Successful Job Application

3h 20m 15s
English
Paid

Course description

In today's competitive job market, it is extremely important to have the skills and knowledge that will help you stand out from the crowd and secure the desired position. This training course is designed to provide you with effective tools and strategies for successful job searching and application submission. You will learn not only how to create resumes and cover letters but also how to prepare for interviews, analyze common questions, showcase your skills, and increase your chances of success. Upon completing the course, you will be confident and fully prepared to conquer the job market as a future data engineer.
Read more about the course

What you will learn:

Career paths, industries, and types of companies

  • Understanding the differences between Data Engineering, Data Science, and Software Engineering
  • Differences between Junior and Middle Data Engineer positions
  • Pros and cons of working in a startup, small business, or large corporation

Personal brand and social networks

  • How to create a strong personal brand through microblogging, video content, and posts
  • Setting up a LinkedIn profile and mistakes to avoid

Project portfolio

  • How to organize a technical portfolio
  • Ready datasets and template for GitHub documentation

How to bypass ATS

  • What ATS (Applicant Tracking System) is and how to "get through" it
  • The most important mistakes and recommendations for resume writing

Resume and cover letter

  • Types of resumes and choosing the appropriate format
  • How to write an effective cover letter
  • Ready-made template of a proven resume that will impress

Open and hidden job markets

  • The difference between the open and hidden job market
  • How to use networking and Boolean search to find hidden vacancies
  • How to properly analyze job descriptions and identify "red flags"

Successful interview process

  • Structure of the interview: from call to offer
  • How to effectively communicate your soft skills
  • How to negotiate salary
  • What questions to ask the interviewer

Freelancing in Data Engineering

  • Why consider working as a freelancer
  • Pros, cons, and tips for finding suitable projects

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# Title Duration
1 Intro 01:53
2 Career Paths 04:28
3 Data Engineer Levels 04:17
4 Transition Industry & Roles 06:07
5 Company Types 10:11
6 Getting Into The 1% 02:15
7 Building Your Personal Brand 04:36
8 LinkedIn Profile Tips 11:09
9 Your Project Portfolio & GitHub Documentation Template 07:11
10 Student Documentations 04:14
11 Introduction Datasets Section 00:54
12 Introduction To Datasets 04:05
13 Good Datasets 07:36
14 Where To Search For Datasets 01:53
15 Hand Picked Datasets 01:04
16 E-Commerce Datasets 04:05
17 Reviews Yelp Dataset 01:53
18 Reviews Airline Dataset 01:46
19 Banking & Machine Learning 02:11
20 Time Series Beijing Dataset 01:41
21 Time Series Energy Demand 01:45
22 Time Series Home Appliances 02:00
23 Conclusion 01:42
24 The CV & ATS 07:17
25 Creating a Resume 08:53
26 Cover Letter 02:12
27 It's ALL About You!! 01:57
28 CV Template & Tips 09:20
29 Open vs Hidden Job Market 08:06
30 Hiring Strategy Companies Explained 03:48
31 Hidden Job Market Do's & Don'ts 05:36
32 How To Search the Open Job Market 06:44
33 Alternative Titles For Data Engineers 03:17
34 Analyzing A Good Job Description 11:43
35 Analyzing A Bad Job Description 03:11
36 Interview Process Explained 03:41
37 How To Prepare For The Interview 04:53
38 The Phone Interview / Zoom Meeting 04:13
39 Camera & Background Setup 06:12
40 Most Important Questions You'll Be Asked 06:11
41 The Technical Interview 02:43
42 Salary Negotiation 09:32
43 Conclusion 01:50

Books

Read Book Successful Job Application

#Title
1DE Skills and Tools Guide

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