Data and Programming Foundations for AI
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.
Skill level
BeginnerTime to complete
Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary39 hoursProjects
25Prerequisites
None
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
Syllabus
9 units • 35 lessons • 25 projects • 26 quizzes- 1
Welcome to Machine Learning/AI Engineering Foundations
See what you will learn in Machine Learning/AI Engineering Foundations!
- 2
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.
- 3
Python Fundamentals for ML/AI Engineers (Part I)
Build a foundation in programming with Python!
- 4
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.
- 5
Portfolio Project: U.S. Medical Insurance
Use your understanding of Python syntax to sort and analyze data about U.S. medical insurance costs!
- 6
Python Pandas for ML/AI Engineers
Learn how to use the Python pandas library and lambda functions.
- 7
Exploratory Data Analysis in Python
Learn about exploratory data analysis (EDA) techniques for Data Science
Certificate of completion available with Plus or Pro
Earn a certificate of completion and showcase your accomplishment on your resume or LinkedIn.
Projects in this skill path
- practice Project
Detecting Product Defects with Probability
Determine 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. - practice Project
Sampling Distributions Dance Party!
Investigate sampling distributions of Spotify data! - practice Project
Image Transformations with NumPy
Use NumPy and linear algebra knowledge to do fun image transformations!
Earn a certificate of completion
Show your network you've done the work by earning a certificate of completion for each course or path you finish.- Show proofReceive a certificate that demonstrates you've completed a course or path.
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- Share with your networkEasily add certificates of completion to your LinkedIn profile to share your accomplishments.
Reviews from learners
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- Brilliant learning experience. Very interactive. Literally a game changer if you're learning on your own.John-AndrewCodecademy Learner @ USA
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What's included in skill paths
Practice Projects
Guided projects that help you solidify the skills and concepts you're learning.Assessments
Auto-graded quizzes and immediate feedback help you reinforce your skills as you learn.Certificate of Completion
Earn a document to prove you've completed a course or path that you can share with your network.