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Expert Top-rated Data Science tutor
Data science taught by trusted tutors in the USA
Data science tutoring with real-world context
Data science lessons delivered by USA tutors
Lessons delivered by professionals in Tucson, Fresno
Steven taught 7 days ago
The Tutor and Student collaborated on improving the salary validation and conversion features of a job application. They added a position type dropdown and refined the logic for hourly vs. annual rate inputs. The next step involves designing the interface and connecting job postings to candidate profiles, scheduled for a future session.
Input Validation
Conditional Validation
Data Conversion
Dropdown Implementation
Field Dependencies
Data Redundancy
Steven taught 8 days ago
The Student and Tutor refined an Excel-based candidate tracking tool by adding informational pop-ups, implementing data validation rules, and enhancing user interface elements. The work included creating default values for dropdown menus and ensuring consistent formatting. The next steps involve completing the add button functionality and further testing.
Adding Help Text (Tooltips)
Input Validation
Dropdown Defaults
Clear Button Functionality
User-Friendly Formatting
Steven taught 17 days ago
The Student and Tutor collaborated on building Excel charts to compare pre- and post-intervention dunning metrics for a client QBR, discussing how to present data effectively for different audiences. The student also learned about VLOOKUP and XLOOKUP functions and their use cases for combining data from different sources. The student will try to find more spreadsheets to work on and bring examples to the next session.
Annualization of Data
Data Storytelling
Relative Lift vs. Overall Lift
VLOOKUP Function
XLOOKUP Function
Data Translation
Efficient Spreadsheet Practices
Steven taught 20 days ago
The Tutor guided the Student in enhancing Excel forms for candidate and position management, focusing on dynamic dropdown menus and input validation. The Student learned to link dropdowns to Excel tables for easy customization and discussed logic for unique ID generation. The next session will focus on implementing the validation code and data insertion.
Input Box Naming Conventions
Dynamic Dropdown Population from Excel Tables
Dropdown Validation
Incrementing IDs for new entries
Adding new candidate workflow
Steven taught 21 days ago
The Student and Tutor analyzed spreadsheet data related to revenue recovery, focusing on restructuring data for better analysis and calculating key performance metrics. They discussed the importance of clear data presentation for clients and explored methods for demonstrating the value of the product. The Student was assigned to practice restructuring a new dataset in preparation for the next session and also clarify the term 'total direct' in the data set.
Data Structure for Analysis
Dunning Process and Revenue Recovery
Impact Assessment: Lift and Cumulative Lift
Simplifying Data Presentation
Understanding Baseline Revenue
Excel Formula Priority
Steven taught 22 days ago
The session addressed issues the Student was encountering with their property management tool in Excel, specifically concerning saving statements and updating data. The Tutor provided a new version of the tool, walked the Student through installation, data merging, and demonstrated new features. The Student learned how to directly modify expense and revenue data within the Excel tool and how to manage filters for accurate data viewing.
Setting the Default Save Path
Statement Preview Feature (Future)
Retaining Inputted Data in Log Forms
Understanding Back-End Data and its Relation to the Front-End
Accessing and Modifying Back-End Data
Filtering Data for Efficient Modification
Importing Data from Previous Versions
Data Science tutoring stats in the U.S.
Total Data Science tutors
312 Data Science tutors available
Expert Data Science tutors
82% hold a Bachelor’s degree
Data Science Industry experience
70% of tutors have worked in Data Science and Analytics
What to expect in data science
How to learn data science?
Data science is an interdisciplinary field that combines statistics, programming, and domain expertise to extract insights from data. Mastering data science can feel overwhelming due to its technical depth and vast applications. You might struggle with statistics, programming, and real-world problem-solving.
One major challenge you may face is understanding machine learning algorithms, data preprocessing, and statistical modeling. Studies show that 80% of a data scientist’s time is spent cleaning and preparing data, making it a crucial yet difficult skill to master.
Self-learning through online courses, books, and coding platforms can help you build foundational knowledge and cover theoretical concepts. However, a data science tutor can simplify technical topics, provide step-by-step explanations, and ensure hands-on practice with real-world datasets.
With data science expected to grow by 36% by 2031, acquiring the right skills is essential. Whether you’re debugging code, optimizing models, or working with large datasets, expert guidance accelerates your learning and ensures you gain practical knowledge for real-world projects.
Who should study from a data science tutor?
Struggling with complex algorithms
You may find it difficult to grasp advanced data science concepts, especially machine learning algorithms like decision trees, neural networks, and clustering. The mathematical foundations behind these topics can be complex, leading to confusion.
A data science tutor can break down these concepts into simple, digestible steps, provide real-world examples, and reinforce your learning through hands-on exercises.
Difficulty in debugging and coding efficiency
Writing optimized Python or R code, troubleshooting errors, and handling large datasets can be frustrating without proper guidance. Debugging issues, especially in large-scale projects, can take hours or even days.
A tutor helps you identify inefficiencies in your code, explains debugging techniques, and provides best practices to improve your coding workflow and accuracy.
Lack of real-world application experience
Transitioning from theoretical learning to solving practical problems can be challenging. Even after completing courses, you may struggle to apply your knowledge to real business cases or industry projects.
A data science tutor bridges this gap by offering guided projects, industry case studies, and personalized feedback to help you develop real-world problem-solving skills.
How to select the right data science tutor?
Educational Qualification
Look for data science tutors with a background in data science, statistics, or machine learning. If you’re an advanced learner, you’ll benefit from a tutor with industry experience.
Experience & Teaching Approach
A tutor with hands-on experience in AI, finance, or healthcare can help you gain practical insights.
Student Reviews & Testimonials
Choose private data science tutors with positive feedback from learners who have successfully transitioned into data science careers.
Affordability & Value
Data science tutors charge between $50 to $200 per hour, depending on experience and level of mentorship.
Finding the right data science tutoring can make a significant difference in your journey to mastering data science. Wiingy offers expert-vetted tutors at an affordable rate of $28 per session, ensuring high-quality learning at the best value. With structured guidance, personalized learning, and hands-on experience, you can develop the skills needed for a successful career in data science.
Frequently asked questions
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