About the ML Engineering & AI Bootcamp
In today's data-driven world, artificial intelligence (AI) and machine learning (ML) are reshaping industries at an unprecedented pace. With a staggering 82% of companies actively seeking professionals with AI and ML skills, now is the perfect time to embark on a career in this exciting field. The global AI market is projected to grow at a CAGR of 38.8% from 2022 to 2029, offering immense opportunities for skilled individuals.
USF CTPE's Machine Learning and AI Bootcamp is designed to equip you with the practical skills and knowledge needed to succeed in this rapidly evolving field. From foundational ML algorithms to cutting-edge topics like large language models and generative AI, you'll gain a comprehensive understanding of the AI landscape.
Through hands-on projects and practical exercises, you'll master the entire machine learning pipeline, including data preprocessing, feature engineering, model training, deployment, and scaling. You'll also benefit from personalized 1:1 mentorship from industry experts and comprehensive career support to help you launch a successful career in AI.
Don't miss this opportunity to position yourself at the forefront of technological innovation. Join USF CTPE's Machine Learning and AI Bootcamp today.
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Careers in machine learning engineering and AI
There are a plethora of different career paths and specializations to choose from within machine learning engineering and AI. Below are possible job titles, fields and salaries that you may consider.
Machine learning engineer: $99,840
Data Scientist: $102,656
Business Intelligence Developer: $104,192
Data Engineer: $117,504
Annual Median Advertised Salary. Source: Lightcast; Dec 2023 - Nov 2024; 0-3 years minimum experience required. Florida.
Machine learning engineering and AI curriculum
The bootcamp curriculum is designed to help you land your first job. You'll develop skills in linear and logistical regression, anomaly detection, cleaning and transforming data. You'll work through real-world projects similar to the work machine learning engineers encounter daily.
Preview some of the curriculum units below:
Machine Learning Models
We’ll teach you the most in-demand machine learning models and algorithms you’ll need to know to succeed as an MLE. For each model, you will learn how it works conceptually first, then the applied mathematics necessary to implement it, and finally you will get experience training and testing the models. We’ll walk you through the best practices for predictive optimization, like hyperparameter tuning, and how to evaluate your performance. You’ll learn how to pick the right model for the challenge you are facing, and critically, how to implement and deploy these models at scale.
Algorithms for both supervised and unsupervised learning
Gauging model performance using a variety of cross-validation metrics
Using AutoML to generate baseline models
Model selection and hyperparameter tuning
Bias in models and model drift
Deep learning techniques like convolutional, and recurrent neural networks, and generative adversarial networks
Recommendation systems
Tools: Scikit-Learn, Tensorflow, Pandas, AutoML systems, AWS
Prove your skills through an end-to-end capstone project
This bootcamp has one capstone project that has been split up into two phases. Design a machine/deep learning system, build a prototype and deploy a running application that can be accessed via API or web service
Phase One: Building a working prototype
Develop your project proposal, collect your data, wrangle and explore data and create a machine learning or deep learning prototype.
Phase Two: Deploying your prototype to production
Create a deployment architecture, run your code end-to-end with testing and deploy your application to production.
Fit learning into your life with industry experts in your corner
Learn on your own time and study on your schedule. Stay on track with mentors and peers to keep you accountable.
Personal mentor with regular 1:1 video calls: Your mentor will provide feedback on projects, help you overcome blockers and give you career advice and industry insight.
Advisors: Call upon your advisor for questions regarding accountability, time management or anything else that comes up throughout the course.
1:1 career coaching sessions: These optional career units can help you navigate the stages of your job search.
Online community: Start discussions with your fellow peers about the work you're doing and receive feedback.
Meet some of our mentors
Having a personal mentor will help you build your skills faster and advance your personal growth.
Is this machine learning bootcamp right for you?
The Machine Learning Engineering and AI Bootcamp is designed for learners who are proficient in object-oriented programming (Python, Java or JavaScript). It is open to learners who are working as software engineers or data scientists and learners who have undergraduate degrees in computer science, physics, computational mathematics, statistics or a similar field. The course is also open to self-taught programmers who display a high degree of technical savvy.
During the application process, learners will take a technical skills survey (TSS) to determine their starting line:
Learners who fail to clear the TSS will be provided with Foundations units that cover Python from scratch.
Learners who clear the TSS would have access to the Foundations units but can move right into the core curriculum.
FAQ
More questions about the program?
Schedule a call with our Enrollment Team by applying now or email Carolina, our Enrollment Advisor, to aid in your decision.