AI & Machine Learning Foundations I
Delve deeper into data science with advanced data processing, regression analysis, and machine learning.
Qualification
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Skill Level
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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
FAQs
Yes. Certificate programs (Part-Time) are designed exactly for this. At 20 hours per week over 15 months, you can stay fully employed while building skills at a sustainable pace. These are built for working professionals who want to upskill and add technical depth to an existing career without stepping away from their current role.
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.
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 AI or cyber 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.
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 only exceptions are the Accelerated AI Engineering Immersive and the Accelerated Cyber Engineering Immersive which require existing software engineering experience (midlevel or higher) because they're built for engineers who are already in production environments.
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 or cyber exposure from day one. Both award the same professional certificate upon completion.
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