| Attribute | Detail |
|---|---|
| Format | Online (e-LMS) |
| Level | Advanced |
| Duration | 3 Weeks |
| Certification | e-Certification + e-Marksheet |
| Fee | ₹4249 / $56 |
| Tools | MyFitnessPal USDA FoodData Central NutriSurvey Open-access APIs |
About the AI in Nutrition and Dietetics Course
AI in Nutrition and Dietetics is a specialized 3-weeks online course designed to empower dietitians, nutritionists, healthcare professionals, and tech-savvy learners to integrate artificial intelligence into nutrition science.
The course focuses on AI-powered tools for personalized diet planning, dietary data analysis, food tracking technologies, and predictive health risk assessments. Learners will explore real-world use cases, emerging AI trends, and ethical concerns surrounding AI in healthcare and nutrition practices.
Program Highlights
• Comprehensive coverage of AI in Nutrition and Dietetics from fundamentals to advanced applications
• Hands-on projects and real-world case studies in AI in Healthcare
• Expert-curated curriculum aligned with current industry standards
• Access to recorded lectures and e-LMS platform for flexible, self-paced learning
• e-Certification and e-Marksheet upon successful completion
• Dedicated mentor support and interactive doubt-clearing sessions
• Practical experience with tools: MyFitnessPal, USDA FoodData Central, NutriSurvey, Open-access APIs
• Career-oriented training for academic and professional growth in AI in Healthcare
Course Curriculum
Module 1: Foundations of AI in Nutrition
- Introduce Artificial Intelligence and Machine Learning fundamentals
- Overview nutrition science and current digital transformation trends
- Understand food databases, nutritional biomarkers, and structured dietary data
Module 2: AI Applications in Diet Planning
- Explore how AI builds personalized meal plans using medical, lifestyle, and genetic inputs
- Apply NLP and image recognition in food tracking and meal logging apps
- Analyze real-time feedback systems for nutrition coaching and smart assistants
Module 3: Advanced Food Tracking Technologies
- Discuss case studies in sports nutrition, pediatric nutrition, and metabolic disorders
- Examine the role of open-access APIs in dietary data collection
- Utilize tools like MyFitnessPal and USDA FoodData Central for data acquisition
Module 4: Predictive Analytics for Health Risks
- Build predictive models for obesity, diabetes, and cardiovascular risk
- Interpret microbiome and nutrigenomics data using deep learning
- Assess the impact of AI on various health outcomes
Module 5: Ethical Considerations & Implementation
- Address data privacy, consent, and ethical issues in AI-led health personalization
- Review regulatory frameworks surrounding AI in healthcare
- Discuss responsible AI development and deployment in nutrition
Module 6: Capstone Project: AI Recommendation Model
- Develop a prototype recommendation model using dummy health data
- Present your AI solution for a specific nutritional challenge
- Receive feedback and refine your project based on expert guidance
Tools, Techniques, or Platforms Covered
MyFitnessPal USDA FoodData Central NutriSurvey Open-access APIs
Real-World Applications
- Apply AI in Nutrition and Dietetics skills directly to academic research, thesis work, and publications
- Build a professional portfolio showcasing practical AI in Healthcare competencies
- Solve industry-relevant problems using AI in Nutrition and Dietetics methodologies and tools
- Contribute to open-source projects and collaborative research in AI in Healthcare
- Prepare for competitive examinations, interviews, and professional certifications in AI in Healthcare
Who Should Attend & Prerequisites
- Industry-recognized e-Certification + e-Marksheet from NSTC
- Hands-on training with practical projects and industrial datasets
- Dedicated expert mentorship and doubt resolution
Certification
