Data Science Interview Prep.Kit 2023 - FAQs in Interviews from Udemy

Are you completely beginner or intermediate in data science and confused about what kind of questions you may get asked in the interview?

Preparing for your next data science interview and wants to boost up your confidence before the interview?

Then this is the course for YOU.

Now as we all know data science is the most in-demand skill of the 21st century. And also the highest paying tech skill of current times. So if you want to:

Become a Data Scientist
Get that high paying job and
Be in demand

Then, you should definitely think of enrolling in this course and complete all the practice tests from important areas of data science like machine learning, statistics, SQL, etc. before your interview.

This course covers practice tests from important areas of data science like machine learning, python, statistics, etc. It covers many key and frequently asked questions in Top MNCs (Deloitte This course is designed as such and to make you more comfortable each practice test is from a different area of data science like machine learning, statistics, python, etc. And this course will be updated with time with more new questions and more new topics asked in the data science interview.

All The Best.

What's inside

Syllabus

This practice test contains actual Statistics questions asked in data science interviews.

This practice test contains actual SQL questions asked in data science interviews.

This test covers FAQs in data science interviews from the R programming area.

This practice test contains actual Python questions asked in data science interviews.

This practice test contains actual machine learning questions asked in data science interviews.

This test includes FAQs on Microsoft Power BI in Top MNCs

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Covers practice tests from machine learning, Python, statistics, and SQL, which are frequently asked about in data science interviews

Designed to boost confidence by familiarizing learners with questions from different areas of data science, such as machine learning and statistics

Includes FAQs on Microsoft Power BI, which is a popular tool for data visualization and business intelligence

Updated with new questions and topics, which helps learners stay current with the evolving demands of data science interviews

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 Interview Prep.Kit 2023 - FAQs in Interviews with these activities:

Review Statistical Concepts

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Solidify your understanding of fundamental statistical concepts to better grasp interview questions related to statistical analysis and modeling.

Browse courses on Hypothesis Testing

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Review key statistical definitions and formulas.
Work through practice problems on statistical tests.
Summarize the assumptions behind each statistical test.

Review 'Cracking the Coding Interview'

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Strengthen your problem-solving skills by reviewing 'Cracking the Coding Interview', focusing on data structures and algorithms relevant to data science.

View Cracking the Coding Interview on Amazon

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Review the chapters on data structures.
Review the chapters on algorithms.
Work through the practice problems in the book.

Review 'Python Data Science Handbook'

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Reinforce your Python skills for data science interviews by reviewing the 'Python Data Science Handbook'.

View Python Data Science Handbook: Essential Tools... on Amazon

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Read the chapters on NumPy and Pandas.
Read the chapters on Matplotlib and Scikit-learn.
Work through the examples in the book.

Four other activities

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Show all seven activities

SQL Query Practice

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Sharpen your SQL skills by solving a variety of query problems, focusing on those commonly asked in data science interviews.

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Practice writing SQL queries for data retrieval.
Practice writing SQL queries for data manipulation.
Optimize query performance using indexes.

Mock Interview Practice

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Simulate a real interview environment by participating in mock interviews with peers, receiving feedback on your technical skills and communication style.

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Find a peer to conduct a mock interview with.
Prepare a list of common data science interview questions.
Provide feedback to each other after the interview.

Create a Machine Learning Cheat Sheet

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Consolidate your knowledge of machine learning algorithms by creating a cheat sheet that summarizes key concepts, formulas, and use cases.

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Choose the machine learning algorithms to include.
Summarize the key concepts and formulas for each algorithm.
Include use cases and examples for each algorithm.

Build a Data Visualization Dashboard

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Showcase your data visualization skills by building an interactive dashboard using tools like Power BI, demonstrating your ability to communicate insights effectively.

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Choose a dataset to visualize.
Design the layout and functionality of the dashboard.
Implement the dashboard using Power BI.

Career center

Learners who complete Data Science Interview Prep.Kit 2023 - FAQs in Interviews will develop knowledge and skills that may be useful to these careers:

Data Scientist

A data scientist analyzes complex data to extract insights and inform business decisions. This role often involves statistical analysis, machine learning, and data visualization. This course, with its focus on interview preparation in areas like machine learning, statistics, and SQL, is highly relevant for aspiring data scientists. The practice tests in this course cover common interview questions that a data scientist might encounter. Familiarity with these questions helps build a foundation for a successful job search. The course's coverage of Python and R programming languages makes it an even better fit.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine learning engineers develop and deploy machine learning models. This typically involves programming, data manipulation, and a strong understanding of algorithms. This course directly addresses the interview preparation needs for aspiring machine learning engineers, with practice tests focused on machine learning concepts and common questions. The course may be useful for someone looking to understand how to apply their skills in a work environment. The coverage of Python aids in developing the necessary coding skills, and the focus on frequently asked interview questions helps learners feel more confident in the job search.

See salaries and explore the career path for Machine Learning Engineer

Data Analyst

A data analyst interprets data to identify trends and patterns, often using SQL and data visualization tools. This role is crucial for translating data into actionable insights for business stakeholders. This course may be useful for those aiming to be a data analyst, especially with the practice tests on SQL, statistics and Power BI, all critical skills for the role. The course's coverage of frequently asked questions in interviews may help the data analyst prepare. The course helps to strengthen a candidate in the most common tools and techniques for the role.

See salaries and explore the career path for Data Analyst

Business Intelligence Analyst

A business intelligence analyst leverages data to create visualizations and dashboards that help business leaders make strategic decisions. The role requires a solid understanding of data analysis and visualization tools and an ability to tell a story with data. As a business intelligence analyst, you leverage software, data modeling, and reporting to understand trends in sales, marketing and other aspects of a business. This course, with its section on Power BI and statistics, may help someone interested in such a role. Additionally, the course's practice tests in Python and SQL provide valuable skills needed to perform data analyses.

