Interviewing, Negotiating a Job Offer, and Career Planning from Coursera

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.

By the end of this course, students will be able to:

• Recall what actions need to be done before, during, and after an interview.

• Discuss a technical interview preparation plan.

• Identify job offer acceptance or refusal best practices.

• Create a career development plan.

What's inside

Syllabus

Develop and Refine Your Interviewing Skills

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.

Preparing for Technical Interviews

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.

Negotiating a Job Offer

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.

Career Planning for DS/AI Professionals

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.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops technical skills for data science job interviews

Offers insights into salary negotiation

Provides guidance on career development for data science professionals

Teaches how to prepare for technical interviews

Covers the entire interview process, from preparation to follow-up

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Interviewing, Negotiating a Job Offer, and Career Planning with these activities:

Compile and Review Study Materials

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Organize and review your notes, assignments, and resources to solidify your understanding.

Browse courses on Interview Preparation

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Gather notes, assignments, and practice problems
Organize them into a logical structure
Review the materials regularly

Read 'Cracking the Coding Interview' by Gayle Laakmann McDowell

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Gain a comprehensive understanding of technical interview strategies and problem-solving techniques.

View Cracking the Coding Interview: 189 Programming... on Amazon

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Purchase or borrow the book
Read through the chapters covering data science interview topics
Attempt the practice problems and coding challenges
Review the solutions and explanations

Follow Online Courses on Interview Preparation

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Learn from experienced professionals and gain structured guidance on interview techniques.

Browse courses on Interview Preparation

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Identify reputable online platforms offering data science interview preparation courses
Enroll in a course that fits your schedule and learning style
Complete the video lessons, assignments, and practice exercises

Four other activities

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Practice Data Science Interview Questions

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Build confidence by preparing for common technical interview questions in data science.

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Identify frequently asked data science interview questions
Review fundamental data science concepts and algorithms
Practice solving data science problems using coding tools
Simulate mock interviews to test your communication skills

Attend Data Science Interview Preparation Workshops

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Gain insights from industry experts and practice your interviewing skills in a supportive environment.

Browse courses on Interview Preparation

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Research and identify upcoming data science interview preparation workshops
Register for a workshop that aligns with your needs
Attend the workshop and actively participate in discussions and exercises

Coding Challenges and LeetCode Practice

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Sharpen your coding skills and prepare for technical interview coding questions.

Browse courses on Coding Challenges

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Choose a coding challenge platform
Select appropriate challenges based on difficulty and relevance
Solve coding problems regularly
Optimize code for efficiency and readability

Attend Data Science Meetups and Conferences

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Connect with professionals in the field, explore job opportunities, and expand your knowledge.

Browse courses on Networking

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Find local data science meetups and conferences
Attend events that align with your interests
Network with attendees, including recruiters, hiring managers, and industry experts

Career center

Learners who complete Interviewing, Negotiating a Job Offer, and Career Planning will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists are responsible for collecting, analyzing, and interpreting large amounts of data to extract meaningful insights and help businesses make informed decisions. This course can provide Data Scientists with the skills they need to prepare for and succeed in interviews, including how to answer technical questions and negotiate job offers. It can also help them develop a career development plan to advance their careers.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers are responsible for designing, building, and maintaining machine learning models. This course can provide Machine Learning Engineers with the skills they need to prepare for and succeed in interviews, including how to answer technical questions and negotiate job offers. It can also help them develop a career development plan to advance their careers.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data to identify trends and patterns. This course can provide Data Analysts with the skills they need to prepare for and succeed in interviews, including how to answer technical questions and negotiate job offers. It can also help them develop a career development plan to advance their careers.

See salaries and explore the career path for Data Analyst

Business Analyst

Business Analysts are responsible for understanding business needs and translating them into technical requirements. This course can provide Business Analysts with the skills they need to prepare for and succeed in interviews, including how to answer technical questions and negotiate job offers. It can also help them develop a career development plan to advance their careers.

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Software Engineer

Software Engineers are responsible for designing, developing, and maintaining software applications. This course may be useful for Software Engineers who are interested in working in the field of data science or machine learning.

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Quantitative Analyst

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Actuary

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Statistician

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Operations Research Analyst

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Financial Analyst

Financial Analysts are responsible for analyzing financial data and making investment recommendations. This course may be useful for Financial Analysts who are interested in developing their skills in data science or machine learning.

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Market Research Analyst

Market Research Analysts are responsible for conducting research to understand consumer behavior and trends. This course may be useful for Market Research Analysts who are interested in developing their skills in data science or machine learning.

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Data Governance Specialist

Data Governance Specialists are responsible for developing and implementing policies and procedures to ensure the accuracy, integrity, and security of data. This course may be useful for Data Governance Specialists who are interested in developing their skills in data science or machine learning.

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Database Administrator

Database Administrators are responsible for managing and maintaining databases. This course may be useful for Database Administrators who are interested in developing their skills in data science or machine learning.

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Data Engineer

Data Engineers are responsible for designing, building, and maintaining data infrastructure. This course may be useful for Data Engineers who are interested in developing their skills in data science or machine learning.

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Cloud Architect

Cloud Architects are responsible for designing and managing cloud computing systems. This course may be useful for Cloud Architects who are interested in developing their skills in data science or machine learning.

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