AI & Machine Learning Foundations I

AI & Machine Learning Foundations I

Delve deeper into data science with advanced data processing, regression analysis, and machine learning.

Financing and flexible payment options available. Learn more

Upcoming Cohort Start Dates

New courses start the first Monday of every month.

January 5, 2026
February 2, 2026
March 2, 2026

Qualification

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Duration

12 Weeks
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Delve deeper into data

Expand your data science toolkit with intermediate SQL, Tableau, PySpark, and Generative AI tools. From advanced data processing techniques to regression analysis and machine learning, you’ll gain the knowledge and hands-on experience needed to tackle real-world data challenges. You’ll explore big data tools, learn to manage and analyze large datasets and develop the skills to build predictive models that drive business decisions. These courses are designed to push your understanding further, helping you transition from basic analysis to mastering the complex techniques that are essential in today’s data-driven industries.

The Furman // Flatiron School difference

Be mentored by a world-class data scientist

Small group classes (max 8 students)

100% online programs

Program prerequisites: AI & Machine Learning Essentials

Upon completion of this program, you'll be able to move on to AI & Machine Learning Foundations II

AI and Data Science Foundations I

Cloud Computing, Generative AI, & Dashboards

FT: 1 week | PT: 3 weeks

This course dives into cloud computing's cost-effective, scalable ecosystem for distributed data processing. Master technical components like PySpark to bridge Python, SQL, and Spark, to manipulate structured and semi-structured data. Leverage libraries to Numpy, Pandas, and PySpark to pull in "big data". You will craft stunning visualizations with Python libraries like Seaborn. Finally, explore the cutting-edge of data analysis with generative AI and advanced dashboards, culminating in a project that brings big data to life through interactive visualizations.

What you'll learn:

  • Create a dashboard using data science methodologies with industry standard tool(s)
  • Model exploratory data analysis with tools for multiple data sets with SQL and SQL table relations
  • Utilize programming techniques to process large data samples with large-scale processing like PySpark with big data

Course focus:

  • Pyspark
  • SQL
  • Numpy
  • Pandas
  • Data Visualization
  • Big Data

Inferential Statistics

FT: 1 week | PT: 3 weeks

In this course you will perform statistical inference with Python. This course equips you with the foundational theory and practical skills to analyze data. Learn about probability distributions, confidence intervals, hypothesis testing, and more. Apply these techniques to single proportions, means, and categorical data. Explore advanced methods for two or more groups and tackle multivariate datasets. This culminates with your final project where you'll showcase your ability to use a multivariate dataset and perform a myriad of the appropriate methods of statistical inference.

What you'll learn:

  • Integrate statistical inference of data using the technical programming
  • Implement methodologies for statistical inference
  • Utilize mathematics, statistics, and probability for data science methodologies to derive insights

Course focus:

  • Pyspark
  • Statistical inference
  • Multivariate datasets
  • Big Data

Regression

FT: 1 week | PT: 3 weeks

This course equips you with the skills to tackle real-world datasets with regression. Master linear regression, exploring diagnostics to ensure model validity. Delve into multiple linear regression, learning to evaluate, diagnose, and leverage its predictive power. Discover advanced techniques like transformations, interactions, and model selection. Explore bias-variance tradeoff and master regularization methods like Lasso and Ridge regression. Finally, in the culminating project, showcase your expertise by building and interpreting a powerful multiple linear regression model.

What you'll learn:

  • Perform logistic regression with data sets using programming techniques, lasso, and ridge
  • Compare statistical results for different types of regression with data sets, linear, transformations of linear, and multiple linear regressions
  • Utilize mathematics, statistics, and probability for data science methodologies to derive insights

Course focus:

  • Linear regression
  • Modeling with data
  • Big Data

Tuition

‍Upfront - Save 9%

$4,700

‍Pay as You Go

$5,200

3 monthly payments of $1,733

FAQs

Can I study part-time while keeping my current job?

Yes. The AI & Data Science Certificate (Part-Time) is designed exactly for this. At 20 hours per week over 15 months, you can stay fully employed while building AI fluency at a sustainable pace. It’s built for working professionals who want to upskill into AI and add technical depth to an existing career without stepping away from their current role.

How does the apprenticeship work in work-integrated programs?

Flatiron facilitates the employer match. You’ll work approximately 20 hours per week in a production-aligned environment alongside your coursework. Apprenticeships are paid and supervised by a workplace supervisor.

How do I know if I qualify for the Accelerated track?

If you have production coding experience – frontend, backend, or full-stack, and you feel the pressure of AI reshaping what it means to be a strong engineer, you likely qualify. This isn’t a beginner course; it’s a rigorous upskilling path for engineers who don’t want to lose momentum. Speak with an Admissions rep to confirm. If you don’t have that background, the Work-Integrated: AI Engineering Immersive is the right work-integrated option for you.

Do I need prior experience to apply?

Most programs have no prerequisites. You just need to be 18+, have a high school diploma or equivalent, and have English proficiency. Whether you’re a recent grad, someone transitioning from a non-technical field, or a working professional looking to pivot, you’re eligible. The one exception is the Accelerated AI Engineering Immersive, which requires existing software engineering experience (midlevel or higher) because it’s built for engineers who are already in production environments.

What’s the difference between a certificate program and a work-integrated program?

Certificate programs are purely educational. You learn, build a portfolio, and graduate ready for the job search. If you’re entering the workforce or transitioning from a non-technical field and want a clear, structured path, this is for you. Work-integrated programs combine coursework with a paid apprenticeship, so you gain work experience and income during the program. This is a strong fit for professionals who need income continuity during a pivot, or experienced engineers who want production AI exposure from day one. Both award the same professional certificate upon completion.

Still have questions?

Our team is here to help.

Not sure where you fit? We’re here to help.

Schedule a call with our Admissions team to get guidance on our programs and find a path that will help you reach your goals.