Machine Learning and AI Fundamentals
Learn the coding, data science, and math you need to get started as a Machine Learning or AI engineer.
Includes Python, Probability, Linear Algebra, Statistics, matplotlib, pandas, and more.
Time to completeAverage based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary39 hours
Certificate of completionYes
About this skill path
Machine Learning and AI are at the forefront of some of the most exciting modern technologies. From fraud detection systems to dating apps, machine learning engineering is changing the world. Joining this movement and becoming a Machine Learning Engineer requires a solid foundation in data literacy, programming, mathematics, statistics, and visualization. This Skill Path is that foundation.
Skills you'll gain
- Code in Python
- Explore and summarize data
- Know the math behind ML/AI
Syllabus9 units • 35 lessons • 25 projects • 26 quizzes
Welcome to Machine Learning/AI Engineering Foundations
See what you will learn in Machine Learning/AI Engineering Foundations!
Principles of Data Literacy
Discover the world of data in this fully conceptual course where you will learn how to think about, visualize, and analyze data.
Python Fundamentals for ML/AI Engineers (Part I)
Build a foundation in programming with Python!
Python Fundamentals for ML/AI Engineers (Part II)
Continue building your Python Skills while applying them to real challenges including finding and working with real data.
Portfolio Project: U.S. Medical Insurance
Use your understanding of Python syntax to sort and analyze data about U.S. medical insurance costs!
Python Pandas for ML/AI Engineers
Learn how to use the Python pandas library and lambda functions.
Exploratory Data Analysis in Python
Learn about exploratory data analysis (EDA) techniques for Data Science
Projects in this skill path
Detecting Product Defects with ProbabilityDetermine the number of defective products made at a factory on a given day. Apply concepts from the Poisson distribution, including random variables, the probability mass function, the cumulative distribution function, and expected values.
Sampling Distributions Dance Party!Investigate sampling distributions of Spotify data!
Image Transformations with NumPyUse NumPy and linear algebra knowledge to do fun image transformations!
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What's included in skill paths
Practice ProjectsGuided projects that help you solidify the skills and concepts you're learning.
AssessmentsAuto-graded quizzes and immediate feedback help you reinforce your skills as you learn.
Certificate of CompletionEarn a document to prove you've completed a course or path that you can share with your network.