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Lead Instructor: Professor Dr. Emdad Khan (CEO, InternetSpeech Inc. USA)
Co-Instructor: Md. Ridoy Sarkar (Lecturer, Daffodil International University)
⏱ Duration: 10 Weeks | 48 Hours (Total)
This course is designed to bridge the critical gap between technical AI skills and business value creation. Moving beyond experimental models, this program equips professionals to architect, govern, and scale AI solutions across large organizations. It focuses on integrating AI with legacy systems (ERP, CRM), ensuring compliance, and optimizing ROI for sustainable business transformation.
With the rapid rise of AI and Digital Transformation, organizations are moving beyond experimental AI models to scalable, governed enterprise solutions. There is a critical gap for professionals who can bridge technical AI skills (Data Science, LLMs) with business value creation (ROI, Compliance, Integration). Industry demands architects who can deploy AI across supply chains, HR, and finance at scale.
The purpose of this course is to equip students with the skills to architect, govern, and scale AI solutions in large organizations. Objectives:
Tentative Syllabus:
Note: Practical assessments constitute approximately 70% of the course grade.
Upon completion, students will be able to:
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⏱ Duration: 6 Weeks | 24 Contact Hours (Blended: Online Lectures + In-person/Virtual Labs)
The global AI in Healthcare market is currently experiencing explosive growth, creating a massive skills gap in the intersection of medicine and technology. Hospitals, diagnostic centers, and HealthTech startups are actively seeking specialized engineers who can analyze complex medical data—such as MRI, CT scans, and X-Rays—using Artificial Intelligence.
This skill set is becoming critical for the modern telemedicine and automated diagnostics industry, particularly for tasks such as the automated detection of tumors, pneumonia, and other pathologies. Despite the high demand, there is a scarcity of professionals capable of bridging the technical gap between traditional biomedical engineering and modern machine learning implementation.
This course is designed to bridge the gap between Biomedical Engineering and Artificial Intelligence, equipping learners with the ability to build automated diagnostic systems.
The course aims to:
This course follows a structured week-by-week progression from foundational image handling to advanced Deep Learning deployment.
Week 1: Introduction & Image Handling
Week 2: Preprocessing Techniques
Week 3: Image Segmentation
Week 4: Feature Extraction & ML Classifiers
Week 5: Deep Learning in Medical Imaging
Week 6: Capstone Project & Showcase
After completing the course, participants will be able to:
After completing this micro-credential, learners may progress to roles such as:
Tools, Instruments & Materials
The following discounts currently apply:
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