Boston, MA – Regus at Federal Street

101 Federal St, Suite 1900, Boston, United States, 02110

The venue is located in the heart of Boston’s Financial District on Federal Street, easily accessible by car via I‑90, I‑93, and I‑95 with numerous nearby parking garages. From Logan International Airport (BOS), a taxi or rideshare takes approximately 20–25 minutes via I‑93 North. Public transit is seamless: the 15th Street and South Station – Financial District stops on MBTA's Red, Orange, and Silver lines are within a few minutes’ walk, and multiple bus routes traverse Federal and Congress Streets.

Burlington, MA – Regus at The District

1500 District Avenue, Burlington, United States, 01803

The venue is located within The District business campus at 1500 District Avenue, easily accessed by car via I‑89 or US‑3 with free on-site parking and additional municipal lots. From Boston’s Logan International Airport (BOS), approximately 15 miles southeast, a taxi or rideshare takes 25–30 minutes via I‑93 North and I‑95 North. Public transit is served by MBTA commuter rail to South Burlington, with the Campus Parkway #2 bus running directly past the entrance—placing the venue within a short walk for attendees without cars.

Cambridge, MA – Regus at Harvard Square

One Mifflin Place, Suite 400, Cambridge, United States, 02138

The venue is ideally situated in the heart of Harvard Square at One Mifflin Place, easily accessed by car via Route 2, MA‑2A, or Memorial Drive, with pay-to-park garages and metered street spaces nearby. From Boston Logan International Airport (BOS), taxis or rideshares take approximately 25–30 minutes via I‑90 West and Cambridge Street. Alternatively, public transit offers seamless connections: take the MBTA Red Line to Harvard station, and the entrance is a 3-minute walk from the square, providing effortless access for attendees without cars.

Worcester, MA – Regus at Campus Square

370 Main Street, Worcester, United States, 01608

The venue is located in the LEED Gold–certified Campus Square building at 370 Main Street in the heart of Worcester, easily reachable by car via I‑290 or I‑90, with abundant on-site parking and municipal garages nearby. From Worcester Regional Airport (ORH), about 5 miles west, a taxi or rideshare takes 10–15 minutes via Airport Drive and Main Street. Public transit is seamless: multiple WRTA bus routes stop just outside the building, and Worcester Amtrak/MBTA train station is an easy 12-minute walk, allowing easy access without a car.

Explore Our Courses

Multimodal AI with DeepSeek: Integrating Text, Image, and Audio

 14 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level to advanced-level AI researchers, developers, and data scientists who wish to leverage DeepSeek’s multimodal capabilities for cross-modal learning, AI automation, and advanced decision-making.

By the end of this training, participants will be able to:

  • Implement DeepSeek’s multimodal AI for text, image, and audio applications.
  • Develop AI solutions that integrate multiple data types for richer insights.
  • Optimize and fine-tune DeepSeek models for cross-modal learning.
  • Apply multimodal AI techniques to real-world industry use cases.
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Multi-Modal AI Agents: Integrating Text, Image, and Speech

 21 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level to advanced-level AI developers, researchers, and multimedia engineers who wish to build AI agents capable of understanding and generating multi-modal content.

By the end of this training, participants will be able to:

  • Develop AI agents that process and integrate text, image, and speech data.
  • Implement multi-modal models such as GPT-4 Vision and Whisper ASR.
  • Optimize multi-modal AI pipelines for efficiency and accuracy.
  • Deploy multi-modal AI agents in real-world applications.
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Prompt Engineering for Multimodal AI

 14 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at advanced-level AI professionals who wish to enhance their prompt engineering skills for multimodal AI applications.

By the end of this training, participants will be able to:

  • Understand the fundamentals of multimodal AI and its applications.
  • Design and optimize prompts for text, image, audio, and video generation.
  • Utilize APIs for multimodal AI platforms such as GPT-4, Gemini, and DeepSeek-Vision.
  • Develop AI-driven workflows integrating multiple content formats.
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Building Custom Multimodal AI Models with Open-Source Frameworks

 21 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at advanced-level AI developers, machine learning engineers, and researchers who wish to build custom multimodal AI models using open-source frameworks.

By the end of this training, participants will be able to:

  • Understand the fundamentals of multimodal learning and data fusion.
  • Implement multimodal models using DeepSeek, OpenAI, Hugging Face, and PyTorch.
  • Optimize and fine-tune models for text, image, and audio integration.
  • Deploy multimodal AI models in real-world applications.
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Multimodal AI for Industrial Automation and Manufacturing

 21 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level to advanced-level industrial engineers, automation specialists, and AI developers who wish to apply multimodal AI for quality control, predictive maintenance, and robotics in smart factories.

By the end of this training, participants will be able to:

  • Understand the role of multimodal AI in industrial automation.
  • Integrate sensor data, image recognition, and real-time monitoring for smart factories.
  • Implement predictive maintenance using AI-driven data analysis.
  • Apply computer vision for defect detection and quality assurance.
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Multimodal AI for Real-Time Translation

 14 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level linguists, AI researchers, software developers, and business professionals who wish to leverage multimodal AI for real-time translation and language understanding.

