Data Science Career Guide - Interview Preparation from Udemy

According to Glassdoor, a career as a Data Scientist is the best job in America. With an average base salary of over $120,000, not only do Data Scientists earn fantastic compensation, but they also get to work on some of the world's most interesting problems. Data Scientist positions are also rated as having some of the best work-life balances by Glassdoor. Companies are in dire need of filling out this unique role, and you can use this course to help you rock your Data Scientist Interview.

This course is designed to be the ultimate resource for getting a career as a Data Scientist. We'll start off with an general overview of the field and discuss multiple career paths, including Product Analyst, Data Engineering, Data Scientist, and many more. You'll understand the various opportunities available and the best way to pursue each of them. The course touches upon a wide variety of topics, including questions on probability, statistics, machine learning, product metrics, example data sets, A/B testing, market analysis, and much more.

The course will be full of real questions sourced from employees working at some of the world's top technology companies, including Amazon, Square, Facebook, Google, Microsoft, AirBnb and more.

The course contains real questions with fully detailed explanations and solutions. Not only is the course designed for candidates to achieve a full understanding of possible interview questions, but also for recruiters to learn about what to look for in each question response. For questions requiring coded solutions, fully commented code examples will be shown for both Python and R. This way you can focus on understanding the code in a programming language you're already familiar with, instead of worrying about syntax.

What's inside

Learning objectives

Create a great data science resume!
Understand various positions and titles available in the data science ecosystem.
Get practice with probability and statistics interview questions.

Build an understanding of good experiment design.
Get practice with sql interview questions.

Create a great data science resume!
Understand various positions and titles available in the data science ecosystem.
Get practice with probability and statistics interview questions.
Build an understanding of good experiment design.
Get practice with sql interview questions.

Syllabus

Let's get you ready for the course!

Course Overview Lecture

Curriculum Overview

Frequently Asked Questions

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Read about what's good

what should give you pause

and possible dealbreakers

Covers a wide array of topics, including probability, statistics, machine learning, product metrics, and A/B testing, which are frequently tested in data science interviews

Includes real questions sourced from employees at top technology companies like Amazon, Facebook, and Google, providing valuable insights into industry expectations

Provides fully detailed explanations and solutions for interview questions, which helps candidates thoroughly understand the reasoning behind each answer

Offers fully commented code examples in both Python and R, allowing candidates to focus on understanding the logic in a familiar programming language

Explores various data science career roles and titles, which helps learners understand the different opportunities available in the field

Includes guidance on resume building, interview processes, and offer negotiation, which are essential skills for landing a data science job

Reviews summary

Interview prep for data science careers

According to learners, this course provides a solid foundation specifically targeted at data science interviews. Students frequently praise the inclusion of real interview questions sourced from top tech companies, finding the detailed explanations and solutions extremely helpful. The course covers a wide range of topics including probability, statistics, SQL, product metrics, and machine learning, offering code examples in both Python and R. While many found the content well-structured and easy to follow, a few reviewers suggested some sections could benefit from more in-depth coverage or updates to reflect current industry trends. Overall, it's seen as a practical resource for those preparing for technical interviews.

Provides code in Python and R.

"Providing solutions in both Python and R was a huge plus for me."

"The fully commented code examples were extremely useful for understanding the implementation."

"It's great to see the coding solutions laid out clearly for each question."

"Being able to review code in my preferred language (Python) made learning easier."

Covers key areas: stats, SQL, ML, product.

"It covers all the key areas expected in a data science interview - stats, probability, SQL, ML, and product metrics."

"I found the breadth of topics covered to be very comprehensive for interview preparation."

"Good overview of the different types of questions asked across various data science domains."

"Includes essential areas like A/B testing and product sense, which are crucial for many roles."

Solutions are detailed and easy to grasp.

"The solutions provided for each question are thorough and easy to understand, which really helped solidify my knowledge."

"Loved the detailed explanations on how to approach and solve the problems, not just getting the answer."

"The solutions are well-explained, making complex topics accessible even if you're rusty on some areas."

"Both the video explanations and the code examples were very clear and helpful."

Focuses on questions from top tech companies.

"The questions included are very relevant to the data science interviews I've been practicing for, mirroring those from FAANG companies."

"Having access to real interview questions from places like Google and Facebook is incredibly valuable."

"This course provides excellent, real-world interview questions that actually come up in technical screens."

"I appreciated that the questions felt authentic and representative of what I might encounter in actual interviews."

Needs occasional updates for trends.

