How To Start A Career In Data Science 2023

The Ultimate Guide to Starting a Data Science Career: Create a Project Portfolio, Build Your Resume, Get an Interview

What you'll learn

How to land a job in data science

Create your data science project portfolio

Build your resume

Get an interview through Networking

Succeed during the phone interview

Solve the take home test

Ace the behavioral and technical questions

Requirements

The course is suitable for individuals interested in a career in data science

Description

Data science jobs are hyper-competitive. For each position, there are multiple other highly qualified candidates eyeing the same role.It is like you are all competing for a $100,000+ prize.If you frame it this way, wouldn’t you want to go the extra mile?By taking this course, you will be doing just that. You will learn valuable information that can give you a much-needed edge over other candidates.What better way to approach data science job hunting than learning from the experience of someone who is an actual data scientist and has recruited data scientists for his team?Ken Jee, your instructor for this course, is one of the most popular YouTubers focusing on data science. Over 70k people follow his YouTube channel. He has worked for several companies: consulting (Scouts Consulting Group), start-ups (GoHealth), and conglomerates like GE. In this course, he will be your private tutor offering a structured approach to landing a data science career.Ken will share invaluable insights leveraging his personal experience. You will learn 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- Ace the behavioral and technical questionsAdditionally, Ken has prepared several mock-interviews and 1-on-1 conversations with people who have successfully landed data science positions. These allow you to get an inside-look into the mind of successful candidates so you can see how the interview process really works. These interviews are not available elsewhere and act as an invaluable shortcut to a career in data science.The course offers you resume templates, downloadable materials, some exciting infographics, as well as a section on how to optimize your LinkedIn, Github, and Kaggle profiles for recruitment purposes.Taking this course can be a crucial step for your future career. No need to think twice. Start your journey towards a data science career today!

Overview

Section 1: Course Introduction

Lecture 1 What does the course cover?

Lecture 2 The data science knowledge you need

Lecture 3 Types of roles in data science

Lecture 4 The interview process structure

Lecture 5 What interviewers look for

Lecture 6 How to get the most out of the course

Section 2: The data science project portfolio

Lecture 7 Portfolio overview

Lecture 8 What is a data science project?

Lecture 9 The projects you should do

Lecture 10 How to differentiate your projects

Lecture 11 Asking a favor

Lecture 12 Where to showcase your projects

Lecture 13 Projects on Github

Lecture 14 Projects on Kaggle

Lecture 15 Bonus content: Portfolio website

Section 3: The data science resume

Lecture 16 Resume overview

Lecture 17 How to structure your resume

Lecture 18 How to write about work and projects

Lecture 19 Customize your resume

Lecture 20 Your virtual resume

Lecture 21 Resume checklist

Lecture 22 Data science cover letters

Lecture 23 Bonus content: LinkedIn

Section 4: Getting a data science interview

Lecture 24 Interviewing overview

Lecture 25 How candidates are selected

Lecture 26 Networking for data scientists

Lecture 27 Leveraging your resources

Lecture 28 Informational interviews

Lecture 29 Reaching out to recruiters

Section 5: The data science phone interview

Lecture 30 Phone interview overview

Lecture 31 What to expect

Lecture 32 How to prepare

Lecture 33 How to succeed

Section 6: The take-home test

Lecture 34 The types of take-home tests

Lecture 35 Dealing with data sets

Lecture 36 Coding quizzes

Lecture 37 Written test

Section 7: The in-person data science interview

Lecture 38 What to expect

Lecture 39 Ace the behavioral interview

Lecture 40 Technical interviews

Lecture 41 Following up

Lecture 42 The briefcase method

Section 8: Bonus content: Interviews with successful data scientists

Lecture 43 Anna interview

Lecture 44 Jaemin Interview

Lecture 45 Jay interview

Lecture 46 Jefferson interview

Lecture 47 Sheng interview

Lecture 48 Mock interview with Rachel Castellino

Lecture 49 Elevator pitch

Lecture 50 Star storytelling technique

Section 9: Bonus downloadable materials

Lecture 51 Resume and cover letter templates and checklist

Lecture 52 Reach out templates

Lecture 53 Interview questions

You should take this course if you want to become a Data Scientist or if you want to learn about the field,This course is for you if you want a great career