By the end of this training, participants will be able to:

  • Understand the fundamentals of multimodal AI for language processing.
  • Use AI models to process and translate speech, text, and images.
  • Implement real-time translation using AI-powered APIs and frameworks.
  • Integrate AI-driven translation into business applications.
  • Analyze ethical considerations in AI-powered language processing.
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Multimodal AI for Smart Assistants and Virtual Agents

 14 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at beginner-level to intermediate-level product designers, software engineers, and customer support professionals who wish to enhance virtual assistants with multimodal AI.

By the end of this training, participants will be able to:

  • Understand how multimodal AI enhances virtual assistants.
  • Integrate speech, text, and image processing in AI-powered assistants.
  • Build interactive conversational agents with voice and vision capabilities.
  • Utilize APIs for speech recognition, NLP, and computer vision.
  • Implement AI-driven automation for customer support and user interaction.
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Multimodal AI for Healthcare

 21 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level to advanced-level healthcare professionals, medical researchers, and AI developers who wish to apply multimodal AI in medical diagnostics and healthcare applications.

By the end of this training, participants will be able to:

  • Understand the role of multimodal AI in modern healthcare.
  • Integrate structured and unstructured medical data for AI-driven diagnostics.
  • Apply AI techniques to analyze medical images and electronic health records.
  • Develop predictive models for disease diagnosis and treatment recommendations.
  • Implement speech and natural language processing (NLP) for medical transcription and patient interaction.
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Multimodal AI for Finance

 14 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level finance professionals, data analysts, risk managers, and AI engineers who wish to leverage multimodal AI for risk analysis and fraud detection.

By the end of this training, participants will be able to:

  • Understand how multimodal AI is applied in financial risk management.
  • Analyze structured and unstructured financial data for fraud detection.
  • Implement AI models to identify anomalies and suspicious activities.
  • Leverage NLP and computer vision for financial document analysis.
  • Deploy AI-driven fraud detection models in real-world financial systems.
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Human-AI Collaboration with Multimodal Interfaces

 14 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at beginner-level to intermediate-level UI/UX designers, product managers, and AI researchers who wish to enhance user experiences through multimodal AI-powered interfaces.

By the end of this training, participants will be able to:

  • Understand the fundamentals of multimodal AI and its impact on human-computer interaction.
  • Design and prototype multimodal interfaces using AI-driven input methods.
  • Implement speech recognition, gesture control, and eye-tracking technologies.
  • Evaluate the effectiveness and usability of multimodal systems.
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Multimodal AI for Content Creation

 21 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level content creators, digital artists and media professionals who wish to learn how multimodal AI can be applied to various forms of content creation.

By the end of this training, participants will be able to:

  • Use AI tools to enhance music and video production.
  • Generate unique visual art and designs with AI.
  • Create interactive multimedia experiences.
  • Understand the impact of AI on the creative industries.
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Multimodal AI in Robotics

 21 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at advanced-level robotics engineers and AI researchers who wish to utilize Multimodal AI for integrating various sensory data to create more autonomous and efficient robots that can see, hear, and touch.

By the end of this training, participants will be able to:

  • Implement multimodal sensing in robotic systems.
  • Develop AI algorithms for sensor fusion and decision-making.
  • Create robots that can perform complex tasks in dynamic environments.
  • Address challenges in real-time data processing and actuation.
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Multimodal AI for Enhanced User Experience

 21 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level UX/UI designers and front-end developers who wish to utilize Multimodal AI to design and implement user interfaces that can understand and process various forms of input.

By the end of this training, participants will be able to:

  • Design multimodal interfaces that improve user engagement.
  • Integrate voice and visual recognition into web and mobile applications.
  • Utilize multimodal data to create adaptive and responsive UIs.
  • Understand the ethical considerations of user data collection and processing.
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Multimodal AI: Integrating Senses for Intelligent Systems

 21 Hours

This instructor-led, live training in Massachusetts (online or onsite) is aimed at intermediate-level AI researchers, data scientists, and machine learning engineers who wish to create intelligent systems that can process and interpret multimodal data.

By the end of this training, participants will be able to:

  • Understand the principles of multimodal AI and its applications.
  • Implement data fusion techniques to combine different types of data.
  • Build and train models that can process visual, textual, and auditory information.
  • Evaluate the performance of multimodal AI systems.
  • Address ethical and privacy concerns related to multimodal data.
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Upcoming Courses

Multimodal AI for Enhanced User Experience

2025-08-25 9:30 am
21 hours
Burlington, MA – Regus at The District
$ 4054 (Online)
$ 5554 (Classroom)

Building Custom Multimodal AI Models with Open-Source Frameworks

2025-09-08 9:30 am
21 hours
Burlington, MA – Regus at The District
$ 4054 (Online)
$ 5554 (Classroom)

Multimodal AI for Finance

2025-09-22 9:30 am
14 hours
Burlington, MA – Regus at The District
$ 2703 (Online)
$ 3703 (Classroom)

Human-AI Collaboration with Multimodal Interfaces

2025-10-06 9:30 am
14 hours
Burlington, MA – Regus at The District
$ 2703 (Online)
$ 3703 (Classroom)

Multimodal AI for Healthcare

2025-10-20 9:30 am
21 hours
Burlington, MA – Regus at The District
$ 4054 (Online)
$ 5554 (Classroom)

Multimodal AI for Healthcare

2025-11-03 9:30 am
21 hours
Burlington, MA – Regus at The District
$ 4054 (Online)
$ 5554 (Classroom)

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