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Arpan Chakraborty, Brynn Claypoole, and Horatio Thomas

Get confident in complex data challenges and real-world ML scenarios to land your dream job with Udacity's Machine Learning Interview Prep Training Course.

What's inside

Syllabus

Get inside the mind of your future employer. Identify business problems that are likely to crop up in the companies where you want to work and explore potential machine learning solutions.
Read more
Step into the role of the interviewer. Observe and analyze answers to technical and behavioral questions representative of a machine learning interview.
Learn about the “algorithm” for answering common technical interviewing questions. Practice and get tips for giving interviewers what they’re looking for.
Practice as much as possible and you will make the best impression in an actual interview.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Prepares learners for the types of questions that are increasingly present in machine learning job interviews
Provides insights into business problems that machine learning can solve, bridging the gap between theory and real-world applications

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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 Machine Learning Interview Preparation with these activities:
Review Calculus I
Refreshes your knowledge of basic calculus concepts, improving your understanding of mathematical concepts
Show steps
  • Review your notes from a previous Calculus I course
  • Complete practice problems on derivatives and integrals
  • Take a practice quiz or exam to assess your understanding
Review Python basics
Refreshes your Python programming skills and helps you to create more effective ML models
Browse courses on Python
Show steps
  • Review the basics of Python syntax and data types
  • Complete coding exercises on variables, loops, and functions
  • Create a simple Python program that performs basic operations
Attend ML meetups and conferences
Expands your network, exposes you to different ML applications, and helps you stay up-to-date with industry trends
Browse courses on Machine Learning
Show steps
  • Identify ML meetups and conferences in your area or online
  • Attend these events and connect with ML professionals
  • Participate in discussions and share your knowledge
Five other activities
Expand to see all activities and additional details
Show all eight activities
Solve ML practice problems
Improves your problem-solving skills, reinforces your understanding of ML concepts, and prepares you for technical interviews
Browse courses on Machine Learning
Show steps
  • Find ML practice problems on websites or in books
  • Work through the problems and check your solutions
  • Analyze your mistakes and find areas for improvement
Join an ML study group
Provides opportunities to collaborate with peers, share knowledge, and learn from different perspectives
Browse courses on Machine Learning
Show steps
  • Find an ML study group in your area or online
  • Regularly attend study group meetings
  • Engage in discussions and share your knowledge with the group
Practice using scikit-learn
Deepens your understanding of scikit-learn, a popular ML library, improving your ability to implement ML algorithms
Browse courses on scikit-learn
Show steps
  • Follow tutorials on using scikit-learn for data preprocessing, model training, and evaluation
  • Complete exercises that guide you through building ML models with scikit-learn
Create a portfolio of ML projects
Provides hands-on experience and helps you build a portfolio to showcase your ML skills to potential employers
Browse courses on Machine Learning
Show steps
  • Identify ML projects that align with your interests and career goals
  • Gather data and explore different ML algorithms
  • Build and train ML models and evaluate their performance
  • Present your projects in a portfolio format
Build a recommendation system
Provides practical experience in building and deploying an ML system, showcasing your skills to potential employers
Browse courses on Machine Learning
Show steps
  • Define the problem and gather relevant data
  • Choose and train an ML algorithm for making recommendations
  • Deploy your recommendation system and evaluate its performance

