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
/ 55 min
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.
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15-days refund
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1-yr validity
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Learner types for data science class
Data Science for intermediate
Data Science for beginners
Data Science for adults
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.
Data Science concepts taught by Rithika
The session focused on a detailed review and practice of adding fractions, with a strong emphasis on finding the lowest common multiple (LCM) for denominators. The Student worked through various examples, both guided and independently, to solidify their understanding of fraction conversion and addition. Homework was assigned, consisting of several worksheets covering both fraction addition and an introduction to fraction subtraction.
Finding the Lowest Common Multiple (LCM)
Converting Improper Fractions to Mixed Numbers
Adding Fractions with Unlike Denominators
The tutor and student worked on applying algebraic expressions to solve word problems involving discounts and multi-step calculations. They also practiced decimal division and fraction subtraction, with the tutor providing targeted instruction and exercises to reinforce these mathematical skills.
Subtracting Fractions with Unlike Denominators
Solving Word Problems with Discounts and Multiple Items
Calculating Unit Price for Word Problems
The Student and Tutor reviewed fundamental mathematical concepts including algebra, Bedmas (order of operations), and rounding large numbers. The Student practiced solving various problems in each area, reinforcing the application of inverse operations and rounding rules. The Tutor assigned additional worksheets on related topics as homework, encouraging the Student to bring any questions to the next class.
Algebraic Equations: Opposite Operations
BEDMAS: Order of Operations
Rounding Whole Numbers to Place Values
The Student and Tutor conducted an initial assessment of the Student's grade 5 math skills using a comprehensive review package. They identified the Student's strengths in multiplication and basic fraction operations, alongside areas for development such as three-digit multiplication, BEDMAS, exponents, algebra, decimals, prime numbers, rounding, and subtracting fractions. The Tutor will assign a basic arithmetic homework packet and plans to use interactive tools like Cahoots for future concept reviews.
Multi-Digit Multiplication
Order of Operations (BEDMAS)
Divisibility and Prime Numbers
Decimal Comparison and Place Value
Fraction Operations
The tutor and student reviewed statistical concepts including the impact of transformations (addition, subtraction, multiplication, division) on measures of central tendency and spread. They then practiced probability calculations using Venn diagrams and explored real-world applications of these concepts, such as analyzing potential biases in self-reported data.
Impact of Data Transformations on Measures of Center and Spread
Probability of Events and Set Operations
Z-Scores and Their Invariance Under Linear Transformations
The tutor and student worked through problems related to statistical distributions, focusing on the application of the Empirical Rule and Z-scores for normal distributions. They practiced calculating standard deviations, determining data ranges, and approximating percentages, and discussed the limitations of the Empirical Rule when a distribution is not normal.
Interpreting Histograms
Normal Distribution Properties
Z-Scores and Z-Tables
The Empirical Rule
Teaching tools used by data science tutor
Google Colab
Jupyter Notebook
Interactive data science classes
Mobile joining
Chat for quick help
Weekend lessons
Note taking
Parent feedback
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Every tutor is interviewed and selected for subject expertise and teaching skill.