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Tier 3 to Data Analyst in 3 months I Complete Roadmap I 2024

Bosscoder Academy Data Science Review, check the details by clicking the link below. https://bit.ly/3K4LJ1s In today's video I have discussed about the career and job opportunity as Data Analyst in India.We have discussed in detail about how you can make your resume and how you can get a job as a Data Analyst.Our guest today is from a biology background and she has discussed with us a very detailed roadmap to come into the data field. Please watch the full video and share your feedback. Thank u so much for all the love you are showering on me🙏🏻Please do like, share and subscribe to my channel 🙇🏻‍♀️ My name is Shivangi Tiwari and I am a software engineer by profession. Hope my videos are helpful for you in getting your dream job. Keep watching my content and applying them in your life to achieve your goals. Feel free to comment me your queries, I will be glad to help you all. Shaima's LinkedIn:   / shaimahmed98   00:00 - 01:00 Recap 01:01 - 02:16 Introduction 02:17 - 02:41 Educational Background 02:42 - 06:03 How did she develop interest in data science? 06:04 - 07:33 Challenges she faced while transitioning to data field as bio student 07:34 - 08:58 Why did you decide to select data-analyst profile? 08:59 - 09:49 Roles and responsibilities as a data-analyst 09:50 - 11:37 Easiest way to become a data-analyst 11:38 - 12:49 Is it easy to come in data science field with no coding? 12:50 - 14:28 Important subjects to learn to become a data-analyst 14:29 - 15:53 Courses and certifications 15:54 - 17:37 Roadmap to become data-analyst from scratch 17:38 - 19:14 Resources to follow to learn data-analysis 19:15 - 22:03 How to make a time-table to learn all the subjects? 22:04 - 23:31 What projects to make? 23:32 - 24:50 Name of projects she has worked on 24:51 - 26:06 How to build a strong resume? 26:07 - 28:00 Interview process of data-analyst 28:01 - 29:07 Questions asked in technical interview round 29:08 - 30:33 Salary ranges for data-analytics role 30:34 - 32:25 Mistakes and learnings 32:26 - 32:56 Conclusion #data #datascience #dataanalytics #softwareengineer