Artificial Intelligence Foundations I

Artificial Intelligence Foundations I

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Hone your AI skills to tackle advanced machine learning, large language models, natural language processing, and neural networks.

$4,700.00 USD

$5,200.00 USD
30-Day Money-Back Guarantee

Financing and flexible payment options available. Learn more

Next Cohort Date

April 7, 2025
December 2, 2024

Program Features

Qualification

Industry Certificate

Duration

12 weeks

Commitment

20 hours weekly

Skill Level

Intermediate

Delivery

Weekly instruction, feedback and support

Start Date

First Monday of each month

Led By

Experienced industry instructors

Features

Flexible schedules and small class sizes (5 max)

Value

Affordable high quality education

Build on your foundation in AI

Career training and instruction from experienced AI specialists.

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.

The SMU x Flatiron School difference: 

  • Be mentored by a world-class AI specialist
  • Small group classes (max 5 students)
  • 100% online programs

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.

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

Program prerequisites: Artificial Intelligence Essentials.

Curriculum

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

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 

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

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

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

Tuition

Flexible small group classes are the best way to learn from top industry instructors in a fun, collaborative environment, while still getting plenty of personalized feedback.

Upfront

$4,700

Pay as You Go

$5,200

3 monthly payments of $1,734

Course Mentors

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Artificial Intelligence Foundations I FAQs

Learn more

Will I earn a certificate or some other credential when I complete the Foundations program?

Yes! Upon the completion of each program in the pathway, you will receive a Credly digital badge from SMU and a certificate from Flatiron School. Digital badges can be used in email signatures or digital resumes, and certificates can be displayed on portfolio websites and social media sites such as LinkedIn, Facebook, and Twitter.

Thousands of our community members use their program certificates and badges to demonstrate skills to potential employers — including our hiring partners — along with their LinkedIn networks. Our curriculum is powered by Flatiron School, whose programs are well-regarded by many top employers, who contribute to our curriculum, hire our community, and partner with us to train their own teams.

Can I skip the intro program and go directly to the Foundations program?

It is VERY occasionally possible to skip the essentials program and go directly to Foundations I. However, we highly recommend that most students do not skip Essentials as it covers a tremendous amount of information and skills that will be used throughout the entire career pathway program and will require some catching up if skipped.

The essentials program is still difficult and covers a ton of material that is necessary for proceeding in the following programs and won't be reviewed in  Foundations. All of the future program material will build upon the essentials.

If you would like to be considered to enter directly into the Foundations-level programs, you'll be required to submit materials demonstrating your proficiency in the materials covered in the Essentials program.

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