Building a career in Data Science

Emily Robinson, co-author of the book Build a Career in Data Science, gives us the inside scoop about optimizing the data science job search. From creating one’s resume, cover letter, and portfolio to knowing how to recognize the right job at a fair compensation rate.

Emily’s expert guidance takes us from the beginning of the process to conclusion, including being successful during your early days in that fantastic new data science position.

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Featuring:

• Emily Robinson – GitHub, X
• Chris Benson – Website, GitHub, LinkedIn, X
• Daniel Whitenack – Website, GitHub, X

Show Notes:

Comment on the episode page for a chance to win a FREE copy of the eBook! Tell us why you are interested in Data Science and how this book might help you achieve your goals. Our 3 favorite comments will be selected on April 13th!

• R Conference | New York City

Books

• “Build a Career in Data Science” by Emily Robinson and Jacqueline Nolis
  • Be sure to use discount code: podpracticalAI19
• “Cracking the Coding Interview” by Gayle Laakmann McDowell
• “Designing Your New Work Life” by Bill Burnett and Dave Evans
• “Designing Your Life” by Bill Burnett and Dave Evans

Something missing or broken? PRs welcome!

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Creators & Guests

Host

Chris Benson

Host

Daniel Whitenack

Guest

Emily Robinson

What is Practical AI?

Making artificial intelligence practical, productive & accessible to everyone. Practical AI is a show in which technology professionals, business people, students, enthusiasts, and expert guests engage in lively discussions about Artificial Intelligence and related topics (Machine Learning, Deep Learning, Neural Networks, GANs, MLOps, AIOps, LLMs & more).

The focus is on productive implementations and real-world scenarios that are accessible to everyone. If you want to keep up with the latest advances in AI, while keeping one foot in the real world, then this is the show for you!