All lesson plans and syllabi are subject to change based upon program choice.
Upon completing the program, you’ll receive a diploma that validates your expertise as a Machine Learning Specialist.
This program requires a set number of clock hours to complete.
$25 application fee
No SAT/ACT
No essay required
Launch your career in one of today’s most in-demand fields with the Machine Learning Specialist program at DSDT College. Offered through both traditional classroom and flexible distance education, this program delivers a comprehensive, hands-on education in artificial intelligence and data science. Students build essential skills in programming, natural language processing (NLP), and machine learning techniques, preparing them for exciting opportunities in AI engineering and beyond.
The Machine Learning Specialist program offers an extensive and immersive learning experience tailored to prepare students for a successful career in the dynamic field of AI language model engineering. This curriculum encompasses a broad range of critical topics, ensuring a solid foundation in Programming, Natural Language Processing (NLP), Machine Learning, Data Analysis, Data Visualization, API Integration, Version Control, Experimentation and Evaluation, Optimization Techniques, and Software Development Best Practices. Through a combination of theoretical instruction and practical, hands-on exercises, students will develop a comprehensive understanding and skill set in prompt engineering, empowering them to address real-world challenges and excel in their professional endeavors
To prepare students for post-program success by providing a rich learning environment utilizing researchbased methods of instruction and providing access to relevant and current resources and materials. Students will participate in a challenging and worthwhile Certificate of Completion program based on current industry/academic expectations. The Machine Learning Specialist Program will provide students with a roadmap to gainful employment by instruction in 7.5 courses.
Morning Schedule
Monday–Wednesday | 9:00 AM–3:40 PM ET
Note: Your live lecture will last approximately 2–3 hours and may be scheduled at any time within this window. The remaining time is reserved for coursework, labs, and instructor support.
Evening Schedule
Monday–Thursday | 4:30–9:30 PM ET
Note: Your live lecture will last approximately 2–3 hours and may be scheduled at any time within this window. The remaining time is reserved for coursework, labs, and instructor support.
Please refer to the Student Handbook, located under the Admissions & Tuition tab, for grading policies.
Python, TensorFlow, Flask, Google Colab, Databricks, Jupyter Notebooks, Visual Studio Code, Github, Scikit-Learn, Matplotlib, Seaborn, Optuna, Pandas, Keras, Numpy, SQL, Kaggle, Google Sheets, Microsoft Office 365, and Populi
7 months
80 Total Hours: Theory 50 / Laboratory 30 / Externship 0
Prerequisite: None
The AI Programming I course is designed to provide students with an introductory understanding of Machine Learning, as well as how to write in computer programming language for writing scripts that are supplemental to artificial intelligence. Over the course of four weeks, participants will learn the fundamentals of how we create AI models, with a particular focus on how to write Python scripts to automate various tasks with AI. The curriculum is structured to address the skills necessary for a machine learning professional, ensuring that students gain practical knowledge through virtual labs and hands-on exercises.
80 Total Hours: Theory 50 / Laboratory 30 / Externship 0
Prerequisite: MLS-100
The AI Programming II course is designed to continue student understanding of computer programming for writing scripts that are supplemental to artificial intelligence. Over the course of four weeks, participants will gain a deeper understanding of how to write more complex Python scripts to automate various tasks with AI. The curriculum is structured to address the skills necessary for a machine learning professional, ensuring that students gain practical knowledge through virtual labs and hands-on exercises.
80 Total Hours: Theory 50 / Laboratory 30 / Externship 0
Prerequisite: MLS-100, MLS-101
The Machine Learning Fundamentals I course is designed to introduce students to the utilization of Machine Learning rather than just traditional programming. Over the course of four weeks, participants will gain a deeper understanding of how to effectively plan a script to create and train a machine learning model when traditional scripting is insufficient. The curriculum is structured to address the skills necessary for a machine learning professional, ensuring that students gain practical knowledge through virtual labs and hands-on exercises.