See salaries and explore the career path for Business Intelligence Analyst

Statistician

A statistician uses statistical methods to analyze data and solve problems. Statisticians develop studies using mathematical methods to answer questions and interpret the results. This career often requires an advanced degree. This course may be useful for statisticians, offering practice tests directly related to common interview questions. The focus on statistical knowledge helps prepare these users to discuss their expertise in an interview setting. The course's coverage of tools like R and Python strengthens one's ability to perform data analysis.

See salaries and explore the career path for Statistician

Research Scientist

A research scientist conducts scientific studies and experiments, often requiring a PhD. They work in academic, government, or industrial settings, using a variety of methods including statistical analysis and data modeling. This course may be useful, as it offers practice tests in statistics, machine learning, and R and Python programming. By building a foundation of knowledge in these areas, and by practicing interview questions, the course is a good resource for those looking to enter this field. This course may help the budding research scientist discuss their knowledge comfortably in interviews.

See salaries and explore the career path for Research Scientist

Quantitative Analyst

A quantitative analyst is involved in creating models and algorithms for financial applications. This role often requires an advanced degree in a quantitative field. The work involves heavy usage of statistics and programming. This course may be useful for one who is interested in becoming a quantitative analyst. The course's coverage of statistical concepts, machine learning techniques, and programming languages like Python and R provides useful skills. The practice tests in the course aid greatly in interview preparedness.

See salaries and explore the career path for Quantitative Analyst

Bioinformatician

A bioinformatician analyzes biological data using computational techniques, often working with genetics and genomics information. This role often requires an advanced degree. The work uses programming languages and statistical methods to analyze complex biological data. This course may help aspiring bioinformaticians with interview preparation, especially with the practice tests in statistics, machine learning, and Python/R. The course may be beneficial in strengthening their foundation of relevant knowledge and the associated skills.

See salaries and explore the career path for Bioinformatician

Database Administrator

A database administrator manages and maintains databases using SQL. They ensure data security and integrity, and optimize query performance. A database administrator must be proficient in data management and database structure. The practice tests in this course related to SQL may be useful to those seeking to enter this field. Although this course isn't specifically targeting database administration, those test questions that appear in interviews may be of use to someone preparing for interviews.

See salaries and explore the career path for Database Administrator

Software Engineer

Software engineers design, develop, and maintain software applications. This usually involves coding in multiple languages and using a wide variety of development tools. The course may be helpful as it covers Python. Although not the main focus, a software engineer may find relevant the practice tests that are common in interviews for data science positions. A software engineer may also find the machine learning section to be useful as well as the information on SQL. The practice with interview questions is of great value for the job seeker.

See salaries and explore the career path for Software Engineer

Financial Analyst

A financial analyst provides insights and recommendations based on financial data. They evaluate financial performance, and develop forecasts. A key aspect of their role is analyzing trends and patterns in financial data. This course may be helpful to one who works in financial analysis, due to its SQL and statistics practice questions. Though not targeted to this role, anyone who works with data, or is interested in working with data, may find the course beneficial.

See salaries and explore the career path for Financial Analyst

Market Research Analyst

A market research analyst studies consumer behavior and market trends. They gather data by conducting surveys, analyzing sales figures, and looking at other sources of information. They help companies better understand their target audiences and competitors. This course may be useful. While it is not the main focus, the course includes relevant practice tests in statistics and SQL. One might benefit from the practice questions in interviews provided in this course.

See salaries and explore the career path for Market Research Analyst

Project Manager

Project managers plan, organize, and oversee projects, making sure they are completed on time and within budget. Project managers manage teams and communicate with stakeholders. A project manager may find this course useful, especially if they work on data-centric projects. Though not a specific focus, the course's sections on SQL, statistics, Power BI, Python and R might be beneficial in understanding how data is used within the team. The practice questions for interviews may also prove helpful.

See salaries and explore the career path for Project Manager

Management Consultant

Management consultants provide strategic advice to organizations on improving their performance, efficiency, and overall strategies. They work with various stakeholders and across different industries. The course may be helpful for a management consultant through it's coverage of tools and techniques used in data science. The course's treatment of Power BI may help them visualize data better. As it touches on machine learning, the course is of value to anyone interested in data science.

See salaries and explore the career path for Management Consultant

Technical Writer

A technical writer creates documentation for technical products and services. They translate complex information into easily understandable content. They often work on user guides and API documentation. Although not directly related to a technical writer role, this course may be useful due to the need for a technical writer to understand the technical concepts in their documentation. The practice tests in the course, especially in areas like machine learning, Python, and SQL, might provide a useful background for the writer.

See salaries and explore the career path for Technical Writer

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Data Science Interview Prep.Kit 2023 - FAQs in Interviews.

Python Data Science Handbook

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Provides a comprehensive overview of essential Python libraries for data science, including NumPy, Pandas, Matplotlib, and Scikit-learn. It valuable resource for refreshing your Python skills and learning how to apply them to data analysis and machine learning tasks. The book is commonly used as a textbook and reference by both students and professionals. It adds depth to the Python-related topics covered in the course.

Python Data Science Handbook: Essential Tools for...

Paperback

$$$

Cracking the Coding Interview

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While not strictly data science focused, this book provides a solid foundation in algorithms and data structures, which are often tested in data science interviews. It offers a structured approach to problem-solving and includes numerous practice questions. is more valuable as additional reading to prepare for the technical aspects of the interview. It is commonly used by software engineers and data scientists alike.

Cracking the Coding Interview

Paperback

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Cracking the Coding Interview

Kindle Edition

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Data Science Interview Prep.Kit 2023 - FAQs in Interviews

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

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