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Pictured are a couple of students from cohort 6 in SF collaborating


Machine Learning

Innovate in an exciting field

Building upon the Full-Stack Software Engineering foundation, Holberton's machine learning curriculum teaches the fundamentals of an emerging and exciting field of study that has implications in almost every industry.

Students are able to continue their strong foundation in Python and learn to build complex machine learning models using Numpy, Tensorflow, and Keras for real-world applications. By the end of their studies, students will develop a machine learning project of their choosing that they will pitch, build, and present to industry professionals.

While machine learning has been around for decades, it is only within the past few years that it has truly gained traction. It is an extremely fast-paced industry, with revolutionary research being published every year. As machine learning is one of the major drivers for the fourth industrial revolution, getting involved now means that you can shape and influence the society of tomorrow.

Pictured are students from cohort 8 in San Francisco collaborating with each other during a Peer Learning Day
Pictured is a Peer Learning Day with cohort 8 in SF

Supervised and Unsupervised and Reinforcement

The Machine Learning curriculum begins with the fundamentals of neural networks and deep supervised learning using Python3's Numpy library. Starting with perceptrons and single layered neural networks, students work their way up to build out the forward and back propagation of deep feed-forward, convolutional, and recurrent neural networks from scratch.

Then, with their proficiency in the foundations of deep learning, students are introduced to the Tensorflow and Keras frameworks in which they are able to build increasingly complex deep architectures for computer vision and natural language processing applications.

Students build upon their knowledge of deep learning by diving into the realm of unsupervised learning. In this subtopic, students discover how to draw inferences from datasets where the outcome is unknown. After being introduced to the concepts of dimensionality reduction and clustering, students are able to apply their knowledge to applications such as market analysis, recommender systems, biological research, and more. To complete the trifecta of machine learning, students dig into the theories behind deep reinforcement learning and how to use them for real life applications such as autonomous driving, and game agents.

Since data is the backbone of all machine learning, our curriculum wouldn't be complete without the study of data collection and management. Students learn about SQL and NOSQL databases, how to scrape and label datasets while avoiding human bias, and how to manage large scale datasets with Pandas, Hadoop, and Google Cloud Platform.

Our curriculum is continuously evolving to focus on current trends, ensuring that students learn what is relevant and are able to evolve with the growing industry. To facilitate students' ability to keep up with such a fast paced industry, students are also asked to read multiple journal articles every week and implement these architectures, ensuring that they are able to continue their studies throughout their careers.

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Opportunities abound

As the accessibility and prevalence of machine learning increases, more industries will adopt ways to utilize this technology.

Machine-learning is a fast-evolving industry with exciting possibilities. Many tech companies including Amazon, Google, Apple, Facebook, Microsoft, and Sony are expanding into the space and companies from a diverse range of industries are also exploring the potential of machine-learning.

Career Services and Professional Growth

Utilizing what students have learned over the previous term, they now have the opportunity and support to find a professional opportunity to get hands on experience. In today's tech world, it's not enough to be good at technical skills, you need to be a clear communicator as well.

We push our students to work on their public speaking skills, to publish blog posts to online tech communities and publications, and to speak at conferences and meetups. Students will build confidence by participating in peer-driven technical interview and whiteboarding, as well as flash presentations and solidification of understandings through events and workshops to supplement students' understanding. Experience a unique exposure to guest speakers, advanced engineering tools, and relevant cultural topics in the tech industry found only at The Holberton School.

Pictured are students from cohort 6 in San Francisco collaborating with each other

Developed by working professionals

Our professional advisors are the backbone of Holberton. They provide feedback about our curriculum, are resources for our students, and are an endless source of knowledge about the most current technologies and frameworks.

Professional Advisors

Gregory Renard

Gregory Renard

Chief AI Officer

Deon Nicholas

Deon Nicholas


Clement Renault

Clement Renault


Specialize in the future

Don't just get ahead of the curve—set the curve. Our Specialization tracks prepare you for the in-demand jobs of today and the yet-to-be-invented jobs of tomorrow.

Pictured is a student from cohort 6 in San Francisco


We're here to help you take the next step. Read our Syllabus for more info, or join one of our upcoming events.