20 Months*

Machine Learning

The Machine Learning diploma program provides an industry-aligned education that focuses on building machine learning models that can be used for predicting, making decisions, and enhancing human capabilities. This program focuses on utilizing a variety of tools, applications, and platforms to create algorithms and complex data structures that can be applied to actual business needs and real-world challenges.

_{*Program length may be extended depending on holiday and break schedules.}

Upon successful completion of the Machine Learning program, graduates will have the skills necessary for an entry-level position in the Machine Learning and Data Analytics fields. Example job titles of graduates from this program are Machine Learning Engineer, Data Analyst Computer Programmer, Computer Programmer Analyst.

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Next Start Date:

Jan 6, 2025

To build a strong programming foundation, students start by learning essential programming concepts such as variables, functions, conditionals, and control flow in the C programming language. Then, they deepen their knowledge by exploring language-specific concepts in:

Python

JavaScript

What You'll Learn in Machine Learning

Machine Learning

Use neural networks to create supervised machine learning models for tasks such as classification and clustering.

Artificial Intelligence (AI)

Develop AI applications using neural networks, computer vision, and natural language processing to identify and solve real-world problems.

Data Structures and Algorithms

Learn and apply various fundamental data structures and algorithms, such as queues, stacks, sorting algorithms, searching algorithms, and binary trees, to solve problems efficiently.

Defensive Coding

Learn to develop robust tests to ensure your code functions as intended and apply defensive coding techniques to prevent user-input errors from causing program failures.

Data Life-Cycle

Identify large data sets, use preprocessing algorithms for the data, and use it in data models.

Data Analytics

Understand the importance of data in decision-making and create visualizations from data model results to inform useful decisions.

Mathematics for Machine Learning

Utilize linear algebra, calculus, and statistics in machine learning models and data visualization.

Practical Applications

Apply your machine learning and deep learning skills to solve real-world problems and present your findings to the class.

Durable Skills

Enhance your technical communication skills, develop modern workspace skills like active listening, conflict resolution, and team building, and utilize project management skills such as planning, sharing project creation, and task delegation.

Deep Learning: Natural Language Processing

Use neural networks for natural language processing tasks, including text preprocessing.

Deep Learning:
Computer Vision

Train convolutional neural networks for tasks related to computer vision.

Deep Learning: Advanced Topics

Explore pioneering topics in machine learning and deep learning.

Problem Solving

Cultivate critical thinking by breaking down problems into core components (inputs, processes, and outputs) and develop coding solutions for real-world scenarios.

Capstone

Collaborate with a team of peers to ideate, pitch, build, and present a fully developed application within time and scoping constraints. The program culminates in a Capstone project where you showcase your minimum viable product (MVP) to peers, family, and potential employers.

Portfolio Development

Portfolios will include a resume, cover letter template, a LinkedIn profile showcasing experience and accomplishments, a tailored GitHub profile highlighting completed projects and applications, and a personal website.

Upon successful completion of the program, graduates will have a comprehensive portfolio highlighting their learned skills, programming language proficiencies, and software tools used throughout the program.

Preparing Students with Workforce-Ready Skills

Durable Skills

Develop essential skills including active listening, conflict resolution, problem solving, adaptability, and team building.

Effective Communication

Enhance your ability to communicate technical topics through written, online, and verbal communication.

Project Management

Utilize project management skills such as project planning, sharing responsibility of project creation, cooperation, and effective task delegation.

Career Planning

Learn essential job search strategies including researching companies, preparing for technical and behavioral interviews, and negotiating salaries and benefits.

Portfolio Building

Upon successful completion of a program, students will have a comprehensive collection of projects that will showcase their skills, achievements, and experiences. Additionally, their portfolio will include a resume, cover letter, LinkedIn profile, GitHub portfolio, and a personal website.

Atlas School is an innovative software engineering school that prepares students for entry-level employment in the constantly changing technology industry.
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Machine Learning Program in Tulsa