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14,604 learning development interview questions shared by candidates

General qualification Q&A, scenario based examples, request of my prior material examples, and a request to build a 5 minute elearning example to demonstrate my abilities. This took about 5 days to complete as I provided two different types of interactive courses. They really liked my work, and moved me to an in person interview. I was asked about my tenure, my past management positions, and explain my ideal working conditions, along with how I would over come obstacles.
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E-learning Specialist

Interviewed at First Tech Federal Credit Union

3.3★
Apr 27, 2017

General qualification Q&A, scenario based examples, request of my prior material examples, and a request to build a 5 minute elearning example to demonstrate my abilities. This took about 5 days to complete as I provided two different types of interactive courses. They really liked my work, and moved me to an in person interview. I was asked about my tenure, my past management positions, and explain my ideal working conditions, along with how I would over come obstacles.

Random Walk Distances On Graphs Given a graph and any pair of vertices i and j, it is possible to take a random walk starting from i and eventually arrive at j, if i is connected to j. Specifically, starting at i, each time we choose an edge to traverse randomly according to some probability distribution P, and repeat until we arrive at j for the first time. The number of edges traversed is a random variable with some expected value, which is the expected random walk distance from i to j. By this definition, the expected random walk distance from a vertex to itself is always 0. Furthermore, multiple traversals of an edge are also counted in the random walk distance. Your task is to write a program to estimate the expected random walk distance between all pairs of vertices in a given graph.
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Machine Learning Engineer

Interviewed at RBC

3.9★
Jul 5, 2017

Random Walk Distances On Graphs Given a graph and any pair of vertices i and j, it is possible to take a random walk starting from i and eventually arrive at j, if i is connected to j. Specifically, starting at i, each time we choose an edge to traverse randomly according to some probability distribution P, and repeat until we arrive at j for the first time. The number of edges traversed is a random variable with some expected value, which is the expected random walk distance from i to j. By this definition, the expected random walk distance from a vertex to itself is always 0. Furthermore, multiple traversals of an edge are also counted in the random walk distance. Your task is to write a program to estimate the expected random walk distance between all pairs of vertices in a given graph.

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