FAQs

This is an in-person program only at this time. If you’re interested in a potential future online option, please contact ProfEd@seas.harvard.edu.

Learners who attend the entire course will receive a participation certificate from Harvard John A. Paulson School of Engineering and Applied Sciences.

Learners who attend the entire program will receive a hard-copy participation certificate at the closing ceremony on Sunday, February 23, 2025.

No, this program is a non-degree professional education course. The course is not credit-bearing.

Learners who attend the entire program will receive a hard-copy certificate of participation from Harvard John A. Paulson School of Engineering and Applied Sciences as evidence of their attendance. For additional documentation needs, please contact us at ProfEd@seas.harvard.edu.

The program will be held on Harvard’s Allston Campus. Learners who purchase a seat in the program will receive a welcome email with more details about the program, including specific location(s).

Although parking will not be arranged for, or included in, this program, fee-based parking is available via daily parking permits on a first-come basis in the lots located at 114 Western Avenue, 2 Hague Street, and in the smaller lot at Travis Street; daily permits must be purchased in advance via the Harvard Online Parking Permit System (HOPPS). Hourly parking at 2 Hague Street is available on a first-come basis via the ZipBy app. For travel around campus and between Cambridge and Allston, follow this link for campus transportation options to the SEC.

Lodging is not included in the program, so participants will need to make their own lodging arrangements that suit their needs through their booking agent of choice. Nearby suggested hotels include the following:
DoubleTree Suites by Hilton Boston-Cambridge
Hotel Studio Allston
Hampton Inn & Suites Watertown-Boston

The discounted rate of $850 is available to registrants with a Harvard University affiliation (alumni, faculty, staff, students, researchers, post-docs). Contact ProfEd@seas.harvard.edu for questions about affiliation status. The non–Harvard affiliate rate is $1,250. There are no further aid packages available for this course.

Cancellation requests made through January 17, 2025, can be issued refunds in full. Cancellation requests received after January 17, 2025, are subject to a cancellation fee equal to the program fee. All requests for cancellations must be made in writing. To request a cancellation, please contact ProfEd@seas.harvard.edu. SEAS Professional Education reserves the right to decline refund requests.

For information about group purchases of 5 or more participants from an organization, contact ProfEd@seas.harvard.edu.

Professionals in AI, developers interested in practical AI applications, and advanced undergraduate and graduate students can benefit from taking this program. This program is designed for learners from all types of organizations who want to increase their individual effectiveness or who have functional responsibilities, including:

• Machine Learning Engineers
• Data Scientists
• Data Engineers
• AI/ML Research Scientists
• Natural Language Processing (NLP) Engineers
• AI/ML Product Designers or Managers
• Solutions Architects
• Data Analysts
• AI/ML Technical Program Managers
• Content Strategists
• Automation Engineers
• Innovation Strategists
• Chief Technology Officers
• Anyone interested in advanced LLMs

Yes, international participants cleared for entry into the United States are encouraged to register for the program. Please contact ProfEd@seas.harvard.edu for support on visa request letters. Please note all program components will be delivered in English language only.

Learners are highly encouraged to come into the program with the following knowledge:

• Programming Skills
  • Proficiency in Python is essential, as the workshop includes extensive coding exercises and API implementations
  • Familiarity with frameworks like PyTorch or TensorFlow
• Core Knowledge in AI and Machine Learning
  • Understanding of basic concepts in AI and machine learning, including supervised learning, unsupervised learning, and model evaluation metrics
  • Familiarity with natural language processing (NLP) principles
• Experience with Neural Networks
  • Prior exposure to neural network architectures, especially transformer models such as BERT or GPT, is highly recommended
• API Integration Experience
  • Basic experience using APIs in Python to interact with external services will be helpful for the hands-on components
• Optional Recommended Skills
  • Knowledge of Git and GitHub for version control
  • Familiarity with the command line for setting up environments and executing scripts

Learners are required to bring a laptop or other portable personal computing device with charging equipment. Learners will be undertaking numerous hands-on exercises during the program. Free wireless internet will be available in the classroom and in the building. Instructions on how to access the wireless network will be provided on the first day of the program.

Light refreshments will be available upon arrival on Friday evening. On Saturday and Sunday, morning beverages will be available prior to the start of sessions, though you are encouraged to seek your own breakfast prior to arrival each day. Weekend lunch and afternoon break refreshments will be provided. Dinners throughout the program are not included. Snack and beverage vending machines are also available in the building, but note the School cafeteria will be closed.

Learners seeking accommodations can disclose their needs during the registration process or by contacting ProfEd@seas.harvard.edu. 

We recommend business-casual attire, with layers for temperature control.

Harvard University welcomes individuals with disabilities to participate in its programs and activities. Learners seeking special accommodations can disclose their needs during the registration process or by contacting ProfEd@seas.harvard.edu. Requests for American Sign Language interpreters and/or CART providers should be made at least two weeks in advance, if possible. Please note that the University will make every effort to secure services, but that services are subject to availability.