Build a Career in Data Science

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Build a Career in Data Science video edition [TutsNode.com] - Build a Career in Data Science video edition
  • 95 - Appendix. Interview questions - A.3.7. Training vs. test data.mp4 (116.1 MB)
  • 96 - Appendix. Interview questions - A.4. Behavioral.mp4 (116.0 MB)
  • 37 - Chapter 7. The technical interview.mp4 (113.6 MB)
  • 77 - Chapter 14. Giving talks.mp4 (107.2 MB)
  • 76 - Chapter 14. Attending conferences.mp4 (106.6 MB)
  • 65 - Chapter 12. Working with stakeholders.mp4 (105.8 MB)
  • 59 - Chapter 10. Wrapping it up.mp4 (102.5 MB)
  • 2 - Chapter 1. What is data science.mp4 (101.8 MB)
  • 94 - Appendix. Interview questions - A.3. Statistics and machine learning.mp4 (99.7 MB)
  • 67 - Chapter 12. Communicating constantly.mp4 (99.2 MB)
  • 30 - Chapter 6. Structure.mp4 (97.5 MB)
  • 39 - Chapter 7. Step 3 - The case study.mp4 (95.7 MB)
  • 87 - Chapter 16. Principal data scientist track.mp4 (94.1 MB)
  • 86 - Chapter 16. The management track.mp4 (91.2 MB)
  • 26 - Chapter 5. Decoding descriptions.mp4 (91.1 MB)
  • 64 - Chapter 11. Keeping the system running.mp4 (89.6 MB)
  • 28 - Chapter 5. Deciding which jobs to apply for.mp4 (87.3 MB)
  • 4 - Chapter 1. Different types of data science jobs.mp4 (86.0 MB)
  • 80 - Chapter 15. Leaving your job gracefully.mp4 (84.6 MB)
  • 61 - Chapter 11. Making the production system.mp4 (83.5 MB)
  • 68 - Chapter 12. Prioritizing work.mp4 (83.1 MB)
  • 83 - Chapter 15. Giving notice.mp4 (82.8 MB)
  • 8 - Chapter 2. Seg-Metra - The early-stage startup.mp4 (81.9 MB)
  • 88 - Chapter 16. Switching to independent consulting.mp4 (81.0 MB)
  • 19 - Chapter 4. Building a portfolio.mp4 (80.4 MB)
  • 91 - Appendix. Interview questions - A.1. Coding and software development.mp4 (79.3 MB)
  • 69 - Chapter 12. Concluding remarks.mp4 (79.3 MB)
  • 63 - Chapter 11. Deploying an API.mp4 (79.0 MB)
  • 49 - Chapter 9. Knowing your data.mp4 (79.0 MB)
  • 6 - Chapter 2. Data science companies.mp4 (78.9 MB)
  • 42 - Chapter 8. Negotiation.mp4 (78.1 MB)
  • 62 - Chapter 11. Building an API.mp4 (77.6 MB)
  • 3 - Chapter 1. Databases_programming.mp4 (77.4 MB)
  • 58 - Chapter 10. Important points for exploring and modeling.mp4 (76.7 MB)
  • 57 - Chapter 10. Doing the analysis.mp4 (76.1 MB)
  • 73 - Chapter 13. Managing risk.mp4 (75.7 MB)
  • 75 - Chapter 14. Joining the data science community.mp4 (74.5 MB)
  • 81 - Chapter 15. How the job search differs after your first job.mp4 (73.8 MB)
  • 33 - Chapter 6. Referrals.mp4 (73.1 MB)
  • 78 - Chapter 14. Contributing to open source.mp4 (73.1 MB)
  • 27 - Chapter 5. Attending meetups.mp4 (72.2 MB)
  • 34 - Chapter 7. The interview - What to expect and how to handle it.mp4 (71.9 MB)
  • 23 - Chapter 4. Interview with David Robinson, data scientist.mp4 (71.2 MB)
  • 56 - Chapter 10. The request.mp4 (69.3 MB)
  • 21 - Chapter 4. Starting a blog.mp4 (69.3 MB)
  • 5 - Chapter 1. Choosing your path.mp4 (69.1 MB)
  • 15 - Chapter 3. Going through a bootcamp.mp4 (68.7 MB)
  • 41 - Chapter 8. The offer - Knowing what to accept.mp4 (67.6 MB)
  • 10 - Chapter 2. Global Aerospace Dynamics - The giant government contractor.mp4 (67.3 MB)
  • 55 - Chapter 10. Making an effective analysis.mp4 (66.9 MB)
  • 32 - Chapter 6. Cover letters - The basics.mp4 (65.7 MB)
  • 92 - Appendix. Interview questions - A.1.5. Frequently used package_library.mp4 (64.9 MB)
  • 13 - Chapter 3. Choosing the school.mp4 (64.7 MB)
  • 16 - Chapter 3. Getting data science work within your company.mp4 (64.5 MB)
  • 79 - Chapter 14. Recognizing and avoiding burnout.mp4 (64.3 MB)
