Tuck | Mr. Risk Manager
GMAT 750, GPA 7.1/10
Harvard | Mr. PE Strategist
GRE 326, GPA 3.6
Harvard | Mr. Student Product Manager
GMAT 760, GPA 3.4
London Business School | Ms. FANG Tech
GRE 321, GPA 3.7
Chicago Booth | Mr. Corporate Development
GMAT 740, GPA 3.2
Cornell Johnson | Mr. Sports Management
GMAT 690, GPA 3.23
Wharton | Mr. Private Equity Analyst
GRE 320, GPA 3.3
Columbia | Mr. CPA
GMAT 720, GPA 3.5
Wharton | Mr. Digital Health Start-Up
GMAT 710, GPA 3.3
Darden | Mr. International Trade
GRE 323, GPA 3.6
Harvard | Mr. Health Clinic Founder
GRE 330, GPA 3
Said Business School | Mr. Strategy Consulting Future
GMAT 720, GPA 3.98
Stanford GSB | Mr. Robotics
GMAT 730, GPA 2.9
Stanford GSB | Mr. Aspiring Tech Entrepreneur
GMAT 690, GPA 3.4
London Business School | Mr. Supply Chain Latino
GRE 320, GPA 3.4
Duke Fuqua | Mr. Operations Manager
GRE 328, GPA 3.1
Harvard | Ms. Media Entertainment
GMAT 740, GPA 3.3
GMAT 770, GPA 3.7
Wharton | Mr. Basketball To B-School
GRE 334, GPA 3.73
Harvard | Mr. E-Sports Coach
GRE 323, GPA 5.72/10
INSEAD | Ms. Insightful Panda
GMAT 700, GPA 87.5%
NYU Stern | Mr. Bioinformatics
GMAT 710, GPA 3.7
Harvard | Mr. Impact Investment
GMAT 760, GPA 3.2
Chicago Booth | Mr. Nonprofit-ish
GRE 333, GPA 3.81
INSEAD | Ms. Humble Auditor
GMAT 710, GPA 3.56
London Business School | Mr. Investment Finance
GMAT 750, GPA 2.2
Georgetown McDonough | Ms. Healthcare Tech
GMAT 680, GPA 3.2

Essential Business MOOCs for September

Networked Life


School: University of Pennsylvania

Platform: Coursera

Registration Link: Networked Life

Start Date: September 1, 2014 (7 Weeks)

Workload: 1-3 Hours Per Week

Instructor: Michael Kearns

Credentials: Professor Kearns specializes in the areas of game theory, artificial intelligence, computational finance, and social networking. A member of the university’s Computer and Information Science department, Kearns also teaches statistics and information management courses at the Wharton school. He is the founding director of the school’s Market and Social Systems Engineering program.

Graded: Students will receive a Statement of Accomplishment for successfully completing the course.

Description: Ever hear the term, “six degrees of separation?” It’s more than a cliché. In fact, it is a pattern based on a science that integrates computer science, mathematics, sociology and economics. In this course, students will study the structural properties underlying network patterns from various origins. In particular, this course will emphasize how data points scale, interact, and connect with each other to form a pattern – and the cumulative impact that these complex variables have on influence, behavior, and outcomes. Using case studies in areas like social networking, search engine algorithms, voting patterns, and global supply chains, students will learn how patterns emerge and evolve over time.

Review: “I had some prior experience with this (Model Thinking course), but still got useful information from this course. It is a great, compact course giving a good introduction to Networks. The lectures are interesting, but the best part is that all videos and quizzes are available from day 1, so if you have done some of this before, you can move through the course quickly at your own pace. I wish more courses would offer this method.” For additional reviews, click here.

Additional Note: Stanford University offers a similar course called Social and Economic Networks: Models and Analysis, which starts on September 21. To register, click here.