"A few topics or question types feel slightly dated given how fast the field evolves."

"It would be beneficial to have updates incorporating newer technologies or interview formats."

"While mostly relevant, keeping the content current with the latest industry practices is important."

"Some reviewers noted a need for updates on specific algorithms or tools."

Some areas could use more depth.

"Some sections felt a bit rushed; I wished for more depth on certain machine learning algorithms."

"While broad, the coverage in specific areas like statistics might not be enough for more advanced roles."

"Could use more in-depth coverage on complex topics or optimization techniques."

"For truly senior roles, the depth might be insufficient, requiring supplementary study."

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 Data Science Career Guide - Interview Preparation with these activities:

Review Probability and Statistics Fundamentals

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Solidify your understanding of probability and statistics concepts to better tackle interview questions.

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Review basic probability rules and distributions.
Practice solving probability problems.
Study statistical inference methods.

Naked Statistics: Stripping the Dread from the Data

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Gain a deeper understanding of statistical concepts and their applications in data science.

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Read chapters on key statistical concepts.
Reflect on real-world examples.
Discuss concepts with peers.

Cracking the Coding Interview

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Reinforce your understanding of data structures and algorithms to prepare for coding-related interview questions.

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Read relevant chapters on data structures.
Practice coding problems.
Review solutions and explanations.

Four other activities

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Practice SQL Queries on Mock Datasets

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Enhance your SQL skills by practicing writing queries on datasets similar to those used in data science interviews.

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Find online SQL practice platforms.
Work through SQL exercises.
Analyze query performance.

Mock Interview with a Peer

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Simulate a real interview experience by conducting a mock interview with a peer.

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Find a peer to practice with.
Prepare interview questions.
Provide constructive feedback.

Design and Analyze an A/B Test

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Apply your knowledge of experiment design and statistical analysis by designing and analyzing an A/B test for a real-world scenario.

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Define a clear hypothesis.
Choose appropriate metrics.
Collect and analyze data.
Interpret the results.

Create a Data Science Portfolio Website

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Showcase your skills and projects by creating a professional data science portfolio website.

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Choose a website platform.
Highlight key projects.
Write clear descriptions.
Include a resume and contact info.

Career center

Learners who complete Data Science Career Guide - Interview Preparation will develop knowledge and skills that may be useful to these careers:

Data Scientist

A Data Scientist applies statistical and machine learning techniques to glean insights from data, building models to solve complex problems. This course is specifically designed to help you land a role as a Data Scientist by preparing you for the types of questions asked in interviews. The course covers probability, statistics, machine learning, and product metrics, which are all crucial for success as a Data Scientist. This course, with its focus on real interview questions from top tech companies, helps to build a deep understanding of necessary concepts and prepares candidates for the interview process and beyond.

See salaries and explore the career path for Data Scientist

Product Analyst

Product Analysts work closely with product teams to analyze user data and help guide product development and strategy. If you want to be a Product Analyst, this course may be particularly useful as it goes over product metrics and example datasets. You'll learn how to approach product related questions as well as other technical aspects like probability, statistics, and SQL, all of which are important for a Product Analyst to be successful. This course will help you see which questions to expect and how to tackle them to impress potential employers.

See salaries and explore the career path for Product Analyst

Machine Learning Engineer

Machine Learning Engineers build, deploy, and maintain machine learning models, working with complex algorithms and data pipelines. This course may be helpful for those interested in becoming a Machine Learning Engineer because it provides an overview of machine learning concepts, as well as real interview questions on machine learning. You will also practice questions on probability, statistics and SQL. These skills enable Machine Learning Engineers to understand, implement and troubleshoot the machine learning systems that are vital to their role. The course also covers the importance of software knowledge which is crucial for this role.

See salaries and explore the career path for Machine Learning Engineer

Business Intelligence Analyst

Business Intelligence Analysts analyze data to help businesses make better informed decisions, often using dashboards and visualizations. This course may help anyone interested in becoming a Business Intelligence Analyst due to its focus on data analysis, SQL, and product metrics. You will also practice questions on statistics and probability. These tools are useful for business insights. This course also covers interview preparation for all these topics.

See salaries and explore the career path for Business Intelligence Analyst

Quantitative Analyst

Quantitative Analysts, sometimes called Quants, utilize mathematical and statistical models to solve complex problems in finance and other sectors. This course may be useful for those looking to become a Quantitative Analyst because it provides a strong foundation in probability and statistics, two key areas in the field. Additionally, the course’s practice with real interview questions helps prepare for the specific types of problems one may face. A Quantitative Analyst will need a deep knowledge of these subjects.

