focusing on subtraction for mastery before moving to multiplication next week.
Double-Digit Subtraction
Understanding Place Value in Subtraction
Checking Your Work in Subtraction
The Student and Tutor worked through problems related to calculating standard deviation manually from dot plots and data sets. They practiced calculating mean, median, IQR, and standard deviation, and discussed how these measures change when data values are added or removed from a set. The session concluded with a brief review of Mean Absolute Deviation.
Mean
Median
Standard Deviation
Interquartile Range (IQR)
Impact of Data Changes on Mean and Standard Deviation
The Student and Tutor worked through a review packet for an upcoming test, covering various statistical concepts. They practiced identifying variable types, describing data distributions from graphs, and applying rules like the empirical rule for standard deviation. The Tutor also guided the Student through calculating z-scores and determining percentiles.
Interpreting Histograms and Box Plots
Normal Distribution and Standard Deviation
Discrete vs. Continuous Variables
Quantitative vs. Categorical Variables
Teaching tools used by data science tutor
Google Colab
Jupyter Notebook
Interactive data science classes
Weekend lessons
Pets are welcomed
Note taking
Mobile joining
Chat for quick help

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Every tutor is interviewed and selected for subject expertise and teaching skill.