Career center

Learners who complete Machine Learning Interview Preparation will develop knowledge and skills that may be useful to these careers:
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and deploys machine learning models. A Machine Learning Interview Preparation course may be useful to Machine Learning Engineers by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Machine Learning Engineers to better understand the needs of their clients and to develop solutions that are tailored to their specific needs.
Machine Learning Scientist
A Machine Learning Scientist designs, develops, and deploys machine learning algorithms and models. This course may be useful to Machine Learning Scientists by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Machine Learning Scientists to better understand the needs of their clients and to develop solutions that are tailored to their specific needs.
Data Analyst
A Data Analyst collects, analyzes, and interprets data to help businesses make informed decisions. A Machine Learning Interview Preparation course may be helpful to Data Analysts by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Data Analysts to better understand the needs of their clients and to develop solutions that are tailored to their specific needs.
Data Scientist
A Data Scientist uses machine learning and other data analysis techniques to extract insights from data. A Machine Learning Interview Preparation course may be helpful to Data Scientists by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Data Scientists to better understand the needs of their clients and to develop solutions that are tailored to their specific needs.
Software Engineer
A Software Engineer designs, develops, and maintains software applications. A Machine Learning Interview Preparation course may be helpful to Software Engineers by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Software Engineers to better understand the needs of their clients and to develop solutions that are tailored to their specific needs.
Quantitative Analyst
A Quantitative Analyst uses mathematical and statistical models to analyze financial data. A Machine Learning Interview Preparation course may be useful to Quantitative Analysts by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Quantitative Analysts to better understand the needs of their clients and to develop solutions that are tailored to their specific needs.
Product Manager
A Product Manager leads the development and launch of new products. A Machine Learning Interview Preparation course may be useful to Product Managers by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Product Managers to better understand the needs of their customers and to develop products that meet their needs.
Researcher
A Researcher conducts scientific research to advance knowledge in a particular field. A Machine Learning Interview Preparation course may be useful to Researchers by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Researchers to better understand the needs of their field and to develop solutions that are tailored to those needs.
Business Analyst
A Business Analyst helps businesses to improve their performance by identifying and solving problems. A Machine Learning Interview Preparation course may be helpful to Business Analysts by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Business Analysts to better understand the needs of their clients and to develop solutions that are tailored to their specific needs.
Consultant
A Consultant provides advice and guidance to businesses on a variety of topics. A Machine Learning Interview Preparation course may be helpful to Consultants by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Consultants to better understand the needs of their clients and to develop solutions that are tailored to their specific needs.
Machine Learning Architect
A Machine Learning Architect designs and builds machine learning systems. A Machine Learning Interview Preparation course may be useful to Machine Learning Architects by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Machine Learning Architects to better understand the needs of their clients and to develop solutions that are tailored to their specific needs.
Data Engineer
A Data Engineer designs, builds, and maintains data pipelines to ensure that data is available for analysis. A Machine Learning Interview Preparation course may be useful to Data Engineers by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Data Engineers to better understand the needs of their clients and to develop solutions that are tailored to their specific needs.
Technical Writer
A Technical Writer creates documentation and other materials to help people understand complex technical concepts. A Machine Learning Interview Preparation course may be useful to Technical Writers by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Technical Writers to better understand the needs of their audience and to develop documentation that is clear and concise.
Sales Engineer
A Sales Engineer helps customers to understand and purchase complex technical products and services. A Machine Learning Interview Preparation course may be useful to Sales Engineers by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Sales Engineers to better understand the needs of their customers and to develop solutions that are tailored to their specific needs.
Project Manager
A Project Manager plans and executes projects to achieve specific goals and objectives. A Machine Learning Interview Preparation course may be useful to Project Managers by providing them with the skills and knowledge necessary to succeed in their role. For example, the course covers topics such as identifying business problems that are likely to crop up in companies where you want to work and exploring potential machine learning solutions. This knowledge can help Project Managers to better understand the needs of their clients and to develop solutions that are tailored to their specific needs.

Reading list

We've selected 12 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 Machine Learning Interview Preparation.
Provides a practical guide to machine learning using Python, Scikit-Learn, Keras, and TensorFlow. It valuable resource for those who want to learn how to apply machine learning to real-world problems.
Provides a probabilistic perspective on machine learning, covering topics such as Bayesian inference, Gaussian processes, and Markov chain Monte Carlo. It valuable resource for those who want to deepen their understanding of the theoretical foundations of machine learning.
Provides a comprehensive overview of deep learning, including neural networks, convolutional neural networks, and recurrent neural networks. It valuable resource for those who want to learn more about the theory and practice of deep learning.
Provides a comprehensive overview of reinforcement learning, including Markov decision processes, value functions, and policy search. It valuable resource for those who want to learn more about the theory and practice of reinforcement learning.
Provides a comprehensive overview of statistical learning, including linear regression, logistic regression, and tree-based methods. It valuable resource for those who want to learn more about the theory and practice of statistical learning.
Provides a comprehensive overview of machine learning, including supervised and unsupervised learning, deep learning, and reinforcement learning. It valuable resource for those who want to learn more about the theory and practice of machine learning.
Provides a practical guide to machine learning using Python. It valuable resource for those who want to learn how to apply machine learning to real-world problems.
Provides a practical guide to machine learning using Python. It valuable resource for those who want to learn how to apply machine learning to real-world problems.
Provides a gentle introduction to machine learning. It valuable resource for those who want to learn the basics of machine learning without getting bogged down in the details.
Provides a hands-on guide to building neural networks using Python. It valuable resource for those who want to learn how to build and train neural networks from scratch.
Provides a comprehensive overview of deep learning for natural language processing. It valuable resource for those who want to learn more about the theory and practice of deep learning for natural language processing.
Provides a comprehensive overview of machine learning for audio, speech, and music. It valuable resource for those who want to learn more about the theory and practice of machine learning for audio, speech, and music.

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