See salaries and explore the career path for Quantitative Analyst

Analytics Consultant

Analytics Consultants work with clients to analyze their data and provide insights that drive business strategy, which requires statistical analysis and data management skills. This course may be helpful to someone looking to become an Analytics Consultant because it includes relevant subjects like machine learning, statistics, and product metrics. The course’s structure and focus on interview preparation may also help you land a position as an Analytics Consultant by helping you present your skill set clearly through a structured interview process.

See salaries and explore the career path for Analytics Consultant

Research Scientist

Research Scientists often conduct experiments and analyze data to advance scientific knowledge. The statistical and probability knowledge covered in this course may be especially useful for you to help form conclusions from data sets as a Research Scientist. The course also covers experiment design, which is a vital skill in research. This course can assist in your interview preparation when applying for jobs in this field.

See salaries and explore the career path for Research Scientist

Data Engineer

Data Engineers build and maintain the infrastructure that enables data analysis, which includes databases and data pipelines. This course covers SQL, which is a key skill for Data Engineers who must be able to extract and transform data. While this course does not specifically focus on other aspects of data engineering, its coverage of data and related interview questions may be useful in your job search as a Data Engineer. You may also find the lessons on statistics and probability useful as you advance in your career.

See salaries and explore the career path for Data Engineer

Statistician

Statisticians collect and analyze numerical data to help solve problems using statistical methods. For those looking to be a Statistician, this course may be particularly useful because it focuses on probability and statistics. You will also have the opportunity to practice solutions to real interview questions. The skills you acquire in this course will provide a strong foundation in the statistical and analytical aspects which are important to a Statistician's role.

See salaries and explore the career path for Statistician

Market Research Analyst

Market Research Analysts study consumer behavior and market trends to help companies make informed decisions about their products and services. This course, with its focus on data analysis, statistics and product metrics, may be useful to those pursuing a career as a Market Research Analyst. The course also helps you prepare for interview questions on these topics. The course's treatment of example data sets and A/B testing also aligns well with the activities of a Market Research Analyst.

See salaries and explore the career path for Market Research Analyst

Financial Analyst

Financial Analysts evaluate financial data to provide recommendations for investment opportunities, which requires analytical and statistical reasoning. This course's coverage of statistics, probability, and data analysis may be helpful when you're applying to be a Financial Analyst. It will help you analyze sets of data and build models for financial planning and forecasting. With this course, you can prepare for interviews with a solid foundation of data-related knowledge.

See salaries and explore the career path for Financial Analyst

Data Visualization Specialist

Data Visualization Specialists create visual representations of data, transforming numbers and text into engaging and understandable formats. This course may be useful for you if you are interested in the technical aspects of the role. While the course does not focus on the visualization aspects of the role, it does strengthen your technical background by teaching you data analysis and manipulation through SQL. It may also be useful to you when preparing for future interviews as a Data Visualization Specialist.

See salaries and explore the career path for Data Visualization Specialist

Operations Research Analyst

Operations Research Analysts use data and mathematical models to help businesses improve efficiency and reduce costs and often work with complex data sets. You may find this course useful because of its focus on the technical aspects of data analysis. The course reviews probability theory, statistical inference, and SQL interview questions. The course will help you become better prepared for a career as an Operations Research Analyst when seeking relevant experience.

See salaries and explore the career path for Operations Research Analyst

Biostatistician

Biostatisticians work with health and medical data using statistical methods to improve treatment, research, and public health. This course may be helpful for those interested in becoming a Biostatistician, given its focus on statistical analysis and probability theory. It contains practice questions for interview preparation, as well as SQL exercises, which may be useful to understanding and structuring data. This course may help you build a foundation in the data analysis skills that a Biostatistician needs.

See salaries and explore the career path for Biostatistician

Risk Analyst

Risk Analysts assess potential risks in various sectors, such as finance and insurance, and often employ mathematical and statistical methods. If you are interested in becoming a Risk Analyst, this course may provide a foundation in probability, statistical analysis, and data handling. The course also covers real interview questions which may help you to succeed in the interview process. The skills covered in this course will provide relevant background knowledge, and increase your overall preparedness when applying to become a Risk Analyst.

See salaries and explore the career path for Risk Analyst

Data Science Career Guide - Interview Preparation

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Interview prep for data science careers

Activities

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