80 Total Hours: Theory 50 / Laboratory 30 / Externship 0
Prerequisite: MLS-100, MLS-101
The Data Science course is designed to introduce students to the importance of and implementation of data engineering techniques. Over the course of four weeks, participants will gain a deeper understanding of how to effectively collect, evaluate, and transform data for use in training a ML model. The curriculum is structured to address the skills necessary for a machine learning professional, ensuring that students gain practical knowledge through virtual labs and hands-on exercises.
80 Total Hours: Theory 50 / Laboratory 30 / Externship 0
Prerequisite: MLS-100, MLS-101, MLS-102, MLS-103
The Machine Learning Fundamentals II course is designed to introduce students to the implementation of Machine Learning. Over the course of four weeks, participants will gain a deeper understanding of how to effectively write a script to create and train a machine learning model when traditional scripting is insufficient. The curriculum is structured to address the skills necessary for a machine learning professional, ensuring that students gain practical knowledge through virtual labs and hands-on exercises.
80 Total Hours: Theory 50 / Laboratory 30 / Externship 0
Prerequisite: MLS-100, MLS-101, MLS-102, MLS-103
The Advanced Machine Learning course is designed to introduce students to the utilization and implementation of Artificial Neural Networks for Deep Learning. Over the course of four weeks, participant will gain a deeper understanding of how to effectively write a script to create and train a deep learning model when traditional scripting is insufficient and traditional algorithms are inefficient. The curriculum is structured to address the skills necessary for a machine learning professional, ensuring that students gain practical knowledge through virtual labs and hands-on exercises.
80 Total Hours: Theory 50 / Laboratory 30 / Externship 0
Prerequisite: MLS-100, MLS-101, MLS-102, MLS-103
The Practical AI course is designed to round out student understanding of how AI models are implemented in production. Over the course of four weeks, participants will gain a hands on understanding of how to design a functional database, how an ETL (data) pipeline works in practice, how data should be pre-processed in practice before finally being used to train the model, security considerations for AI, and how deploy a ML model to the web. The curriculum is structured to address the skills necessary for a machine learning professional, ensuring that students gain practical knowledge through virtual labs and hands-on exercises.
40 Total Hours: Theory 40 / Laboratory 0 / Externship 0
Prerequisite: None
The course focuses on job-readiness skills, professional soft skills, and health & safety practices. It ensures that students not only excel technically in their roles but also understand how to navigate the job market, maintain a professional work attitude, communicate effectively, and prioritize their health and safety in a workplace setting.
A basic understanding of technology is recommended, but no prior experience is needed to enroll.
Personal Computer with stable access to internet (highly recommended)
8-16GB USB Flash Drive or Portable USB or FireWire Hard Drive and Dropbox account (Highly recommended)
Notebook and/or sketch book
Check out our schedule to find available class times that fit your routine. Your academic counselor will assist you in planning your courses for the Machine Learning Specialist program.
The estimated total cost of attending school for a specific period, including tuition, fees, housing, food, books, transportation, and other related expenses.
Submit a Free Application for Federal Student Aid (FAFSA) to explore grant funding opportunities. Use our school code 042752 to ensure your application is properly processed.
Attendance on a daily basis is a mandatory requirement for all students. Any class session or activity missed, regardless of cause, reduces the opportunity for learning and may adversely affect a student’s achievement. Students are responsible to instructors for class attendance and for any class work missed during an absence. Student is responsible to catch up on the missing material on his/her own by contacting fellow classmates or instructor.
Embark on a rewarding career path with a Machine Learning Specialist Diploma, where your skills in data-driven decision-making and AI development are in high demand. This program opens doors to exciting roles that shape the future of technology and innovation.
Embarking on your degree is a significant decision, and we aim to streamline your application process by removing any obstacles.
DSDT is accredited by the Commission of the Council on Occupational Education.
