Tuck | Mr. Consulting To Tech
GMAT 750, GPA 3.2
INSEAD | Ms. Hope & Goodwill
GMAT 740, GPA 3.5
Stanford GSB | Mr. MBB to PM
GRE 338, GPA 4.0
IU Kelley | Ms. Biracial Single Mommy
, GPA 2.5/3.67 Grad
Darden | Ms. Unicorn Healthcare Tech
GMAT 730, GPA 3.5
Stanford GSB | Mr. MBA Class of 2023
GMAT 725, GPA 3.5
Harvard | Mr. Sales To Consulting
GMAT 760, GPA 3.49
Chicago Booth | Mr. Guy From Taiwan
GRE 326, GPA 3.3
Stanford GSB | Mr. Energy Reform
GMAT 700, GPA 3.14 of 4
Stanford GSB | Mr. Systems Change
GMAT 730, GPA 4
Ross | Mr. Verbal Engineer
GMAT 710, GPA 3.3
INSEAD | Mr. Airline Captain
GMAT 740, GPA 3.8
UCLA Anderson | Ms. Packaging Manager
GMAT 730, GPA 3.47
Kellogg | Mr. Danish Raised, US Based
GMAT 710, GPA 10.6 out of 12
Stanford GSB | Mr. Navy Officer
GMAT 770, GPA 4.0
Wharton | Mr. Sr. Systems Engineer
GRE 1280, GPA 3.3
Chicago Booth | Mr. Semiconductor Guy
GMAT 730, GPA 3.3
Harvard | Mr. Polyglot
GMAT 740, GPA 3.65
Duke Fuqua | Mr. Enlisted Undergrad
GRE 315, GPA 3.75
Stanford GSB | Mr. Rocket Scientist Lawyer
GMAT 730, GPA 3.65 Cumulative
Darden | Mr. Stock Up
GMAT 700, GPA 3.3
Stanford GSB | Mr. Classic Candidate
GMAT 760, GPA 3.9
Cambridge Judge Business School | Mr. Social Scientist
GRE 330, GPA 3.5
Darden | Mr. Federal Consultant
GMAT 780, GPA 3.26
INSEAD | Mr. Consulting Fin
GMAT 730, GPA 4.0
Harvard | Mr. Milk Before Cereals
GMAT 710, GPA 3.3 (16/20 Portuguese scale)
Darden | Mr. Leading Petty Officer
GRE (MCAT) 501, GPA 4.0

November’s Essential Business MOOCs


The IBM 360

Watching Mad Men, you’d guess that great advertising starts with all-nighters, where creatives dredge their aspirations and disappointments for moments of clarity. Sure, the Don Drapers and Peggy Olsons could draw from studies and focus groups. But how often have you seen these characters actually read them? In advertising’s golden age, the final product was seemingly more art than science, an outlet for would-be novelists and painters to romanticize the trappings of Lucky Strikes and Jaguars.

Maybe that’s why the cast was so terrified of the IBM 360 this past season. They could see the future, where placement and message would be driven by constellations formed by billions of data bits. These days, they call it big data…and it has become big business. Take some data sets, slice-and-dice them according to various models, and voila! Suddenly, you can identify patterns and trends – if you know how to decipher them, that is. Yes, science can deliver data any way you want. But asking questions, interpreting results, and formulating strategies to capitalize on findings…well, that’s still an art.

Data mining

Alas, you can’t teach imagination and ingenuity. But you can sure transmit the basics and how (and where) to apply them. This month, you’ll find a series of big data-themed MOOCs. To learn the basics, you can enroll in the University of Texas’ “Foundations of Data Analysis,” which provides an undergraduate grounding in statistics coupled with modeling basics. From there, the Eindhoven University of Technology takes it a step further with “Process Mining: Data Science in Action,” taught by Wil van der Aalst, one of the most cited scholars in information technology. And if you’re wondering where to apply this information, consider taking “An Introduction to Consumer Neuroscience and Neuromarketing.” This multi-disciplinary course focuses on how the consumer brain works – and what drives purchasing decisions.

Looking to launch a business? Consider the first part of the University of Rochester’s “Technology Commercialization: Setting Up Your Idea Filtering System,” designed to help would-be entrepreneurs avoid the pitfalls inherent to startups requiring longer incubation. If you’re drawn to social enterprise, take a look at “Financial Sustainability: The Numbers Side of the Enterprise,” where you’ll learn the accounting side of scaling your operation. And if you’re wondering if you should even start a business, check out Jeroen van den Hoven’s “Responsible Innovation,” which explores the disruptive side of progress – and how entrepreneurs can ease the worst effects of innovation.

Want to learn more about these courses – and many more? Click on the links below, where you can also enroll in these courses.

Technology Commercialization, Part 1: Setting up your Idea Filtering System / University of Rochester / November 1

Analyzing Global Trends for Business and Society / Wharton / November 3

Process Mining: Data Science in Action / Eindhoven University of Technology / November 12

Business and Its Environment: An Overview of Business and the Role of Finance in Business / Open Education Consortium / November 17

Common Sense Economics for Life / Florida State University and Northern Michigan University / November 3

Designing and Connecting Your Career / University of California-Irvine / November 3

Introduction to Strategic Thinking / November 3

Foundations of Data Analysis / University of Texas-Austin / November 4

Financing New Ventures / University of California-San Francisco / November 4

How to Succeed at Interviews / University of Sheffield / November 4

Responsible Innovation / DelftX / November

Inspiring Leadership Through Emotional Intelligence / Case Western University / November 3

An Introduction to Consumer Neuroscience and Neuromarketing / Copenhagen Business School / November 10

Financial Sustainability: The Numbers Side of the Enterprise / +Acumen / November 18

Introduction to Public Speaking: Improptu Speaking / University of Washington / November 17

Additional Courses