AI & Machine Learning Foundations

Build on your foundation in AI

Career training and instruction from experienced AI specialists

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This 12-week program takes you past the basics of data science and AI and throws you into creating your own AI models. Guided by an industry expert, you'll advanced machine learning, large language models, natural language processing, and neural networks and complete the program with a portfolio of original, industry-level projects.

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The U of U // Flatiron School difference

Be mentored by a world-class AI specialist

Small group classes (max 5 students)

100% online programs

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In this foundations program, you'll delve deep into the world of AI - creating your own AI models and utilizing data science methodologies to derive data-driven insights. We know that sounds fast, but you'll have lots of support! A dedicated industry mentor will be there the entire 12 weeks to guide you, provide direct feedback, and help you gain speed and confidence with industry software, techniques and best practices, and continue you along your AI learning journey.

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‍Upon completion of this program, you'll be able to move on to Artificial Intelligence Capstone

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Program prerequisites: Artificial Intelligence Essentials

Curriculum

Industry-approved curriculum to support your journey into data and AI

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Machine Learning with Scikit-Learn - 3 weeks

This course covers both supervised and unsupervised machine learning models. You'll learn about distance metrics and k-Nearest Neighbors for classification, recommender systems using SVD, clustering techniques like k-means, and dimensionality reduction with PCA. The course concludes with a project where you'll build and demonstrate both a supervised (k-Nearest Neighbors) and an unsupervised (k-means) learning model, showcasing your skills in classification and clustering tasks.

What you'll learn: 

• Utilize foundational machine learning modeling like decision trees and supervised learning
• Prepare data for machine learning modeling with preprocessing (feature extraction) and normalization
• Integrate mathematics, statistics, and probability for data science methodologies to derive insights 

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Natural Language Processing, Time Series and Neural Networks - 3 weeks

This course teaches skills to build advanced models, focusing on natural language processing (NLP) with techniques like text classification and vectorization, time series analysis for managing and visualizing trends, and neural networks using Keras. The course culminates in a project where you'll build and showcase three models: a language model, a time series model, and a basic neural network.

What you'll learn: 

• Develop insights from language, time, and image data using neural networks and Natural Language Processing (NLP)
• Integrate mathematics, statistics, and probability for data science methodologies to derive insights

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‍Neural Networks and Similar Models - 3 weeks

This course builds on neural network fundamentals, teaching optimization techniques like normalization and regularization. You'll explore Convolutional Neural Networks (CNNs) for image classification, Recurrent Neural Networks (RNNs) for forecasting and sequence data, and advanced models like transformers and BERT. The course concludes with a project where you'll demonstrate your expertise by building an advanced neural network application.

What you'll learn: 

• Create an advanced neural network application
• Integrate mathematics, statistics, and probability for data science methodologies to derive insights

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Large Language Models - 3 weeks

This course covers large language models (LLMs) and their practical applications. You'll learn to extract insights from text, time, and image data using neural networks and natural language processing (NLP). The course also integrates key concepts from mathematics, statistics, and probability to enhance your data and AI skills.

What you'll learn: 

• Develop insights from language, time, and image data using neural networks and Natural Language Processing (NLP)
• Integrate mathematics, statistics, and probability for data science methodologies to derive insights

Tuition

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‍Upfront - Save 9%

$4,700

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‍Pay as You Go

$5,200

3 monthly payments of $1,733