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Working in a hands-on learning environment, led by Data Science expert instructor, students will learn about and explore: You’ll explore the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the course.

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Unlimited Duration

Last Updated

January 14, 2021

Students Enrolled

Total Video Time

EXPIRED

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Certification

Course Description

Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the course.

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Course Curriculum

    • Different types of data science jobs 00:00:00
    • Choosing your path 00:00:00
    • Interview with Robert Chang, Data Scientist at Airbnb 00:00:00
    • MTC – the Massive Tech Company 00:00:00
    • Handbag LOVE – the established retailer 00:00:00
    • Seg-Metra – the early-stage startup 00:00:00
    • Videory – the late-stage, successful tech start-up 00:00:00
    • Global Aerospace Dynamics (GAD) – the massive government contractor 00:00:00
    • Putting it all together 00:00:00
    • Interview with Randy Au, Quantitative User Experience Researcher at Google 00:00:00
    • Earning a data science degree 00:00:00
    • Going through a bootcamp 00:00:00
    • Getting data science work within your company 00:00:00
    • Teaching yourself 00:00:00
    • Making the choice 00:00:00
    • Interview with Julia Silge, Data Scientist at Stack Overflow 00:00:00
    • Creating a project 00:00:00
    • Starting a Blog 00:00:00
    • Example Projects 00:00:00
    • Interview with David Robinson, Data Insights Engineering Manager at Flatiron Health 00:00:00
    • Finding jobs 00:00:00
    • Deciding which jobs to apply for 00:00:00
    • Interview with Jesse Mostipak, Managing Director of Data Science at Teaching Trust 00:00:00
    • Resume: the basics 00:00:00
    • Cover letters: the basics 00:00:00
    • Tailoring 00:00:00
    • Referrals 00:00:00
    • Interview with Kristen Kehrer, a data science instructor and course creator 00:00:00
    • What do companies want? 00:00:00
    • The interview processes 00:00:00
    • Step one: the initial phone screen interview 00:00:00
    • Step two: the on-site interview 00:00:00
    • Step three: the case study 00:00:00
    • Step four: the final interview 00:00:00
    • The offer 00:00:00
    • Interview with Ryan Williams, Senior Decision Scientist at Starbucks 00:00:00
    • The process 00:00:00
    • Receiving the offer 00:00:00
    • Negotiation 00:00:00
    • Negotiation Tactics 00:00:00
    • How to pick between two “good” job offers 00:00:00
    • Interview with Brooke Watson Madubuonwu, a Senior Data Scientist at the ACLU 00:00:00
    • The First Month 00:00:00
    • Becoming productive 00:00:00
    • If you’re the first data scientist 00:00:00
    • When it’s not what was promised 00:00:00
    • Interview with Jarvis Miller, Data Scientist at Spotify 00:00:00
    • The request 00:00:00
    • The analysis plans 00:00:00
    • Doing the analysis 00:00:00
    • Wrapping it up 00:00:00
    • Interview with Hilary Parker, a Data Scientist at Stitch Fix 00:00:00
    • What is deploying to production anyway? 00:00:00
    • Making the production system 00:00:00
    • Keeping the system running 00:00:00
    • Wrapping up 00:00:00
    • Interview with Heather Nolis, a Machine Learning Engineer at T-Mobile 00:00:00
    • Types of stakeholders 00:00:00
    • Working with stakeholders 00:00:00
    • Prioritizing work 00:00:00
    • Concluding remarks 00:00:00
    • Interview with Sade Snowden-Akintunde, a Data Scientist at Etsy 00:00:00
    • Why data science projects fail 00:00:00
    • What you can do when your projects failed 00:00:00
    • Interview with Michelle Keim, Head of Data Science & Machine Learning at Pluralsight 00:00:00
    • Growing your portfolio 00:00:00
    • Attending Conferences 00:00:00
    • Giving talks 00:00:00
    • Contributing to open source 00:00:00
    • Recognizing and avoiding burnout 00:00:00
    • Interview with Renee Teate, Director of Data Science at HelioCampus 00:00:00
    • Deciding to leave 00:00:00
    • How the job search differs after your first job 00:00:00
    • Giving notice 00:00:00
    • Interview with Amanda Casari, Engineering Manager at Google 00:00:00
    • The management tracks 00:00:00
    • Principal data scientist track 00:00:00
    • Switching to independent consulting 00:00:00
    • Choosing your path 00:00:00
    • Interview with Angela Bassa, Head of Data Science, Data Engineering, and Machine Learning at iRobot 00:00:00

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