The Graduate Certificate in Artificial Intelligence is a cutting-edge, full-spectrum AI program that covers Artificial Intelligence from the hardware-intensive robotics side to the data/machine learning-centric software side in a highly integrated curriculum.
The robotics portion of the program covers both the hardware and electronics of robotics and software applications such as machine learning, natural language processing, and deep learning. Robotics labs are pervasive throughout the robotics courses and include continual hands-on robot building from basic electronics to fully software-integrated robotic systems.
The data science and machine learning portion of the program utilizes the latest software tools to analyze and develop comprehensive AI solutions on a wide variety of topics ranging from medicine and science to business and social media applications. As a whole, the AI certificate prepares students to enter into the AI field in any scientific, business, or research-based domain with the skills necessary to become an AI expert in that field.
All courses in the certificate program are reviewed on a quarterly basis to ensure that all material taught is current, relevant, and cutting-edge. All industry-relevant tools utilized in the program are also reviewed and updated regularly to ensure that students are job-ready when they complete the program.
At-a-glance information about this course for your convenience:
Summer Start Date:
July 3, 2023
Fall Start Date:
October 2, 2023
Winter Start Date:
January 8, 2024
Total Number of Units:
Choose from On-Ground or Hybrid & Weekend Courses (Effective from the Fall 2021 Quarter Term, our MSCS courses will be offered only during the weekends and through the University’s Learning Management System (which can be completed at home). Some courses may be structured as directed studies in which students work one-on-one with the Program Chair or other faculty.)
Click here to see admissions requirements
We understand there are countless online bootcamps and certificate programs you can choose from. Here’s what sets our program apart from the competition.
Entire AI Spectrum
Our program covers the entire AI spectrum from hardware (robotics) through software (data-science).
Our graduate cert program integrates machine and deep learning throughout the AI spectrum.
Students will utilize the latest set of AI tools and products on the market in this program.
Our curriculum is updated on a quarterly basis ensuring the content is cutting-edge and up to par with what is currently going on in the industry.
Our program is highly hands-on with frequent labs and activities including robot building.
Basic Components are Covered
All courses cover basic topics so that anyone can do well in the program, even without an AI or computer science background.
Key Program Highlights:
Interested in discovering how you’ll learn in the classroom?
1. Applied Practice
Engage in hands-on labs designed to provide direct, experiential learning of AI and Machine Learning tools.
2. Tech Visits
Participate in field trips to local technology companies, immersing you in real-world applications of AI and Machine Learning.
3. Academic Rigor
Delve into traditional graduate-level academics with a special focus on artificial intelligence and machine learning theories.
4. Research Endeavors
Contribute to the field with significant research and writing projects, fostering critical thinking in AI & Machine Learning.
5. Community Connections
Enhance your professional network by interacting with graduate students in the tech hubs of Silicon Valley and Southern California.
6. Software Creation
Gain practical experience in computer program development, a vital skill in the AI and Machine Learning industry.
Meet the Instructor:
Dr. Donna Dulo
Learn more about the instructor for this program:
Dr. Donna Dulo
Program Chair for Computer Science Department
Dr. Dulo has extensive experience in the field of aerospace software safety engineering and aviation cybersecurity and is an expert in drone systems engineering and drone/ aviation law. She retired from the Department of Defense as a computer scientist and mathematician with 34 years of combined active duty and civilian service. She writes extensively in the area of Aviation and Drone Law for the American Bar Association and wrote the seminal Drone Law book for the ABA which continues to be an authoritative legal reference.
AIE Certification Program
Our program supports students to AIE certification. The Artificial Intelligence Engineer certification is founded on the international AMDEX™ knowledge framework for career aspirants in AI.
To receive a Graduate Certificate in Artificial Intelligence, students must successfully complete a minimum of 18 units. The following are specific required courses.
This course covers the various elements of mathematics, statistics, data structures, databases, and computer science, and how they work together to provide the optimal analysis of data. The basic techniques of data science, algorithms for data mining, and basic statistical modeling are core competencies that will be studied in depth. Data science leverages all available and relevant data to effectively provide a predictive model that can be applied to real world business, engineering, and scientific problems. A major goal of data science is to make it easier for others to find and coalesce data with greater ease. Data science technologies impact how data scientists access data and conduct research across various domains, including the biological sciences, medical informatics, social sciences, and the humanities.
