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Machine Learning Guide

MLG 006 Certificates & Degrees

16 min • 17 februari 2017

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Full notes at ocdevel.com/mlg/6

Pursuing Machine Learning:
  • Individuals may engage with machine learning for self-education, as a hobby, or to enter the industry professionally.
  • Use a combination of resources, including podcasts, online courses, and textbooks, for a comprehensive self-learning plan.
Online Courses (MOOCs):
  • MOOCs, or Massive Open Online Courses, offer accessible education.
  • Key platforms: Coursera and Udacity. Coursera is noted for standalone courses; Udacity offers structured nanodegrees.
  • Udacity nanodegrees include video content, mentoring, projects, and peer interaction, priced at $200/month.
Industry Recognition:
  • Udacity nanodegrees are currently not widely recognized or respected by employers.
  • Emphasize building a robust portfolio of independent projects to augment qualifications in the field.
Advanced Degrees:
  • Master’s Degrees:
  • Valued by employers, provide an edge in job applications.
  • Example: Georgia Tech's OMSCS (Online Master’s of Science in Computer Science) offers a cost-effective ($7,000) online master’s program.
  • PhD Programs:
  • Embark on a PhD for in-depth research in AI rather than industry entry. Program usually pays around $30,000/year.
  • Compare industry roles (higher pay, practical applications) vs. academic research (lower pay, exploration of fundamental questions).
Career Path Decisions:
  • Prioritize building a substantial portfolio of projects to bypass formal degree requirements and break into industry positions.
  • Consider enriching your qualifications with a master's degree, or eventually pursue a PhD if deeply interested in pioneering AI research.
Discussion and Further Reading:
  • See online discussions about degrees/certifications: 1 2 3 4
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