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Data Analytics Career Overview - From Skills to Interviews
Rating: 4.8 out of 5(62 ratings)
1,075 students

Data Analytics Career Overview - From Skills to Interviews

A guide to your career in analytics track
Last updated 1/2024
English

What you'll learn

  • If analytics career is right for you
  • What tools and skills you need for getting an analytics job
  • To know how analytics can help you in work
  • Understand different analytics tools and use cases
  • Frequently seen mistakes during analysis
  • Quantitative method that can help you better in analysis
  • Interview questions for analytics roles
  • Some tips of job offers negotiation

Course content

5 sections72 lectures2h 47m total length
  • Intro to the course3:39
  • Course Materials1:58

Requirements

  • No prerequisite for coding and analysis, but requires basic statistics knowledge, i.e. mean, percentiles, and distribution
  • Ideally some SQL & spreadsheet knowledge would be better

Description

Do you need data analysis in your work? Or you want to be an data analyst but don't know where to start? Many companies claim that they are data-driven and looking for analytical talents. But what is data driven and what exactly is analytical skills? Why we are already looking at numbers but still don't know what to do? Why I have required skills like SQL or Python, but still not hired?


If you have related questions like mentioned above or wonder if analytics career is right for you, this course could be right to you. This course won't teach you everything of SQL, Python, or R. But will let you know what tools or techniques you need to be an analyst. It's perfect for students or people who want to be analyst.


I'll walk you through what roles you would have chance to apply analysis, what popular tools there are in tech industry, and how the interviews would look like. I even provided the list of courses and resources that I recommend. My 5 years of experience and job searching knowledge sharing in a nutshell.


Chapters

Overview

  • Different roles and their scenarios of using analysis during works

Tools

  • Spreadsheet

  • SQL

  • Tableau

  • Python & R

Quantitative Analysis

  • Metrics Definition

  • Normalization

  • Frequently seen mistakes

Interview

  • Behavioral

  • SQL

  • Technical Screening

  • Case Interviews

Who this course is for:

  • People who are interested in but new to analytics
  • Analytics workers who are struggle to find better methodologies for analysis
  • Engineers or Product Managers who would like to know more about product analysis
  • People from marketing or operation who would like to apply analytics in their work