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TOC for de zoomcamp; new structure, content, toc, images, description, faq, related posts for ml zoomcamp
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‎_data/faqs/machine-learning-zoomcamp.yml‎

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- question: "How is the Machine Learning Zoomcamp course structured?"
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The course runs for 4 months and includes pre-recorded videos, live office hours, hands-on projects, and a vibrant community. You'll need around 10 hours per week for coursework and projects.
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- question: "How can I start learning ML Zoomcamp (GitHub and cohort options)?"
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You can choose between two learning paths: self-paced learning, where you can start immediately with pre-recorded materials freely available on GitHub and learn at your own pace, or joining our live cohort starting on September 15, 2025, to learn alongside peers, participate in live sessions, submit homework and projects, and earn a certificate. Note that certificates are only available for cohort participants.
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- question: "What's included in the live ML Zoomcamp cohort?"
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The live cohort includes regular office hours with instructors, a structured learning path with deadlines, peer interaction and community support, the opportunity to earn a certificate, and access to all recorded sessions and office hours. Note that even if you're learning at your own pace, you still have access to all course materials and recordings.
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- question: "How do I get certified in the Machine Learning Zoomcamp?"
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To earn a certificate, you’ll need to finalize and submit two projects: one during the midterm (Midterm project) and another at the end (Capstone project 1 and/or Capstone project 2). You'll also need to review 3 peers' projects by the deadline. Keep in mind that projects must be completed individually, and you must be part of a cohort to be eligible for certification.
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- question: "Can I join ML Zoomcamp after the course has started?"
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Yes! While you might miss some homework deadlines, you can still join and get certified by completing the required projects. All course materials remain accessible.
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- question: "What Python knowledge do I need for ML Zoomcamp?"
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You should be familiar with basic Python concepts like variables, libraries, and Jupyter notebooks. If you need to brush up, we recommend taking our Introduction to Python course first.
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- question: "How can I engage with the DataTalks.Club Slack community for ML Zoomcamp?"
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Join our active Slack community, participate in office hours, and share your learning journey on social media with #mlzoomcamp. You can earn extra points for sharing your learning experience publicly.
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- question: "Is the Machine Learning Zoomcamp suitable for beginners?"
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Yes! If you have basic Python knowledge, you can start the course. The course is designed to be beginner-friendly, with step-by-step explanations of concepts, a practical hands-on learning approach, active community support in Slack, regular office hours for questions, and comprehensive learning materials.
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- question: "What technical setup do I need for ML Zoomcamp?"
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For machine learning modules, you only need a laptop with internet connection. For deep learning sections, we'll use cloud resources (like Saturn Cloud) for more intensive computations.
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- question: "What are the prerequisites for the Machine Learning Zoomcamp?"
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The only requirement for this course is prior programming experience (1+ year) and familiarity with the command line.
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- question: "What's the difference between self-paced and cohort learning in ML Zoomcamp?"
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While all course materials are freely available for self-paced learning, joining a cohort offers additional benefits. You'll get a structured timeline with regular deadlines, the ability to submit homework and projects for evaluation, active peer learning and discussion, live office hours and troubleshooting support, the opportunity to earn a certificate, and a shared learning experience with others facing similar challenges. Self-paced learners can access all materials and the Slack community but cannot submit homework, participate in project evaluations, or earn certificates. Many students find the cohort structure helps them stay motivated and complete the course successfully.
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- question: "How can I make the most of ML Zoomcamp for my career?"
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To maximize the course's career impact, we recommend starting your capstone project planning early and building a portfolio-worthy project that solves a real problem. Stay engaged with the Slack community and share your learning journey on social media using #mlzoomcamp. Take time to review and learn from other students' projects. When job hunting, use your project to demonstrate practical skills in applications and interviews - many of our alumni have successfully leveraged their course projects to demonstrate their machine learning capabilities during the hiring process.
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- question: "What is the Machine Learning Zoomcamp by DataTalks.Club?"
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The Machine Learning Zoomcamp is a free, community-driven program by [DataTalks.Club](https://datatalks.club/) that teaches core machine learning skills through [hands-on projects](#building-your-portfolio-with-machine-learning-projects).
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This machine learning course has a 4-month [curriculum](#course-curriculum) and all the materials are open and available any time on the [Machine Learning Zoomcamp GitHub repo](https://github.com/DataTalksClub/machine-learning-zoomcamp). You'll work with an industry-standard stack including Python, Jupyter notebooks, scikit-learn, pandas, NumPy, and Matplotlib and earn a [certificate](#how-does-the-machine-learning-zoomcamp-certificate-work).
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- question: "Is the Machine Learning Zoomcamp really free (free machine learning courses 2025)?"
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Yes, the Machine Learning Zoomcamp is completely free. There are no hidden costs, no tuition fees, and no paid tiers. All course materials, videos, homework assignments, and access to the [community](#datatalksclub-community-and-support) are provided at no cost. Unlike traditional bootcamps that charge $10,000-$20,000+, this course is entirely community-driven and open source.
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- question: "ML Zoomcamp vs machine learning bootcamp: what's the difference?"
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The Machine Learning Zoomcamp differs from traditional machine learning bootcamps in several key ways.
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1. **Cost**: While bootcamps typically cost $10,000-$20,000+, the Machine Learning Zoomcamp has no tuition fees whatsoever.
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2. **Community**: The Machine Learning Zoomcamp is community-driven and open source. All materials remain available forever on GitHub, unlike bootcamps that lock content behind paywalls.
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3. **Flexibility**: You can continue at your own pace even after the cohort ends, whereas bootcamps usually have rigid schedules and limited access periods.

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