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April 2, 2024 48 mins

This episode features Dr. Andrea Isoni, an expert in AI and data sciences. The conversation focuses on the journey to becoming a machine learning engineer or data scientist without a degree. The interview covers topics such as understanding Linux and the command line, learning programming languages, using frameworks like Django, and collaborating with others using Git/GitHub.

Andrea also shares insights on finding the right internships and job opportunities, staying competitive in the field, and building a strong CV.

On the topic of boot camps, Andrea cautions against believing in boot camps that promise quick results and high-paying jobs, highlighting the competitive and saturated job market. He suggests researching boot camps and online courses thoroughly, considering reviews, and talking to others who have gone through them.

Finally, He encourages perseverance and dedication for those looking to break into the field without a college degree, acknowledging that it is a challenging but possible journey.

Key points discussed:

  • Becoming a machine learning engineer or data scientist without a degree is a multi-year journey that requires dedication and continuous learning.
  • Fundamental knowledge of Linux, the command line, programming languages, and frameworks like Django is essential for success in the field.
  • Collaboration and self-motivation are key to overcoming challenges and staying competitive in the industry.
  • Building a strong CV through internships, certifications, and personal projects is crucial for career advancement.
  • Regular self-evaluation and setting realistic expectations are important for maintaining motivation and progress. Finding the right learning resources is crucial for success in AI and machine learning.
  • Be cautious of boot camps that promise quick results and high-paying jobs.
  • Thoroughly research boot camps and online courses, considering reviews, and talking to others who have gone through them.
  • Breaking into the field without a college degree is possible but requires dedication and hard


  • 00:00 Introduction and Background
  • 02:24 Starting with Linux and Programming
  • 05:20 Understanding Front-end and Back-end Development
  • 07:39 Learning Object-Oriented Programming and Git
  • 10:03 Getting Comfortable with Programming
  • 13:24 Qualifying for Internships or Software Testing Positions
  • 15:48 Maximizing the Internship Experience
  • 23:20 Staying Competitive in the Field
  • 29:39 Experimenting with AI Tools and Competitions
  • 34:41 Judging Progress and Evaluating Skills
  • 38:04 Continuing to Learn and Stay Competitive
  • 46:45 Final Thoughts and Recommendations
  • 47:14 Conclusion and Sponsorship

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Books and resources mentioned in this podcast:


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