University of Southern California

How this program compares

University of Southern California's MS in Electrical and Computer Engineering - Machine Learning and Data Science Track lists about $74.6K total tuition — about 74% above the $42.9K AI master's average (87th percentile in our data). It is one of the 54% of programs in our database offered fully or partly online.

Admission Snapshot

Typical admitted student: Applicants must hold a bachelor's degree in engineering or a related field with a minimum GPA of 3.0, and should have completed coursework in mathematics, statistics, computer science, and physics.[2] International students must demonstrate English proficiency with TOEFL (80+), IELTS (6.5+), or PTE (61+).[2

About This Program

This specialized track offers a focused education on the intersection of electrical engineering and advanced data-driven intelligence. Coursework concentrates on Machine Learning and AI Engineering / Applied AI. Most students complete it in about 1.5 years.

Design and implement machine learning models for real-world engineering applications including deep learning and neural networks.

Estimated total tuition is $74.6K, above the $42.9K average for AI master's programs in our database and in the 87th percentile on cost at this level. Applicants should weigh that premium against the program's outcomes and brand.

It is one of 65 AI-related programs we track in California, of which about 37% offer an online option. On price, it comes in higher than about 75% of the California programs in our data, where typical tuition runs near $63.3K.

Graduates frequently move into roles such as Machine Learning Engineer, with reported salaries around $128,000.

Career Outcomes

Graduates of University of Southern California's MS in Electrical and Computer Engineering - Machine Learning and Data Science Track most often target Machine Learning Engineer roles, where reported compensation runs around $128,000. Its focus on Machine Learning and AI Engineering / Applied AI maps directly to how employers in engineering ai screen for specialized skills rather than generic degrees. Federal projections for this occupational area point to roughly 36% growth this decade — verify the current figure on the BLS Occupational Outlook Handbook before you rely on it.

• 1. Machine Learning Engineer
• 2. Data Scientist
• 3. AI Research Scientist
• 4. Systems Engineer (AI/ML Infrastructure)

What You'll Learn

• Design and implement machine learning models for real-world engineering applications including deep learning and neural networks
• Develop data science solutions using statistical analysis, data mining, and predictive modeling techniques
• Apply advanced mathematical and computational methods to solve complex engineering problems
• Conduct capstone or industry-sponsored projects integrating machine learning with electrical and computer engineering systems

Curriculum Highlights

The coursework includes required foundations in signal processing and software design, plus advanced electives in computer vision and speech recognition.

Top Employers

Top employers for graduates include Google, Microsoft, Meta, Amazon, Tesla, NVIDIA, and major tech and defense contractors like Lockheed Martin and Raytheon Technologies.[4

Admissions

Admission to University of Southern California's MS in Electrical and Computer Engineering - Machine Learning and Data Science Track generally expects a bachelor's degree in engineering or related field. Plan for the GRE, which this program lists as required (gre typical for engineering programs). Deadlines, testing policies and funding change year to year, so confirm the current requirements on the official program page before applying.

Application Materials

• Statement of Purpose: Required
• Letters of Recommendation: 2–3
• Resume: Required
• Official Transcripts: Required
• Application Fee: $90

Frequently Asked Questions