This course covers the foundations of artificial intelligence as a holistic discipline. Artificial intelligence (AI) is the intelligence exhibited by machines or software. Artificial intelligence covers the many aspects of how human intelligence is encoded in computer programs and mechanisms such as robots. This course introduces the foundation of simulating or creating intelligence from a computational point of view. It allows the students to gain generic problem-solving skills that have applicability to a wide range of real-world complex problems. It covers the techniques of reduction, reasoning, problem solving, search, knowledge representation, and machine learning. It also covers computational complexity and issues arising at the junction between biological and artificial intelligence.
Machine learning is a complex yet a fast-moving field with many real world commercial applications. The goal of machine learning is to build computer models that can produce useful information whether they are predictions, associations, or classifications. The ultimate goal for many machine-learning researchers is to build computing systems that can automatically adapt and learn from their experience. This course will study the theory and practical algorithms, basic concepts and paradigms, key techniques, challenges, and tricks of machine learning. It also covers examples of how machine learning is used/applied today in the real world, and exposes students to the construction and use of machine learning algorithms. This course discusses recent applications of machine learning, such as robotic control, speech recognition, face recognition, data mining, autonomous navigation, bioinformatics, and text and web data processing. It also fuses machine learning with other areas of artificial intelligence and robotics.
This course explores the computational processes and artificial intelligence basis of robotics. The integration of software and hardware systems will be emphasized through proper computational paradigms such as algorithms, automata, search structures, and data manipulation in real-time reactive systems. Coverage of electronics and electronic interfaces will provide a solid foundation on which to base artificial intelligence structures. The use of sensors and motors, as controlled by software will be covered in addition to the use of embedded and mechanical software driven systems. A special emphasis shall be placed on robot autonomy and learning through the precise use of computer algorithms and data structures. Robot sensing, analyzing, vision, and locomotion through computational structures will also be covered.
This course will provide an advanced study of the latest research and applications in artificial intelligence, machine learning, robotics, and the data science used in their applications. It will survey complex and relevant issues and will provide students with a holistic look into the advanced concepts of AI, which fuse together many areas of computer science, mathematics, and engineering. The course concludes with a comprehensive research paper that covers new and emerging areas of the fields of AI, machine learning, and robotics.
This course covers advanced robotics computing areas such as robotics programming and robot operating systems. It applies the concepts of artificial intelligence and machine learning with electrical and mechanical structures to produce functioning robots that are logically and structurally sound in both hardware and software. The course is hands-on and robots will be constructed and programmed to perform various computationally complex tasks including navigation, sensing, effecting and actuating. The course concludes with the construction of a robot that is thoroughly analyzed and tested.
Frequently Asked Questions (FAQs):
Our FAQ section provides a quick and comprehensive guide to answer your questions about Sofia University’s Dream Studies Certificate program.
Students with an undergraduate degree or higher who wish to have a graduate-level credential in a specialized area. This program is also perfect for career professionals with at least an undergraduate level degree who needs advanced knowledge in one of the specialized areas or a career professional who has a Master’s degree but needs and wants cutting-edge knowledge in an area of specialization. Individuals who want an additional credential for their resume for a promotion or new job, students with a Master’s degree who wants preparation for a doctoral program in that area of specialization or someone with at least an undergraduate degree who wants to get into the area of computer science in a specific area of specialization.
Applicants are required to have a bachelor’s degree or higher from a regionally accredited college or university or international equivalent with a minimum GPA of 3.0. Students without a background in computer science or related field (as determined by the Program Chair), will need to speak with a program chair before being accepted into the program. We highly encourage scheduling a meeting with a counselor to identify what program best suits your professional aspirations.
Students can expect to get the following skills out of the program:
- Mathematics of Artificial (Discrete Math and Statistics)
- AI Systems Development
- AI Algorithmic Development
- AI problem-solving skills, full-spectrum AI skills from hardware-based AI (Robotics, drones, self-driving cars)
- Software-based AI skills (data science, data analytics, machine learning, deep learning, natural language processing)
- Data Analytics skills
The total cost for the program is $8,460. All materials are included, and the tuition can be paid over four quarters at $2,115 each quarter.
Please talk to your dedicated admissions counselor regarding our policy on withdrawals and refunds.