Engineering research generates enormous datasets, and Jared's PhD work at Lehigh means he lives in Excel — building formulas, using VLOOKUP and pivot tables to organize experimental data, and creating charts that communicate results clearly. He teaches students and professionals to move past basic spreadsheet use into the functions and formatting that make Excel genuinely powerful.

Most people use about ten percent of what Excel can do. Matthew's quantitative background in math and CS means he digs into the powerful side — pivot tables, VLOOKUP versus INDEX/MATCH, conditional formatting rules, and basic VBA automation — turning spreadsheets from data dumps into actual analytical tools.

Most people use about 10% of what Excel can do. Rhamy unpacks the features that actually save time — VLOOKUP, pivot tables, conditional formatting, and basic macros — tailoring each session to whether a student needs Excel for a class project, a business case, or data cleanup.

Mica's Science, Technology, and Society degree at Stanford meant constant data wrangling — organizing research datasets, running analyses, and presenting findings in structured formats. She brings that academic rigor to Excel sessions, tackling everything from formula logic and data cleanup to building spreadsheets that actually answer a research question. Rated 5.0 by students.

Excel is one of those tools that's easy to use at a surface level but transformative once you learn what's under the hood. Seong teaches practical skills like VLOOKUP, pivot tables, conditional formatting, and data visualization — the functions that turn a messy spreadsheet into something useful. Her experience organizing research data in Northwestern's neuroscience program means she approaches Excel as a problem-solving tool, not just a grid of cells.

Most people learn Excel by Googling one formula at a time, which leaves huge gaps in how they think about spreadsheets. Brian tackles Excel systematically — VLOOKUP vs. INDEX/MATCH, pivot tables, conditional formatting, and building financial models — drawing on the quantitative modeling he did throughout his Economics and CS studies at Caltech.

Engineering coursework at Duke means Eric lives in spreadsheets — building data models, running regression analyses, and automating repetitive calculations with formulas like VLOOKUP, INDEX-MATCH, and conditional arrays. He teaches Excel as a problem-solving tool rather than a grid of cells, walking students through pivot tables, data visualization, and the logic behind nested functions.

Computational science at MIT requires wrangling large datasets, and Excel is often the first tool Tim reaches for when cleaning, sorting, and visualizing data before moving to heavier platforms. He covers formulas, pivot tables, VLOOKUP, and conditional formatting with an emphasis on building spreadsheets that are organized and repeatable. Students leave sessions with files they can actually reuse, not just notes about menu locations.

Between research data and engineering coursework, Annie lives in spreadsheets — building formulas, creating pivot tables, and using VLOOKUP to organize large datasets from her cancer immunotherapy lab. She walks students through Excel's logic step by step, whether they need to learn basic cell references or more advanced tools like conditional formatting and data visualization.

Economics at Brown means living inside spreadsheets — building regression models, cleaning datasets, and automating repetitive calculations with VLOOKUP, pivot tables, and conditional formatting. Clive teaches Excel as a practical tool for solving real problems, walking through formulas and data visualization techniques that students can immediately apply to coursework or projects.

Engineering research generates enormous datasets, and Jared's PhD work at Lehigh means he lives in Excel — building formulas, using VLOOKUP and pivot tables to organize experimental data, and creating charts that communicate results clearly. He teaches students and professionals to move past basic spreadsheet use into the functions and formatting that make Excel genuinely powerful.

Most people use about ten percent of what Excel can do. Matthew's quantitative background in math and CS means he digs into the powerful side — pivot tables, VLOOKUP versus INDEX/MATCH, conditional formatting rules, and basic VBA automation — turning spreadsheets from data dumps into actual analytical tools.

Most people use about 10% of what Excel can do. Rhamy unpacks the features that actually save time — VLOOKUP, pivot tables, conditional formatting, and basic macros — tailoring each session to whether a student needs Excel for a class project, a business case, or data cleanup.

Mica's Science, Technology, and Society degree at Stanford meant constant data wrangling — organizing research datasets, running analyses, and presenting findings in structured formats. She brings that academic rigor to Excel sessions, tackling everything from formula logic and data cleanup to building spreadsheets that actually answer a research question. Rated 5.0 by students.

Excel is one of those tools that's easy to use at a surface level but transformative once you learn what's under the hood. Seong teaches practical skills like VLOOKUP, pivot tables, conditional formatting, and data visualization — the functions that turn a messy spreadsheet into something useful. Her experience organizing research data in Northwestern's neuroscience program means she approaches Excel as a problem-solving tool, not just a grid of cells.

Most people learn Excel by Googling one formula at a time, which leaves huge gaps in how they think about spreadsheets. Brian tackles Excel systematically — VLOOKUP vs. INDEX/MATCH, pivot tables, conditional formatting, and building financial models — drawing on the quantitative modeling he did throughout his Economics and CS studies at Caltech.

Engineering coursework at Duke means Eric lives in spreadsheets — building data models, running regression analyses, and automating repetitive calculations with formulas like VLOOKUP, INDEX-MATCH, and conditional arrays. He teaches Excel as a problem-solving tool rather than a grid of cells, walking students through pivot tables, data visualization, and the logic behind nested functions.

Computational science at MIT requires wrangling large datasets, and Excel is often the first tool Tim reaches for when cleaning, sorting, and visualizing data before moving to heavier platforms. He covers formulas, pivot tables, VLOOKUP, and conditional formatting with an emphasis on building spreadsheets that are organized and repeatable. Students leave sessions with files they can actually reuse, not just notes about menu locations.

Between research data and engineering coursework, Annie lives in spreadsheets — building formulas, creating pivot tables, and using VLOOKUP to organize large datasets from her cancer immunotherapy lab. She walks students through Excel's logic step by step, whether they need to learn basic cell references or more advanced tools like conditional formatting and data visualization.

Economics at Brown means living inside spreadsheets — building regression models, cleaning datasets, and automating repetitive calculations with VLOOKUP, pivot tables, and conditional formatting. Clive teaches Excel as a practical tool for solving real problems, walking through formulas and data visualization techniques that students can immediately apply to coursework or projects.