Starting a Career in Data Science: Project Portfolio, Resume, and Interview Process

This course provides you with invaluable insights directly from a top-level data scientist with first-hand experience in recruiting data scientists for his team. You will learn everything you need to get a competitive edge over other job candidates and start a career in data science: how to create your data science project portfolio, build your resume, get an interview through networking, succeed during the phone interview, solve the take-home test, and ace the behavioral and technical questions. The course also offers you resume templates, downloadable materials, helpful infographics, as well as a section on how to optimize your LinkedIn, Github, and Kaggle profiles for recruitment purposes.

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Section 1

Course Intro: What Is Data Science

An overview of the whole data science job market. The section covers the technical and non-technical skills you need, types of roles in data science, the interview process structure, as well as what employers look for in a candidate.

Premium course icon Course Overview
Premium course icon The Data Science Knowledge You Need
Premium course icon Types of Data Science Roles
Premium course icon The Interview Process Structure
Premium course icon What Interviewers Look For
Premium course icon How to Get the Most

Section 2

The Project Portfolio

In this section, you will understand what makes a good data science project, what types of data science projects you should do, and how to organize your projects into a portfolio on Kaggle or GitHub to make them appealing to employers.

Premium course icon Portfolio Overview
Premium course icon What Is a Data Science Project
Premium course icon The Projects You Should Do
Premium course icon How to Differentiate Your Projects
Premium course icon Where to Showcase Your Projects
Premium course icon Github Profile Best Practices
Premium course icon Kaggle Profile

Section 3

The Resume

Here, you will learn how to organize your resume, both virtual and hard copy, as well as what you should include to make a lasting impression on prospective employers. The section also includes a downloadable resume template - a great starting point if you haven't created a data science resume yet.

Premium course icon Resume Overview
Premium course icon How to Structure Your Resume
Premium course icon How to Write about Work and Projects
Premium course icon Customize your Resume
Premium course icon Your Virtual Resume
Premium course icon Resume Checklist
Premium course icon The Cover Letter

Section 4

Get an Interview

This section gives you a succinct overview of how candidates get selected, how networking can increase your chances, and how to leverage your existing resources into a data science interview opportunity.

Premium course icon Interviewing Overview
Premium course icon How Candidates are Selected
Premium course icon Networking for Data Scientists
Premium course icon Leveraging Your Resources
Premium course icon Informational Interviews
Premium course icon Reaching out to Recruiters

Section 5

The Phone Interview

Here, you will learn what to expect in data science phone interviews and discover some of the proven techniques on how to prepare for and succeed through this phase.

Premium course icon The Phone Interview Overview
Premium course icon What to Expect
Premium course icon How to Prepare
Premium course icon How to Succeed

Section 6

The Take-Home Test

This section gives you insight into the three types of take-home tests you can be given at this stage of the interview process. You will find out how to deal with data sets assignments, solve coding quizzes, and master the written test.

Premium course icon The Types of Take-Home Tests
Premium course icon Dealing with Data Sets
Premium course icon Coding Quizzes
Premium course icon Written Test

Section 7

The In-Person Interview

A detailed walk-through of the three different types of interviews - the behavioral, the in-person assessment, and the technical questions. This section comprises the best tips on how to ace the in-person interview and introduces you to the Briefcase Method – an interviewing technique that will certainly set you apart.

Premium course icon What to Expect
Premium course icon Ace the Behavioral Interview
Premium course icon Technical Interviewing
Premium course icon Following Up
Premium course icon The Briefcase Method

Section 8

Bonus Content: Interview with Successful Data Scientists

Here, you will get an inside look into the mind of successful candidates and how the interview process actually works. The section involves exclusive mock-interviews and 1-on-1 conversations with professionals who have successfully landed data science positions - an invaluable shortcut to a career in data science.

Premium course icon Anna Interview
Premium course icon Elevator Pitch Outline and Examples
Premium course icon Jaemin Interview
Premium course icon Jay Interview
Premium course icon Jefferson Interview
Premium course icon Sheng Interview
Premium course icon Glassdoor Findings
Premium course icon LinkedIn Bonus Content
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Premium course icon Bonus Content: Portfolio Website
Premium course icon Bonus Content: Star Storytelling Technique
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Section 9

Bonus Downloadable Materials

This bonus section comprises a variety of valuable downloadable resources: resume and cover letter templates and samples, reach-out templates and examples, a networking guide, as well as a complete guide with real data science interview questions and answers.

Premium course icon Resume and Cover Letter Templates and Checklist
Premium course icon Reach Out Templates
Premium course icon Interview Questions

Data Science Fundamentals

This course is part of Module 1 of the 365 Data Science Program. The complete training consists of four modules, each building upon your knowledge from the previous one. Whereas the other three modules are designed to improve upon your technical skill set, Module 1 is designed to help you create a strong foundation for your data science career. You will understand the core principles of probability, statistics, and mathematics; you will also learn how to visualize your data.

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