Successful Job Application
3h 20m 15s
English
Paid
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 |
Read Book Successful Job Application
# | Title |
---|---|
1 | DE Skills and Tools Guide |
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