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Certification

Certification in Building Machine Learning Models

Become certified in applied data science and machine learning. You'll be ready to build, evaluate, and deploy models with Python and SQL, tackle real projects from start to finish, and turn messy data into decisions employers trust.

Exam of 10 to 20 questionsCertificate for LinkedInBeginner · Intermediate
IT and developmentScience and research
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The exam

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Multiple-choice questions about the course. Pass with 70% or more and your certificate is issued at once, with a public page and an "Add to LinkedIn" button.

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What the exam covers

2 questions from each of the 15 chapters of the course

20 multiple-choice questions, drawn fresh for every attempt. Pass with 70% or more.

  1. 01What is data science?6:24
  2. 02Data roles compared9:16
  3. 03A data science roadmap9:00
  4. 04Python for data science2:41
  5. 05NumPy and pandas66:03
  6. 06Visualization with Matplotlib50:24
  7. 07Exploratory data analysis38:58
  8. 08Types of machine learning11:26
  9. 09Linear regression197:04
  10. 10Logistic regression40:25
  11. 11SVM and decision trees4:13
  12. 12K-means clustering55:17
  13. 13Project: recommendation system80:35
  14. 14Interview questions65:15
  15. 15MCP servers22:06
About the course

This certification is a complete walkthrough of the data science workflow, from framing the right questions to deploying machine learning models that actually work. You'll gain practical Python and SQL skills, a solid grasp of statistics and ML algorithms, and the kind of project experience that gives you a real competitive advantage and sets you up for a future-proof career with higher income potential. It's free, it's thorough, and if you're serious about getting job-ready, this is the place to start.

This certification covers the following topics:

  • The Data Science Lifecycle: A Structured Approach
  • The Three Pillars: Data Engineer, Data Analyst, and Data Scientist
  • The Data Science Roadmap: A Step-by-Step Study Plan
  • Python Essentials: Your Data Science Toolkit
  • Data Visualization: Telling Stories with Charts
  • Exploratory Data Analysis (EDA) in Practice
  • Core Machine Learning Algorithms: A Deep Dive
  • Recommendation Systems: Powering Personalization
  • Important Statistical Concepts and Model Evaluation
  • Modern Developments: MCP Servers and the Future of AI
  • Interview Preparation: Core Topics You Must Know

Jobs this certification suits

Our AI checked this certification against 500 jobs; these get the most out of it. Each job links to its learning path.

Bioinformaticians