Prepare yourself for interviewing and landing a job in the DS/AI field. In this course, we will discuss what needs to be done before, during, and after the interview process. We will also provide tips and tricks on how to practice for a major component of data science interviews: the technical interview. Finally, this course will cover best practices for accepting or declining a job offer, salary negotiations, and how to create a career development plan.
Interviewing, Negotiating a Job Offer, and Career Planning
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Interviewing, Negotiating a Job Offer, and Career Planning
This course is part of Interviewing for DS/AI Roles Specialization
Instructor: Camille Funk
2,477 already enrolled
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Gain insight into a topic and learn the fundamentals.
Beginner level
Recommended experience
13 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Discuss a technical interview preparation plan.
Recall what actions need to be done before, during, and after an interview.
Identify job offer acceptance or refusal best practices and create a career development plan.
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
4 assignments
Taught in English
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This course is part of the Interviewing for DS/AI Roles Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course
Welcome to Module 1, Develop and Refine Your Interviewing Skills. After deciding on a position, updating your materials, and applying for jobs in the first two courses, now it’s time to prepare for interviews. In this module, we will discuss what research and preparation need to happen before an interview, what to do and say during an interview, and what actions need to be taken soon after an interview. We’ll conclude this module with a reflection on past interviews that might have included some sour notes and what can be done differently in the future.
What's included
2 readings1 assignment1 discussion prompt2 plugins
Welcome to Module 2, Preparing for Technical Interviews. Technical interviews are an opportunity to show your interviewers how well you can perform the skills associated with your desired role. In this module, we will cover common technical interview questions, places you can practice various data science interview problems, red flags to avoid, and other ways to prepare for your technical interview. We will wrap up the module with a discussion on how to improve your interview performance.
What's included
2 readings1 assignment1 discussion prompt1 plugin
Welcome to Module 3, Negotiating a Job Offer. Congratulations! All your hard work has paid off and you’ve got a job offer. As exciting as this is, the work is not over. Now you need to decide if the offer meets your expectations. In this module, we will discuss best practices related to accepting or declining a job offer. We will also explore strategies for negotiating your salary and other benefits. We will close the module with a discussion about personal experiences with job offer negotiation and what strategies we plan to implement in our next negotiation.
What's included
2 readings1 assignment1 discussion prompt2 plugins
Welcome to Module 4, Career Planning for DS/AI Professionals. Now that you’ve landed the job, it’s time to start considering your future career. In this module, we will identify the career paths for the DS/AI field, including paths for those who don’t want to get into management. We will also identify strategies for forward career progression and describe how we can implement the core skills learned throughout this specialization to improve our own job searches and interviews. Finally, we will take everything we’ve learned and create a career development plan to help guide us from our next job to our dream job.
What's included
2 readings1 assignment1 peer review1 discussion prompt1 plugin
Instructor
Instructor ratings
4.8 (5 ratings)5 Courses12,840 learners
Offered by
Recommended if you're interested in Data Analysis
Northwestern University
Duke University
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