After a couple of weeks of introspection, brainstorming and prioritizing, I’ve come up with a set of professional and personal goals that I want to achieve in the coming year. I feel that posting goals publicly is one of the simplest ways to keep myself honest.

Learning

1. Consume 4 academic texts

Having graduated about a year ago, I realized that my appetite for steep-learning curves dropped drastically. I also missed the rigor that an academic environment demands. I also immensely value the “dive deep” aspect of learning a new concept or technology.

One of the important aspects of this goal is consume; the focus here is to process, digest and assimilate the content of the textbook. Working through the exercises, recommended reading, and the like hold more weight that the quantity of content.

I’ve picked the number 4 deliberately, since this is approximately the same workload as a quarter-based part-time (professional) Master’s degree would require.

A tentative list is

  1. Deep Learning by Ian Goodfellow, Yoshua Bengio, Aaron Courville
  2. TBD Text on Quantum Computing
  3. TBD Text on Advanced Algorithms
  4. TBD

Projects

1. Interview Preparation Toolkit

I typically mentor about 1-2 students throughout the year, w.r.t. projects, job applications and interview preparation. A recurring problem that has surfaced in this process is that good interview problems are either

  1. locked behind a subscription/paywall (LeetCode)
  2. don’t have an automated test set (CareerCup)

The core idea behind this project is to address both of those problem areas. A rough set of requirements is:

  1. A small set of dependencies that will be easily available on any platform
  2. A fuzzy-test generator to generate a variety of test cases for a given problem
  3. A human-readable input-output format.
  4. A curated set of problems
  5. A simple and minimalistic CLI for validating solutions.
  6. [Optional] Big-O analysis of solutions

2. SQL Stories

Another frequent problem that often pops up, particularly during preparing for data-scientist-ish roles is a surprising lack of good SQL resources. Most notable is the lack of a diverse set of data sets, along with a set of genuine, organic and non-contrived questions that you’d want to ask of the dataset.

(Not to mention, I’m pretty tired of dealing with the standard “school”, “library” and “flights” schemas)

The goal is to come up with a couple of curated data sets, accompanied by increasingly difficult/categorized questions.

Fitness

These are a fairly short set of goals, easily quantifiable and trackable:

  1. 75 consecutive pushups
  2. work out at least 4/7 days
  3. run a 10-minute mile

Miscellaneous

  1. Read at least 30 books (with ~5 non-fiction)
  2. Write a review for at least 8 books
  3. Write a review for at least 8 board games
  4. Publish 12 technical articles/posts (learning lists don’t count)

Overall Time Commitments

Item Time (in hours per week)
Work 40
Sleep 56
Consume 4 Academic Texts 5
Interview Preparation Toolkit 3
SQL Stories 1
Fitness 10
Buffer 56
Total 168