CodeDotNet

My Self-Development in 2017

My corporate annual review period recently passed, and I was reminded of all the skills developed and completed tasks over the past year, both in and out of work. Sincerely, remembering what I've done over the past year makes me feel good, and really reminds me of how much I enjoy learning.

Video Courses

Although largely focused on reading to learn, I do partake of various streaming video resources via Pluralsight. The courses I've completed this past year:

Multiple courses on management and leadership

• Developer to Manager
• Technical Writing: Documentation on Software Projects

Quantitative & AI-related courses, accompanied by work in R, Python, or VBA

• Understanding Machine Learning
• Understanding Machine Learning with R
• Data Mining Algorithms in SSAS, Excel, and R
• Understanding and Applying Logistic Regression
• Understanding and Applying Factor Analysis and PCA
• Understanding and Applying Financial Risk Modeling Techniques

Books

Software Development

• Efficient R Programming: A Practical Guide to Smarter Programming
• Make Your Own Neural Network by Tariq Rashid
• Text Analysis with R for Students of Literature
• Complex Adaptive Systems: An Introduction to Computational Models of Social Life
• Exercises in Programming Style

Work and Periphery

• The Systems View of Life: A Unifying Vision
• Cultures and Organizations: Software of the Mind
• Radical Enlightenment: Philosophy and the Making of Modernity 1650-1750
• 100 Tricks to Appear Smart in Meetings: How to Get By Without Even Trying

Posts

To avoid repeating myself, here are My Most Popular Posts of 2017.

Review: Complex Adaptive Systems: An Introduction to Computational Models of Social Life

Complex Adaptive Systems: An Introduction to Computational Models of Social Life by John H. Miller
My rating: 4 of 5 stars

A thought-provoking introductory exploration to modeling social systems, covering ideas for rule-based agents within a variety of rule-based systems, moving onto evolutionary-like automata and organization of agents to solve problems. Underlying some of the ideas, one could see references to deeper concepts, e.g., nonlinearity, attractors, emergence, and complexity, none of which was explained explicitly. At times, I did find the writing tedious, as some ideas were too obvious to spend time detailing, but overall, a well-written easy to digest text.

View all my reviews