  • 45 - Chapter 8. Interview with Brooke Watson Madubuonwu, senior data scientist at the ACLU.mp4 (63.1 MB)
  • 53 - Chapter 9. The work environment is toxic.mp4 (62.8 MB)
  • 60 - Chapter 11. Deploying a model into production.mp4 (62.6 MB)
  • 43 - Chapter 8. How much you can negotiate.mp4 (62.2 MB)
  • 50 - Chapter 9. Becoming productive.mp4 (61.4 MB)
  • 44 - Chapter 8. Negotiation tactics.mp4 (61.0 MB)
  • 9 - Chapter 2. Videory - The late-stage, successful tech startup.mp4 (60.5 MB)
  • 72 - Chapter 13. The data doesn’t have a signal.mp4 (60.2 MB)
  • 93 - Appendix. Interview questions - A.2. SQL and databases.mp4 (58.6 MB)
  • 36 - Chapter 7. Step 2 - The on-site interview.mp4 (56.6 MB)
  • 40 - Chapter 7. The offer.mp4 (56.2 MB)
  • 7 - Chapter 2. HandbagLOVE - The established retailer.mp4 (55.6 MB)
  • 84 - Chapter 15. Interview with Amanda Casari, engineering manager at Google.mp4 (54.1 MB)
  • 89 - Chapter 16. Choosing your path.mp4 (54.1 MB)
  • 22 - Chapter 4. Working on example projects.mp4 (52.2 MB)
  • 52 - Chapter 9. If you’re the first data scientist.mp4 (50.9 MB)
  • 71 - Chapter 13. When your data science project fails.mp4 (50.5 MB)
  • 12 - Chapter 3. Getting the skills.mp4 (50.2 MB)
  • 14 - Chapter 3. Getting into an academic program.mp4 (50.1 MB)
  • 35 - Chapter 7. Step 1 - The initial phone screen interview.mp4 (50.0 MB)
  • 17 - Chapter 3. Teaching yourself.mp4 (49.9 MB)
  • 66 - Chapter 12. Working with stakeholders.mp4 (49.6 MB)
  • 18 - Chapter 3. Interview with Julia Silge, data scientist and software engineer at RStudio.mp4 (49.1 MB)
  • 48 - Chapter 9. Understanding and setting expectations.mp4 (45.7 MB)
  • 11 - Chapter 2. Putting it all together.mp4 (44.9 MB)
  • 38 - Chapter 7. The behavioral interview.mp4 (44.1 MB)
  • 25 - Chapter 5. The search - Identifying the right job for you.mp4 (43.8 MB)
  • 82 - Chapter 15. Finding a new job while employed.mp4 (42.7 MB)
  • 51 - Chapter 9. Building relationships.mp4 (41.9 MB)
  • 54 - Chapter 9. Interview with Jarvis Miller, data scientist at Spotify.mp4 (41.1 MB)
  • 47 - Chapter 9. The first months on the job.mp4 (38.5 MB)
  • 74 - Chapter 13. Interview with Michelle Keim, head of data science and machine le- earning at Pluralsight.mp4 (35.5 MB)
  • 31 - Chapter 6. Deeper into the experience section - generating content.mp4 (35.4 MB)
  • 97 - Appendix. Interview questions - A.5. Brain teasers.mp4 (34.6 MB)
  • 85 - Chapter 16. Moving up the ladder.mp4 (33.9 MB)
  • 29 - Chapter 6. The application - Résumés and cover letters.mp4 (32.3 MB)
  • 20 - Chapter 4. Choosing a direction.mp4 (30.6 MB)
  • 90 - Epilogue.mp4 (25.9 MB)
  • 1 - PART 1.mp4 (18.0 MB)
  • 24 - PART 2.mp4 (12.3 MB)
  • 46 - PART 3.mp4 (9.8 MB)
  • Description


    Description

    Full of useful advice, real-case scenarios, and contributions from professionals in the industry.
    Sebastián Palma Mardones, ArchDaily

    You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager.

    about the technology
    What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career.

    about the book
    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 book.
    What’s inside

    Creating a portfolio of data science projects
    Assessing and negotiating an offer
    Leaving gracefully and moving up the ladder
    Interviews with professional data scientists



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Build a Career in Data Science


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6.3 GB
seeders:21
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Build a Career in Data Science


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