What Should I Always Be Learning?
summary
Advocates adopting an always-be-learning stance and gives concrete targets: contribute to open source on GitHub and build a visible portfolio; treat code as data first because companies process petabytes now and some projects plan for exabytes; learn tooling like Docker, Kubernetes, Apache Kafka, Spark, Hadoop, TensorFlow and languages Go, Python or Rust; study OWASP top ten proactive controls for security; expect continuous everything and that machine learning will create technical debt to be refactored later.
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chapters (7)
- 0:00Start
- 2:20What Can a Developer or an Engineer Do To Set Themselves Up for Success for the Next Three to Five Years
- 4:02Six Trends That Are Happening Right Now
- 4:59Industry Trends
- 12:22Teamwork
- 18:02Where To Start Start Learning about Machine Learning
- 21:39Resources
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